x86 avx2 optimization for convolution gemm int8 (#3489)

src/layer/x86/convolution_1x1_int8.h

@@ -12,6 +12,76 @@
 // CONDITIONS OF ANY KIND, either express or implied. See the License for the
 // specific language governing permissions and limitations under the License.
 
+static void conv1x1s1_sgemm_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int h = bottom_blob.h;
+    const int size = w * h;
+
+    Mat bottom_im2col = bottom_blob;
+    bottom_im2col.w = size;
+    bottom_im2col.h = 1;
+
+    im2col_sgemm_int8_sse(bottom_im2col, top_blob, kernel, opt);
+}
+
+static void conv1x1s2_sgemm_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int channels = bottom_blob.c;
+    size_t elemsize = bottom_blob.elemsize;
+    int elempack = bottom_blob.elempack;
+
+    int outw = top_blob.w;
+    int outh = top_blob.h;
+
+    const int tailstep = w - 2 * outw + w;
+
+    Mat bottom_blob_shrinked;
+    bottom_blob_shrinked.create(outw, outh, channels, elemsize, elempack, opt.workspace_allocator);
+
+    #pragma omp parallel for num_threads(opt.num_threads)
+    for (int p = 0; p < channels; p++)
+    {
+        const signed char* r0 = bottom_blob.channel(p);
+        signed char* outptr = bottom_blob_shrinked.channel(p);
+
+        for (int i = 0; i < outh; i++)
+        {
+            int j = 0;
+            for (; j + 3 < outw; j += 4)
+            {
+                outptr[0] = r0[0];
+                outptr[1] = r0[2];
+                outptr[2] = r0[4];
+                outptr[3] = r0[6];
+
+                r0 += 8;
+                outptr += 4;
+            }
+            for (; j + 1 < outw; j += 2)
+            {
+                outptr[0] = r0[0];
+                outptr[1] = r0[2];
+
+                r0 += 4;
+                outptr += 2;
+            }
+            for (; j < outw; j++)
+            {
+                outptr[0] = r0[0];
+
+                r0 += 2;
+                outptr += 1;
+            }
+
+            r0 += tailstep;
+        }
+    }
+
+    conv1x1s1_sgemm_int8_sse(bottom_blob_shrinked, top_blob, kernel, opt);
+}
+
 static void conv1x1s1_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& _kernel, const Option& opt)
 {
     int inch = bottom_blob.c;

src/layer/x86/convolution_1x1_pack1to4_int8.h

@@ -0,0 +1,83 @@
+// Tencent is pleased to support the open source community by making ncnn available.
+//
+// Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved.
+//
+// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+// in compliance with the License. You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// Unless required by applicable law or agreed to in writing, software distributed
+// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+// CONDITIONS OF ANY KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations under the License.
+
+static void conv1x1s1_sgemm_pack1to4_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int h = bottom_blob.h;
+    const int size = w * h;
+
+    Mat bottom_im2col = bottom_blob;
+    bottom_im2col.w = size;
+    bottom_im2col.h = 1;
+
+    im2col_sgemm_pack1to4_int8_sse(bottom_im2col, top_blob, kernel, opt);
+}
+
+static void conv1x1s2_sgemm_pack1to4_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int channels = bottom_blob.c;
+    size_t elemsize = bottom_blob.elemsize;
+    int elempack = bottom_blob.elempack;
+
+    int outw = top_blob.w;
+    int outh = top_blob.h;
+
+    const int tailstep = w - 2 * outw + w;
+
+    Mat bottom_blob_shrinked;
+    bottom_blob_shrinked.create(outw, outh, channels, elemsize, elempack, opt.workspace_allocator);
+
+    #pragma omp parallel for num_threads(opt.num_threads)
+    for (int p = 0; p < channels; p++)
+    {
+        const signed char* r0 = bottom_blob.channel(p);
+        signed char* outptr = bottom_blob_shrinked.channel(p);
+
+        for (int i = 0; i < outh; i++)
+        {
+            int j = 0;
+            for (; j + 3 < outw; j += 4)
+            {
+                outptr[0] = r0[0];
+                outptr[1] = r0[2];
+                outptr[2] = r0[4];
+                outptr[3] = r0[6];
+
+                r0 += 8;
+                outptr += 4;
+            }
+            for (; j + 1 < outw; j += 2)
+            {
+                outptr[0] = r0[0];
+                outptr[1] = r0[2];
+
+                r0 += 4;
+                outptr += 2;
+            }
+            for (; j < outw; j++)
+            {
+                outptr[0] = r0[0];
+
+                r0 += 2;
+                outptr += 1;
+            }
+
+            r0 += tailstep;
+        }
+    }
+
+    conv1x1s1_sgemm_pack1to4_int8_sse(bottom_blob_shrinked, top_blob, kernel, opt);
+}

src/layer/x86/convolution_1x1_pack8to1_int8.h

@@ -0,0 +1,65 @@
+// Tencent is pleased to support the open source community by making ncnn available.
+//
+// Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved.
+//
+// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+// in compliance with the License. You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// Unless required by applicable law or agreed to in writing, software distributed
+// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+// CONDITIONS OF ANY KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations under the License.
+
+static void conv1x1s1_sgemm_pack8to1_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int h = bottom_blob.h;
+    const int size = w * h;
+
+    Mat bottom_im2col = bottom_blob;
+    bottom_im2col.w = size;
+    bottom_im2col.h = 1;
+
+    im2col_sgemm_pack8to1_int8_sse(bottom_im2col, top_blob, kernel, opt);
+}
+
+static void conv1x1s2_sgemm_pack8to1_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int channels = bottom_blob.c;
+    size_t elemsize = bottom_blob.elemsize;
+    int elempack = bottom_blob.elempack;
+
+    int outw = top_blob.w;
+    int outh = top_blob.h;
+
+    const int tailstep = w - 2 * outw + w;
+
+    Mat bottom_blob_shrinked;
+    bottom_blob_shrinked.create(outw, outh, channels, elemsize, elempack, opt.workspace_allocator);
+
+    #pragma omp parallel for num_threads(opt.num_threads)
+    for (int p = 0; p < channels; p++)
+    {
+        const int64_t* r0 = bottom_blob.channel(p);
+        int64_t* outptr = bottom_blob_shrinked.channel(p);
+
+        for (int i = 0; i < outh; i++)
+        {
+            int j = 0;
+            for (; j < outw; j++)
+            {
+                outptr[0] = r0[0];
+
+                r0 += 2;
+                outptr += 1;
+            }
+
+            r0 += tailstep;
+        }
+    }
+
+    conv1x1s1_sgemm_pack8to1_int8_sse(bottom_blob_shrinked, top_blob, kernel, opt);
+}

src/layer/x86/convolution_1x1_pack8to4_int8.h

@@ -25,7 +25,7 @@ static void conv1x1s1_sgemm_pack8to4_int8_sse(const Mat& bottom_blob, Mat& top_b
     im2col_sgemm_pack8to4_int8_sse(bottom_im2col, top_blob, kernel, opt);
 }
 
-static void conv1x1s2_pack8to4_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
+static void conv1x1s2_sgemm_pack8to4_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
 {
     int w = bottom_blob.w;
     int channels = bottom_blob.c;

src/layer/x86/convolution_3x3_pack1to4_int8.h

@@ -0,0 +1,147 @@
+// Tencent is pleased to support the open source community by making ncnn available.
+//
+// Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved.
+//
+// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+// in compliance with the License. You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// Unless required by applicable law or agreed to in writing, software distributed
+// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+// CONDITIONS OF ANY KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations under the License.
+
+static void conv3x3s1_pack1to4_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int inch = bottom_blob.c;
+
+    int outw = top_blob.w;
+    int outh = top_blob.h;
+    const int size = outw * outh;
+
+    const int maxk = 9;
+
+    // im2col
+    Mat bottom_im2col(size, maxk, inch, 1u, 1, opt.workspace_allocator);
+    {
+        const int gap = w - outw;
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int p = 0; p < inch; p++)
+        {
+            const Mat img = bottom_blob.channel(p);
+            signed char* ptr = bottom_im2col.channel(p);
+
+            for (int u = 0; u < 3; u++)
+            {
+                for (int v = 0; v < 3; v++)
+                {
+                    const signed char* sptr = img.row<const signed char>(u) + v;
+
+                    for (int i = 0; i < outh; i++)
+                    {
+                        int j = 0;
+                        for (; j + 3 < outw; j += 4)
+                        {
+                            ptr[0] = sptr[0];
+                            ptr[1] = sptr[1];
+                            ptr[2] = sptr[2];
+                            ptr[3] = sptr[3];
+
+                            sptr += 4;
+                            ptr += 4;
+                        }
+                        for (; j + 1 < outw; j += 2)
+                        {
+                            ptr[0] = sptr[0];
+                            ptr[1] = sptr[1];
+
+                            sptr += 2;
+                            ptr += 2;
+                        }
+                        for (; j < outw; j++)
+                        {
+                            ptr[0] = sptr[0];
+
+                            sptr += 1;
+                            ptr += 1;
+                        }
+
+                        sptr += gap;
+                    }
+                }
+            }
+        }
+    }
+
+    im2col_sgemm_pack1to4_int8_sse(bottom_im2col, top_blob, kernel, opt);
+}
+
+static void conv3x3s2_pack1to4_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int inch = bottom_blob.c;
+
+    int outw = top_blob.w;
+    int outh = top_blob.h;
+    const int size = outw * outh;
+
+    const int maxk = 9;
+
+    // im2col
+    Mat bottom_im2col(size, maxk, inch, 1u, 1, opt.workspace_allocator);
+    {
+        const int gap = w * 2 - outw * 2;
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int p = 0; p < inch; p++)
+        {
+            const Mat img = bottom_blob.channel(p);
+            signed char* ptr = bottom_im2col.channel(p);
+
+            for (int u = 0; u < 3; u++)
+            {
+                for (int v = 0; v < 3; v++)
+                {
+                    const signed char* sptr = img.row<const signed char>(u) + v;
+
+                    for (int i = 0; i < outh; i++)
+                    {
+                        int j = 0;
+                        for (; j + 3 < outw; j += 4)
+                        {
+                            ptr[0] = sptr[0];
+                            ptr[1] = sptr[2];
+                            ptr[2] = sptr[4];
+                            ptr[3] = sptr[6];
+
+                            sptr += 8;
+                            ptr += 4;
+                        }
+                        for (; j + 1 < outw; j += 2)
+                        {
+                            ptr[0] = sptr[0];
+                            ptr[1] = sptr[2];
+
+                            sptr += 4;
+                            ptr += 2;
+                        }
+                        for (; j < outw; j++)
+                        {
+                            ptr[0] = sptr[0];
+
+                            sptr += 2;
+                            ptr += 1;
+                        }
+
+                        sptr += gap;
+                    }
+                }
+            }
+        }
+    }
+
+    im2col_sgemm_pack1to4_int8_sse(bottom_im2col, top_blob, kernel, opt);
+}

src/layer/x86/convolution_7x7_pack1to4_int8.h

@@ -0,0 +1,80 @@
+// Tencent is pleased to support the open source community by making ncnn available.
+//
+// Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved.
+//
+// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+// in compliance with the License. You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// Unless required by applicable law or agreed to in writing, software distributed
+// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+// CONDITIONS OF ANY KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations under the License.
+
+static void conv7x7s2_pack1to4_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int inch = bottom_blob.c;
+
+    int outw = top_blob.w;
+    int outh = top_blob.h;
+    const int size = outw * outh;
+
+    const int maxk = 49;
+
+    // im2col
+    Mat bottom_im2col(size, maxk, inch, 1u, 1, opt.workspace_allocator);
+    {
+        const int gap = w * 2 - outw * 2;
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int p = 0; p < inch; p++)
+        {
+            const Mat img = bottom_blob.channel(p);
+            signed char* ptr = bottom_im2col.channel(p);
+
+            for (int u = 0; u < 7; u++)
+            {
+                for (int v = 0; v < 7; v++)
+                {
+                    const signed char* sptr = img.row<const signed char>(u) + v;
+
+                    for (int i = 0; i < outh; i++)
+                    {
+                        int j = 0;
+                        for (; j + 3 < outw; j += 4)
+                        {
+                            ptr[0] = sptr[0];
+                            ptr[1] = sptr[2];
+                            ptr[2] = sptr[4];
+                            ptr[3] = sptr[6];
+
+                            sptr += 8;
+                            ptr += 4;
+                        }
+                        for (; j + 1 < outw; j += 2)
+                        {
+                            ptr[0] = sptr[0];
+                            ptr[1] = sptr[2];
+
+                            sptr += 4;
+                            ptr += 2;
+                        }
+                        for (; j < outw; j++)
+                        {
+                            ptr[0] = sptr[0];
+
+                            sptr += 2;
+                            ptr += 1;
+                        }
+
+                        sptr += gap;
+                    }
+                }
+            }
+        }
+    }
+
+    im2col_sgemm_pack1to4_int8_sse(bottom_im2col, top_blob, kernel, opt);
+}

src/layer/x86/convolution_sgemm_pack1to4_int8.h

@@ -0,0 +1,750 @@
+// Tencent is pleased to support the open source community by making ncnn available.
+//
+// Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved.
+//
+// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+// in compliance with the License. You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// Unless required by applicable law or agreed to in writing, software distributed
+// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+// CONDITIONS OF ANY KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations under the License.
+
+static void im2col_sgemm_pack1to4_int8_sse(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    // Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator);
+
+    const int size = bottom_im2col.w;
+    const int maxk = bottom_im2col.h;
+    const int inch = bottom_im2col.c;
+
+    const int outch = top_blob.c;
+
+    // permute
+    Mat tmp;
+    if (inch >= 4)
+    {
+#if __AVX2__
+        if (size >= 4)
+            tmp.create(4 * maxk, inch / 4 + inch % 4, size / 4 + (size % 4) / 2 + size % 2, 4u, 4, opt.workspace_allocator);
+        else if (size >= 2)
+            tmp.create(2 * maxk, inch / 4 + inch % 4, size / 2 + size % 2, 4u, 4, opt.workspace_allocator);
+        else
+            tmp.create(maxk, inch / 4 + inch % 4, size, 4u, 4, opt.workspace_allocator);
+#else
+        if (size >= 2)
+            tmp.create(2 * maxk, inch / 4 + inch % 4, size / 2 + size % 2, 4u, 4, opt.workspace_allocator);
+        else
+            tmp.create(maxk, inch / 4 + inch % 4, size, 4u, 4, opt.workspace_allocator);
+#endif
+    }
+    else
+    {
+#if __AVX2__
+        if (size >= 4)
+            tmp.create(4 * maxk, inch, size / 4 + (size % 4) / 2 + size % 2, 1u, 1, opt.workspace_allocator);
+        else if (size >= 2)
+            tmp.create(2 * maxk, inch, size / 2 + size % 2, 1u, 1, opt.workspace_allocator);
+        else
+            tmp.create(maxk, inch, size, 1u, 1, opt.workspace_allocator);
+#else
+        if (size >= 2)
+            tmp.create(2 * maxk, inch, size / 2 + size % 2, 1u, 1, opt.workspace_allocator);
+        else
+            tmp.create(maxk, inch, size, 1u, 1, opt.workspace_allocator);
+#endif
+    }
+    {
+#if __AVX2__
+        int remain_size_start = 0;
+        int nn_size = size >> 2;
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int ii = 0; ii < nn_size; ii++)
+        {
+            int i = remain_size_start + ii * 4;
+
+            signed char* tmpptr = tmp.channel(i / 4);
+
+            int q = 0;
+            for (; q + 3 < inch; q += 4)
+            {
+                const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i;
+                const signed char* img1 = (const signed char*)bottom_im2col.channel(q + 1) + i;
+                const signed char* img2 = (const signed char*)bottom_im2col.channel(q + 2) + i;
+                const signed char* img3 = (const signed char*)bottom_im2col.channel(q + 3) + i;
+
+                for (int k = 0; k < maxk; k++)
+                {
+                    tmpptr[0] = img0[0];
+                    tmpptr[1] = img1[0];
+                    tmpptr[2] = img2[0];
+                    tmpptr[3] = img3[0];
+                    tmpptr[4] = img0[1];
+                    tmpptr[5] = img1[1];
+                    tmpptr[6] = img2[1];
+                    tmpptr[7] = img3[1];
+                    tmpptr[8] = img0[2];
+                    tmpptr[9] = img1[2];
+                    tmpptr[10] = img2[2];
+                    tmpptr[11] = img3[2];
+                    tmpptr[12] = img0[3];
+                    tmpptr[13] = img1[3];
+                    tmpptr[14] = img2[3];
+                    tmpptr[15] = img3[3];
+                    tmpptr += 16;
+
+                    img0 += size;
+                    img1 += size;
+                    img2 += size;
+                    img3 += size;
+                }
+            }
+            for (; q < inch; q++)
+            {
+                const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i;
+
+                for (int k = 0; k < maxk; k++)
+                {
+                    tmpptr[0] = img0[0];
+                    tmpptr[1] = img0[1];
+                    tmpptr[2] = img0[2];
+                    tmpptr[3] = img0[3];
+
+                    tmpptr += 4;
+
+                    img0 += size;
+                }
+            }
+        }
+
+        remain_size_start += nn_size << 2;
+        nn_size = (size - remain_size_start) >> 1;
+#else
+        int remain_size_start = 0;
+        int nn_size = (size - remain_size_start) >> 1;
+#endif
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int ii = 0; ii < nn_size; ii++)
+        {
+            int i = remain_size_start + ii * 2;
+
+#if __AVX2__
+            signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
+#else
+            signed char* tmpptr = tmp.channel(i / 2);
+#endif
+
+            int q = 0;
+            for (; q + 3 < inch; q += 4)
+            {
+                const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i;
+                const signed char* img1 = (const signed char*)bottom_im2col.channel(q + 1) + i;
+                const signed char* img2 = (const signed char*)bottom_im2col.channel(q + 2) + i;
+                const signed char* img3 = (const signed char*)bottom_im2col.channel(q + 3) + i;
+
+                for (int k = 0; k < maxk; k++)
+                {
+                    tmpptr[0] = img0[0];
+                    tmpptr[1] = img1[0];
+                    tmpptr[2] = img2[0];
+                    tmpptr[3] = img3[0];
+                    tmpptr[4] = img0[1];
+                    tmpptr[5] = img1[1];
+                    tmpptr[6] = img2[1];
+                    tmpptr[7] = img3[1];
+                    tmpptr += 8;
+
+                    img0 += size;
+                    img1 += size;
+                    img2 += size;
+                    img3 += size;
+                }
+            }
+            for (; q < inch; q++)
+            {
+                const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i;
+
+                for (int k = 0; k < maxk; k++)
+                {
+                    tmpptr[0] = img0[0];
+                    tmpptr[1] = img0[1];
+
+                    tmpptr += 2;
+
+                    img0 += size;
+                }
+            }
+        }
+
+        remain_size_start += nn_size << 1;
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int i = remain_size_start; i < size; i++)
+        {
+#if __AVX2__
+            signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
+#else
+            signed char* tmpptr = tmp.channel(i / 2 + i % 2);
+#endif
+
+            int q = 0;
+            for (; q + 3 < inch; q += 4)
+            {
+                const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i;
+                const signed char* img1 = (const signed char*)bottom_im2col.channel(q + 1) + i;
+                const signed char* img2 = (const signed char*)bottom_im2col.channel(q + 2) + i;
+                const signed char* img3 = (const signed char*)bottom_im2col.channel(q + 3) + i;
+
+                for (int k = 0; k < maxk; k++)
+                {
+                    tmpptr[0] = img0[0];
+                    tmpptr[1] = img1[0];
+                    tmpptr[2] = img2[0];
+                    tmpptr[3] = img3[0];
+                    tmpptr += 4;
+
+                    img0 += size;
+                    img1 += size;
+                    img2 += size;
+                    img3 += size;
+                }
+            }
+            for (; q < inch; q++)
+            {
+                const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i;
+
+                for (int k = 0; k < maxk; k++)
+                {
+                    tmpptr[0] = img0[0];
+
+                    tmpptr += 1;
+
+                    img0 += size;
+                }
+            }
+        }
+    }
+
+    #pragma omp parallel for num_threads(opt.num_threads)
+    for (int p = 0; p < outch; p++)
+    {
+        int* outptr0 = top_blob.channel(p);
+
+        int i = 0;
+#if __AVX2__
+        for (; i + 3 < size; i += 4)
+        {
+            const signed char* tmpptr = tmp.channel(i / 4);
+            const signed char* kptr0 = kernel.channel(p / 4);
+
+            int nn4 = (inch / 4) * maxk;
+            int nn1 = (inch % 4) * maxk;
+
+            __m256i _sum00_12 = _mm256_setzero_si256();
+            __m256i _sum20_32 = _mm256_setzero_si256();
+
+            if (nn4 > 0)
+            {
+                __m256i _sum10_02 = _mm256_setzero_si256();
+                __m256i _sum01_13 = _mm256_setzero_si256();
+                __m256i _sum11_03 = _mm256_setzero_si256();
+                __m256i _sum30_22 = _mm256_setzero_si256();
+                __m256i _sum21_33 = _mm256_setzero_si256();
+                __m256i _sum31_23 = _mm256_setzero_si256();
+
+                int j = 0;
+                for (; j < nn4; j++)
+                {
+                    __m128i _val0123 = _mm_loadu_si128((const __m128i*)tmpptr);
+                    __m256i _val0123_16 = _mm256_cvtepi8_epi16(_val0123);
+
+                    __m256i _val01_16 = _mm256_permute4x64_epi64(_val0123_16, _MM_SHUFFLE(1, 1, 0, 0));
+                    __m256i _val23_16 = _mm256_permute4x64_epi64(_val0123_16, _MM_SHUFFLE(3, 3, 2, 2));
+
+                    __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                    __m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
+
+                    __m256i _val10_16 = _mm256_permute4x64_epi64(_val01_16, 78);
+                    __m256i _val32_16 = _mm256_permute4x64_epi64(_val23_16, 78);
+
+                    __m256i _sl00_11 = _mm256_mullo_epi16(_val01_16, _w01_16);
+                    __m256i _sh00_11 = _mm256_mulhi_epi16(_val01_16, _w01_16);
+                    __m256i _sl10_01 = _mm256_mullo_epi16(_val10_16, _w01_16);
+                    __m256i _sh10_01 = _mm256_mulhi_epi16(_val10_16, _w01_16);
+                    __m256i _sl20_31 = _mm256_mullo_epi16(_val23_16, _w01_16);
+                    __m256i _sh20_31 = _mm256_mulhi_epi16(_val23_16, _w01_16);
+                    __m256i _sl30_21 = _mm256_mullo_epi16(_val32_16, _w01_16);
+                    __m256i _sh30_21 = _mm256_mulhi_epi16(_val32_16, _w01_16);
+
+                    _sum00_12 = _mm256_add_epi32(_sum00_12, _mm256_unpacklo_epi16(_sl00_11, _sh00_11));
+                    _sum10_02 = _mm256_add_epi32(_sum10_02, _mm256_unpacklo_epi16(_sl10_01, _sh10_01));
+                    _sum01_13 = _mm256_add_epi32(_sum01_13, _mm256_unpackhi_epi16(_sl00_11, _sh00_11));
+                    _sum11_03 = _mm256_add_epi32(_sum11_03, _mm256_unpackhi_epi16(_sl10_01, _sh10_01));
+                    _sum20_32 = _mm256_add_epi32(_sum20_32, _mm256_unpacklo_epi16(_sl20_31, _sh20_31));
+                    _sum30_22 = _mm256_add_epi32(_sum30_22, _mm256_unpacklo_epi16(_sl30_21, _sh30_21));
+                    _sum21_33 = _mm256_add_epi32(_sum21_33, _mm256_unpackhi_epi16(_sl20_31, _sh20_31));
+                    _sum31_23 = _mm256_add_epi32(_sum31_23, _mm256_unpackhi_epi16(_sl30_21, _sh30_21));
+
+                    tmpptr += 16;
+                    kptr0 += 16;
+                }
+
+                // transpose 4x8
+                {
+                    __m256i _tmp0, _tmp1, _tmp2, _tmp3;
+                    _tmp0 = _mm256_unpacklo_epi32(_sum00_12, _sum10_02);
+                    _tmp1 = _mm256_unpacklo_epi32(_sum01_13, _sum11_03);
+                    _tmp2 = _mm256_unpackhi_epi32(_sum00_12, _sum10_02);
+                    _tmp3 = _mm256_unpackhi_epi32(_sum01_13, _sum11_03);
+                    _sum00_12 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
+                    _sum10_02 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
+                    _sum01_13 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
+                    _sum11_03 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
+                }
+                {
+                    __m256i _tmp0, _tmp1, _tmp2, _tmp3;
+                    _tmp0 = _mm256_unpacklo_epi32(_sum20_32, _sum30_22);
+                    _tmp1 = _mm256_unpacklo_epi32(_sum21_33, _sum31_23);
+                    _tmp2 = _mm256_unpackhi_epi32(_sum20_32, _sum30_22);
+                    _tmp3 = _mm256_unpackhi_epi32(_sum21_33, _sum31_23);
+                    _sum20_32 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
+                    _sum30_22 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
+                    _sum21_33 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
+                    _sum31_23 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
+                }
+
+                _sum00_12 = _mm256_add_epi32(_sum00_12, _sum10_02);
+                _sum01_13 = _mm256_add_epi32(_sum01_13, _sum11_03);
+                _sum00_12 = _mm256_add_epi32(_sum00_12, _sum01_13);
+
+                _sum20_32 = _mm256_add_epi32(_sum20_32, _sum30_22);
+                _sum21_33 = _mm256_add_epi32(_sum21_33, _sum31_23);
+                _sum20_32 = _mm256_add_epi32(_sum20_32, _sum21_33);
+
+                __m256i _perm_mask = _mm256_set_epi32(6, 4, 3, 1, 7, 5, 2, 0);
+                _sum00_12 = _mm256_permutevar8x32_epi32(_sum00_12, _perm_mask);
+                _sum20_32 = _mm256_permutevar8x32_epi32(_sum20_32, _perm_mask);
+            }
+
+            __m128i _sum00 = _mm256_extracti128_si256(_sum00_12, 0);
+            __m128i _sum10 = _mm256_extracti128_si256(_sum00_12, 1);
+            __m128i _sum20 = _mm256_extracti128_si256(_sum20_32, 0);
+            __m128i _sum30 = _mm256_extracti128_si256(_sum20_32, 1);
+
+            int j = 0;
+            for (; j < nn1; j++)
+            {
+                __m128i _val01 = _mm_set_epi16(tmpptr[1], tmpptr[1], tmpptr[1], tmpptr[1], tmpptr[0], tmpptr[0], tmpptr[0], tmpptr[0]);
+                __m128i _val23 = _mm_set_epi16(tmpptr[3], tmpptr[3], tmpptr[3], tmpptr[3], tmpptr[2], tmpptr[2], tmpptr[2], tmpptr[2]);
+
+                __m128i _w0123 = _mm_set_epi16(kptr0[3], kptr0[2], kptr0[1], kptr0[0], kptr0[3], kptr0[2], kptr0[1], kptr0[0]);
+
+                __m128i _sl00 = _mm_mullo_epi16(_val01, _w0123);
+                __m128i _sh00 = _mm_mulhi_epi16(_val01, _w0123);
+                __m128i _sl10 = _mm_mullo_epi16(_val23, _w0123);
+                __m128i _sh10 = _mm_mulhi_epi16(_val23, _w0123);
+
+                _sum00 = _mm_add_epi32(_sum00, _mm_unpacklo_epi16(_sl00, _sh00));
+                _sum10 = _mm_add_epi32(_sum10, _mm_unpackhi_epi16(_sl00, _sh00));
+                _sum20 = _mm_add_epi32(_sum20, _mm_unpacklo_epi16(_sl10, _sh10));
+                _sum30 = _mm_add_epi32(_sum30, _mm_unpackhi_epi16(_sl10, _sh10));
+
+                tmpptr += 4;
+                kptr0 += 4;
+            }
+
+            _mm_storeu_si128((__m128i*)outptr0, _sum00);
+            _mm_storeu_si128((__m128i*)(outptr0 + 4), _sum10);
+            _mm_storeu_si128((__m128i*)(outptr0 + 8), _sum20);
+            _mm_storeu_si128((__m128i*)(outptr0 + 12), _sum30);
+            outptr0 += 16;
+        }
+#endif
+        for (; i + 1 < size; i += 2)
+        {
+#if __AVX2__
+            const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
+#else
+            const signed char* tmpptr = tmp.channel(i / 2);
+#endif
+            const signed char* kptr0 = kernel.channel(p);
+
+            int nn4 = (inch / 4) * maxk;
+            int nn1 = (inch % 4) * maxk;
+
+#if __AVX2__
+            __m256i _sum00_12 = _mm256_setzero_si256();
+#else
+            __m128i _sum00 = _mm_setzero_si128();
+            __m128i _sum10 = _mm_setzero_si128();
+#endif
+
+            if (nn4 > 0)
+            {
+#if __AVX2__
+                __m256i _sum10_02 = _mm256_setzero_si256();
+                __m256i _sum01_13 = _mm256_setzero_si256();
+                __m256i _sum11_03 = _mm256_setzero_si256();
+#else
+                __m128i _sum01 = _mm_setzero_si128();
+                __m128i _sum02 = _mm_setzero_si128();
+                __m128i _sum03 = _mm_setzero_si128();
+                __m128i _sum11 = _mm_setzero_si128();
+                __m128i _sum12 = _mm_setzero_si128();
+                __m128i _sum13 = _mm_setzero_si128();
+#endif
+
+                int j = 0;
+                for (; j < nn4; j++)
+                {
+#if __AVX2__
+                    __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                    __m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
+
+                    _val01_16 = _mm256_permute4x64_epi64(_val01_16, _MM_SHUFFLE(1, 1, 0, 0));
+
+                    __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                    __m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
+
+                    __m256i _val10_16 = _mm256_permute4x64_epi64(_val01_16, 78);
+
+                    __m256i _sl00_11 = _mm256_mullo_epi16(_val01_16, _w01_16);
+                    __m256i _sh00_11 = _mm256_mulhi_epi16(_val01_16, _w01_16);
+                    __m256i _sl10_01 = _mm256_mullo_epi16(_val10_16, _w01_16);
+                    __m256i _sh10_01 = _mm256_mulhi_epi16(_val10_16, _w01_16);
+
+                    _sum00_12 = _mm256_add_epi32(_sum00_12, _mm256_unpacklo_epi16(_sl00_11, _sh00_11));
+                    _sum10_02 = _mm256_add_epi32(_sum10_02, _mm256_unpacklo_epi16(_sl10_01, _sh10_01));
+                    _sum01_13 = _mm256_add_epi32(_sum01_13, _mm256_unpackhi_epi16(_sl00_11, _sh00_11));
+                    _sum11_03 = _mm256_add_epi32(_sum11_03, _mm256_unpackhi_epi16(_sl10_01, _sh10_01));
+#else
+                    // TODO use _mm_cvtepi8_epi16 on sse4.1
+                    __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                    __m128i _extval01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _val01);
+                    _val01 = _mm_unpacklo_epi8(_val01, _extval01);
+
+                    __m128i _val0 = _mm_shuffle_epi32(_val01, _MM_SHUFFLE(1, 0, 1, 0));
+                    __m128i _val1 = _mm_shuffle_epi32(_val01, _MM_SHUFFLE(3, 2, 3, 2));
+
+                    // TODO use _mm_cvtepi8_epi16 on sse4.1
+                    __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                    __m128i _extw01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w01);
+                    __m128i _w0 = _mm_unpacklo_epi8(_w01, _extw01);
+                    __m128i _w1 = _mm_unpackhi_epi8(_w01, _extw01);
+
+                    __m128i _sl00 = _mm_mullo_epi16(_val0, _w0);
+                    __m128i _sh00 = _mm_mulhi_epi16(_val0, _w0);
+                    __m128i _sl01 = _mm_mullo_epi16(_val0, _w1);
+                    __m128i _sh01 = _mm_mulhi_epi16(_val0, _w1);
+                    __m128i _sl10 = _mm_mullo_epi16(_val1, _w0);
+                    __m128i _sh10 = _mm_mulhi_epi16(_val1, _w0);
+                    __m128i _sl11 = _mm_mullo_epi16(_val1, _w1);
+                    __m128i _sh11 = _mm_mulhi_epi16(_val1, _w1);
+
+                    _sum00 = _mm_add_epi32(_sum00, _mm_unpacklo_epi16(_sl00, _sh00));
+                    _sum01 = _mm_add_epi32(_sum01, _mm_unpackhi_epi16(_sl00, _sh00));
+                    _sum02 = _mm_add_epi32(_sum02, _mm_unpacklo_epi16(_sl01, _sh01));
+                    _sum03 = _mm_add_epi32(_sum03, _mm_unpackhi_epi16(_sl01, _sh01));
+                    _sum10 = _mm_add_epi32(_sum10, _mm_unpacklo_epi16(_sl10, _sh10));
+                    _sum11 = _mm_add_epi32(_sum11, _mm_unpackhi_epi16(_sl10, _sh10));
+                    _sum12 = _mm_add_epi32(_sum12, _mm_unpacklo_epi16(_sl11, _sh11));
+                    _sum13 = _mm_add_epi32(_sum13, _mm_unpackhi_epi16(_sl11, _sh11));
+#endif
+
+                    tmpptr += 8;
+                    kptr0 += 16;
+                }
+
+#if __AVX2__
+                // transpose 4x8
+                {
+                    __m256i _tmp0, _tmp1, _tmp2, _tmp3;
+                    _tmp0 = _mm256_unpacklo_epi32(_sum00_12, _sum10_02);
+                    _tmp1 = _mm256_unpacklo_epi32(_sum01_13, _sum11_03);
+                    _tmp2 = _mm256_unpackhi_epi32(_sum00_12, _sum10_02);
+                    _tmp3 = _mm256_unpackhi_epi32(_sum01_13, _sum11_03);
+                    _sum00_12 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
+                    _sum10_02 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
+                    _sum01_13 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
+                    _sum11_03 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
+                }
+
+                _sum00_12 = _mm256_add_epi32(_sum00_12, _sum10_02);
+                _sum01_13 = _mm256_add_epi32(_sum01_13, _sum11_03);
+                _sum00_12 = _mm256_add_epi32(_sum00_12, _sum01_13);
+
+                __m256i _perm_mask = _mm256_set_epi32(6, 4, 3, 1, 7, 5, 2, 0);
+                _sum00_12 = _mm256_permutevar8x32_epi32(_sum00_12, _perm_mask);
+#else
+                // transpose 4x4
+                {
+                    __m128i _tmp0, _tmp1, _tmp2, _tmp3;
+                    _tmp0 = _mm_unpacklo_epi32(_sum00, _sum01);
+                    _tmp1 = _mm_unpacklo_epi32(_sum02, _sum03);
+                    _tmp2 = _mm_unpackhi_epi32(_sum00, _sum01);
+                    _tmp3 = _mm_unpackhi_epi32(_sum02, _sum03);
+                    _sum00 = _mm_unpacklo_epi64(_tmp0, _tmp1);
+                    _sum01 = _mm_unpackhi_epi64(_tmp0, _tmp1);
+                    _sum02 = _mm_unpacklo_epi64(_tmp2, _tmp3);
+                    _sum03 = _mm_unpackhi_epi64(_tmp2, _tmp3);
+                }
+                {
+                    __m128i _tmp0, _tmp1, _tmp2, _tmp3;
+                    _tmp0 = _mm_unpacklo_epi32(_sum10, _sum11);
+                    _tmp1 = _mm_unpacklo_epi32(_sum12, _sum13);
+                    _tmp2 = _mm_unpackhi_epi32(_sum10, _sum11);
+                    _tmp3 = _mm_unpackhi_epi32(_sum12, _sum13);
+                    _sum10 = _mm_unpacklo_epi64(_tmp0, _tmp1);
+                    _sum11 = _mm_unpackhi_epi64(_tmp0, _tmp1);
+                    _sum12 = _mm_unpacklo_epi64(_tmp2, _tmp3);
+                    _sum13 = _mm_unpackhi_epi64(_tmp2, _tmp3);
+                }
+
+                _sum00 = _mm_add_epi32(_sum00, _sum01);
+                _sum02 = _mm_add_epi32(_sum02, _sum03);
+                _sum10 = _mm_add_epi32(_sum10, _sum11);
+                _sum12 = _mm_add_epi32(_sum12, _sum13);
+
+                _sum00 = _mm_add_epi32(_sum00, _sum02);
+                _sum10 = _mm_add_epi32(_sum10, _sum12);
+#endif
+            }
+
+#if __AVX2__
+            __m128i _sum00 = _mm256_extracti128_si256(_sum00_12, 0);
+            __m128i _sum10 = _mm256_extracti128_si256(_sum00_12, 1);
+#endif
+
+            int j = 0;
+            for (; j < nn1; j++)
+            {
+                __m128i _val = _mm_set_epi16(tmpptr[1], tmpptr[1], tmpptr[1], tmpptr[1], tmpptr[0], tmpptr[0], tmpptr[0], tmpptr[0]);
+
+                __m128i _w0123 = _mm_set_epi16(kptr0[3], kptr0[2], kptr0[1], kptr0[0], kptr0[3], kptr0[2], kptr0[1], kptr0[0]);
+
+                __m128i _sl00 = _mm_mullo_epi16(_val, _w0123);
+                __m128i _sh00 = _mm_mulhi_epi16(_val, _w0123);
+
+                _sum00 = _mm_add_epi32(_sum00, _mm_unpacklo_epi16(_sl00, _sh00));
+                _sum10 = _mm_add_epi32(_sum10, _mm_unpackhi_epi16(_sl00, _sh00));
+
+                tmpptr += 2;
+                kptr0 += 4;
+            }
+
+            _mm_storeu_si128((__m128i*)outptr0, _sum00);
+            _mm_storeu_si128((__m128i*)(outptr0 + 4), _sum10);
+            outptr0 += 8;
+        }
+        for (; i < size; i++)
+        {
+#if __AVX2__
+            const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
+#else
+            const signed char* tmpptr = tmp.channel(i / 2 + i % 2);
+#endif
+            const signed char* kptr0 = kernel.channel(p);
+
+            int nn4 = (inch / 4) * maxk;
+            int nn1 = (inch % 4) * maxk;
+
+            __m128i _sum0 = _mm_setzero_si128();
+
+            if (nn4 > 0)
+            {
+                __m128i _sum1 = _mm_setzero_si128();
+                __m128i _sum2 = _mm_setzero_si128();
+                __m128i _sum3 = _mm_setzero_si128();
+
+                int j = 0;
+                for (; j < nn4; j++)
+                {
+                    // TODO use _mm_cvtepi8_epi16 on sse4.1
+                    __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                    __m128i _extval01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _val01);
+                    __m128i _val0 = _mm_unpacklo_epi8(_val01, _extval01);
+
+                    _val0 = _mm_shuffle_epi32(_val0, _MM_SHUFFLE(1, 0, 1, 0));
+
+                    // TODO use _mm_cvtepi8_epi16 on sse4.1
+                    __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                    __m128i _extw01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w01);
+                    __m128i _w0 = _mm_unpacklo_epi8(_w01, _extw01);
+                    __m128i _w1 = _mm_unpackhi_epi8(_w01, _extw01);
+
+                    __m128i _sl00 = _mm_mullo_epi16(_val0, _w0);
+                    __m128i _sh00 = _mm_mulhi_epi16(_val0, _w0);
+                    __m128i _sl01 = _mm_mullo_epi16(_val0, _w1);
+                    __m128i _sh01 = _mm_mulhi_epi16(_val0, _w1);
+
+                    _sum0 = _mm_add_epi32(_sum0, _mm_unpacklo_epi16(_sl00, _sh00));
+                    _sum1 = _mm_add_epi32(_sum1, _mm_unpackhi_epi16(_sl00, _sh00));
+                    _sum2 = _mm_add_epi32(_sum2, _mm_unpacklo_epi16(_sl01, _sh01));
+                    _sum3 = _mm_add_epi32(_sum3, _mm_unpackhi_epi16(_sl01, _sh01));
+
+                    tmpptr += 4;
+                    kptr0 += 16;
+                }
+
+                // transpose 4x4
+                {
+                    __m128i _tmp0, _tmp1, _tmp2, _tmp3;
+                    _tmp0 = _mm_unpacklo_epi32(_sum0, _sum1);
+                    _tmp1 = _mm_unpacklo_epi32(_sum2, _sum3);
+                    _tmp2 = _mm_unpackhi_epi32(_sum0, _sum1);
+                    _tmp3 = _mm_unpackhi_epi32(_sum2, _sum3);
+                    _sum0 = _mm_unpacklo_epi64(_tmp0, _tmp1);
+                    _sum1 = _mm_unpackhi_epi64(_tmp0, _tmp1);
+                    _sum2 = _mm_unpacklo_epi64(_tmp2, _tmp3);
+                    _sum3 = _mm_unpackhi_epi64(_tmp2, _tmp3);
+                }
+
+                _sum0 = _mm_add_epi32(_sum0, _sum1);
+                _sum2 = _mm_add_epi32(_sum2, _sum3);
+                _sum0 = _mm_add_epi32(_sum0, _sum2);
+            }
+
+            int j = 0;
+            for (; j < nn1; j++)
+            {
+                __m128i _val = _mm_set1_epi16(tmpptr[0]);
+
+                __m128i _w0123 = _mm_set_epi16(0, 0, 0, 0, kptr0[3], kptr0[2], kptr0[1], kptr0[0]);
+
+                __m128i _sl00 = _mm_mullo_epi16(_val, _w0123);
+                __m128i _sh00 = _mm_mulhi_epi16(_val, _w0123);
+
+                _sum0 = _mm_add_epi32(_sum0, _mm_unpacklo_epi16(_sl00, _sh00));
+
+                tmpptr += 1;
+                kptr0 += 4;
+            }
+
+            _mm_storeu_si128((__m128i*)outptr0, _sum0);
+            outptr0 += 4;
+        }
+    }
+}
+
+static void convolution_im2col_sgemm_transform_kernel_pack1to4_int8_sse(const Mat& _kernel, Mat& kernel_tm, int inch, int outch, int kernel_w, int kernel_h)
+{
+    const int maxk = kernel_w * kernel_h;
+
+    // interleave
+    // src = maxk-inch-outch
+    // dst = 4a-4b-maxk-inch/4a-outch/4b
+    Mat kernel = _kernel.reshape(maxk, inch, outch);
+    if (inch >= 4)
+        kernel_tm.create(16 * maxk, inch / 4 + inch % 4, outch / 4, (size_t)1u);
+    else
+        kernel_tm.create(4 * maxk, inch, outch / 4, (size_t)1u);
+
+    for (int q = 0; q + 3 < outch; q += 4)
+    {
+        signed char* g00 = kernel_tm.channel(q / 4);
+
+        int p = 0;
+        for (; p + 3 < inch; p += 4)
+        {
+            for (int k = 0; k < maxk; k++)
+            {
+                for (int i = 0; i < 4; i++)
+                {
+                    for (int j = 0; j < 4; j++)
+                    {
+                        const signed char* k00 = kernel.channel(q + i).row<const signed char>(p + j);
+
+                        g00[0] = k00[k];
+
+                        g00++;
+                    }
+                }
+            }
+        }
+        for (; p < inch; p++)
+        {
+            for (int k = 0; k < maxk; k++)
+            {
+                for (int i = 0; i < 4; i++)
+                {
+                    const signed char* k00 = kernel.channel(q + i).row<const signed char>(p);
+
+                    g00[0] = k00[k];
+
+                    g00++;
+                }
+            }
+        }
+    }
+}
+
+static void convolution_im2col_sgemm_pack1to4_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, int kernel_w, int kernel_h, int dilation_w, int dilation_h, int stride_w, int stride_h, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int inch = bottom_blob.c;
+
+    int outw = top_blob.w;
+    int outh = top_blob.h;
+    const int size = outw * outh;
+
+    const int maxk = kernel_w * kernel_h;
+
+    // im2col
+    Mat bottom_im2col(size, maxk, inch, 1u, 1, opt.workspace_allocator);
+    {
+        const int gap = w * stride_h - outw * stride_w;
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int p = 0; p < inch; p++)
+        {
+            const Mat img = bottom_blob.channel(p);
+            signed char* ptr = bottom_im2col.channel(p);
+
+            for (int u = 0; u < kernel_h; u++)
+            {
+                for (int v = 0; v < kernel_w; v++)
+                {
+                    const signed char* sptr = img.row<const signed char>(dilation_h * u) + dilation_w * v;
+
+                    for (int i = 0; i < outh; i++)
+                    {
+                        int j = 0;
+                        for (; j + 3 < outw; j += 4)
+                        {
+                            ptr[0] = sptr[0];
+                            ptr[1] = sptr[stride_w];
+                            ptr[2] = sptr[stride_w * 2];
+                            ptr[3] = sptr[stride_w * 3];
+
+                            sptr += stride_w * 4;
+                            ptr += 4;
+                        }
+                        for (; j + 1 < outw; j += 2)
+                        {
+                            ptr[0] = sptr[0];
+                            ptr[1] = sptr[stride_w];
+
+                            sptr += stride_w * 2;
+                            ptr += 2;
+                        }
+                        for (; j < outw; j++)
+                        {
+                            ptr[0] = sptr[0];
+
+                            sptr += stride_w;
+                            ptr += 1;
+                        }
+
+                        sptr += gap;
+                    }
+                }
+            }
+        }
+    }
+
+    im2col_sgemm_pack1to4_int8_sse(bottom_im2col, top_blob, kernel, opt);
+}

src/layer/x86/convolution_sgemm_pack8to1_int8.h

@@ -0,0 +1,839 @@
+// Tencent is pleased to support the open source community by making ncnn available.
+//
+// Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved.
+//
+// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+// in compliance with the License. You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// Unless required by applicable law or agreed to in writing, software distributed
+// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+// CONDITIONS OF ANY KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations under the License.
+
+static void im2col_sgemm_pack8to1_int8_sse(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt)
+{
+    // Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator);
+
+    const int size = bottom_im2col.w;
+    const int maxk = bottom_im2col.h;
+    const int inch = bottom_im2col.c;
+
+    const int outch = top_blob.c;
+
+    // permute
+    Mat tmp;
+#if __AVX2__
+    if (size >= 4)
+        tmp.create(4 * maxk, inch, size / 4 + (size % 4) / 2 + size % 2, 8u, 8, opt.workspace_allocator);
+    else if (size >= 2)
+        tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
+    else
+        tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
+#else
+    if (size >= 2)
+        tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
+    else
+        tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
+#endif
+    {
+#if __AVX2__
+        int remain_size_start = 0;
+        int nn_size = size >> 2;
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int ii = 0; ii < nn_size; ii++)
+        {
+            int i = remain_size_start + ii * 4;
+
+            int64_t* tmpptr = tmp.channel(i / 4);
+
+            for (int q = 0; q < inch; q++)
+            {
+                const int64_t* img0 = (const int64_t*)bottom_im2col.channel(q) + i;
+
+                for (int k = 0; k < maxk; k++)
+                {
+                    __m256i _v = _mm256_loadu_si256((const __m256i*)img0);
+                    _mm256_storeu_si256((__m256i*)tmpptr, _v);
+                    tmpptr += 4;
+                    img0 += size;
+                }
+            }
+        }
+
+        remain_size_start += nn_size << 2;
+        nn_size = (size - remain_size_start) >> 1;
+#else
+        int remain_size_start = 0;
+        int nn_size = (size - remain_size_start) >> 1;
+#endif
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int ii = 0; ii < nn_size; ii++)
+        {
+            int i = remain_size_start + ii * 2;
+
+#if __AVX2__
+            int64_t* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
+#else
+            int64_t* tmpptr = tmp.channel(i / 2);
+#endif
+
+            for (int q = 0; q < inch; q++)
+            {
+                const int64_t* img0 = (const int64_t*)bottom_im2col.channel(q) + i;
+
+                for (int k = 0; k < maxk; k++)
+                {
+                    __m128i _v = _mm_loadu_si128((const __m128i*)img0);
+                    _mm_storeu_si128((__m128i*)tmpptr, _v);
+                    tmpptr += 2;
+                    img0 += size;
+                }
+            }
+        }
+
+        remain_size_start += nn_size << 1;
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int i = remain_size_start; i < size; i++)
+        {
+#if __AVX2__
+            int64_t* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
+#else
+            int64_t* tmpptr = tmp.channel(i / 2 + i % 2);
+#endif
+
+            for (int q = 0; q < inch; q++)
+            {
+                const int64_t* img0 = (const int64_t*)bottom_im2col.channel(q) + i;
+
+                for (int k = 0; k < maxk; k++)
+                {
+                    tmpptr[0] = img0[0];
+                    tmpptr += 1;
+                    img0 += size;
+                }
+            }
+        }
+    }
+
+    int nn_outch = 0;
+    int remain_outch_start = 0;
+
+    nn_outch = outch >> 2;
+
+    #pragma omp parallel for num_threads(opt.num_threads)
+    for (int pp = 0; pp < nn_outch; pp++)
+    {
+        int p = pp * 4;
+
+        int* outptr0 = top_blob.channel(p);
+        int* outptr1 = top_blob.channel(p + 1);
+        int* outptr2 = top_blob.channel(p + 2);
+        int* outptr3 = top_blob.channel(p + 3);
+
+        int i = 0;
+#if __AVX2__
+        for (; i + 3 < size; i += 4)
+        {
+            const signed char* tmpptr = tmp.channel(i / 4);
+            const signed char* kptr0 = kernel.channel(p / 4);
+
+            int nn = inch * maxk; // inch always > 0
+
+            __m256i _sum00_11 = _mm256_setzero_si256();
+            __m256i _sum10_01 = _mm256_setzero_si256();
+            __m256i _sum02_13 = _mm256_setzero_si256();
+            __m256i _sum12_03 = _mm256_setzero_si256();
+
+            __m256i _sum04_15 = _mm256_setzero_si256();
+            __m256i _sum14_05 = _mm256_setzero_si256();
+            __m256i _sum06_17 = _mm256_setzero_si256();
+            __m256i _sum16_07 = _mm256_setzero_si256();
+
+            int j = 0;
+            for (; j < nn; j++)
+            {
+                __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                __m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
+
+                __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                __m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
+                __m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
+                __m256i _w23_16 = _mm256_cvtepi8_epi16(_w23);
+
+                __m256i _val10_16 = _mm256_permute4x64_epi64(_val01_16, 78);
+
+                __m256i _sl00_11 = _mm256_mullo_epi16(_val01_16, _w01_16);
+                __m256i _sh00_11 = _mm256_mulhi_epi16(_val01_16, _w01_16);
+                __m256i _sl10_01 = _mm256_mullo_epi16(_val10_16, _w01_16);
+                __m256i _sh10_01 = _mm256_mulhi_epi16(_val10_16, _w01_16);
+                __m256i _sl02_13 = _mm256_mullo_epi16(_val01_16, _w23_16);
+                __m256i _sh02_13 = _mm256_mulhi_epi16(_val01_16, _w23_16);
+                __m256i _sl12_03 = _mm256_mullo_epi16(_val10_16, _w23_16);
+                __m256i _sh12_03 = _mm256_mulhi_epi16(_val10_16, _w23_16);
+
+                _sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpacklo_epi16(_sl00_11, _sh00_11));
+                _sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpacklo_epi16(_sl10_01, _sh10_01));
+                _sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpacklo_epi16(_sl02_13, _sh02_13));
+                _sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpacklo_epi16(_sl12_03, _sh12_03));
+                _sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpackhi_epi16(_sl00_11, _sh00_11));
+                _sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpackhi_epi16(_sl10_01, _sh10_01));
+                _sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpackhi_epi16(_sl02_13, _sh02_13));
+                _sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpackhi_epi16(_sl12_03, _sh12_03));
+
+                __m128i _val23 = _mm_loadu_si128((const __m128i*)(tmpptr + 16));
+                __m256i _val23_16 = _mm256_cvtepi8_epi16(_val23);
+                __m256i _val32_16 = _mm256_permute4x64_epi64(_val23_16, 78);
+
+                __m256i _sl04_15 = _mm256_mullo_epi16(_val23_16, _w01_16);
+                __m256i _sh04_15 = _mm256_mulhi_epi16(_val23_16, _w01_16);
+                __m256i _sl14_05 = _mm256_mullo_epi16(_val32_16, _w01_16);
+                __m256i _sh14_05 = _mm256_mulhi_epi16(_val32_16, _w01_16);
+                __m256i _sl06_17 = _mm256_mullo_epi16(_val23_16, _w23_16);
+                __m256i _sh06_17 = _mm256_mulhi_epi16(_val23_16, _w23_16);
+                __m256i _sl16_07 = _mm256_mullo_epi16(_val32_16, _w23_16);
+                __m256i _sh16_07 = _mm256_mulhi_epi16(_val32_16, _w23_16);
+
+                _sum04_15 = _mm256_add_epi32(_sum04_15, _mm256_unpacklo_epi16(_sl04_15, _sh04_15));
+                _sum14_05 = _mm256_add_epi32(_sum14_05, _mm256_unpacklo_epi16(_sl14_05, _sh14_05));
+                _sum06_17 = _mm256_add_epi32(_sum06_17, _mm256_unpacklo_epi16(_sl06_17, _sh06_17));
+                _sum16_07 = _mm256_add_epi32(_sum16_07, _mm256_unpacklo_epi16(_sl16_07, _sh16_07));
+                _sum04_15 = _mm256_add_epi32(_sum04_15, _mm256_unpackhi_epi16(_sl04_15, _sh04_15));
+                _sum14_05 = _mm256_add_epi32(_sum14_05, _mm256_unpackhi_epi16(_sl14_05, _sh14_05));
+                _sum06_17 = _mm256_add_epi32(_sum06_17, _mm256_unpackhi_epi16(_sl06_17, _sh06_17));
+                _sum16_07 = _mm256_add_epi32(_sum16_07, _mm256_unpackhi_epi16(_sl16_07, _sh16_07));
+
+                tmpptr += 32;
+                kptr0 += 32;
+            }
+
+            // transpose 4x8
+            {
+                __m256i _tmp0, _tmp1, _tmp2, _tmp3;
+                _tmp0 = _mm256_unpacklo_epi32(_sum00_11, _sum10_01);
+                _tmp1 = _mm256_unpacklo_epi32(_sum02_13, _sum12_03);
+                _tmp2 = _mm256_unpackhi_epi32(_sum00_11, _sum10_01);
+                _tmp3 = _mm256_unpackhi_epi32(_sum02_13, _sum12_03);
+                _sum00_11 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
+                _sum10_01 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
+                _sum02_13 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
+                _sum12_03 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
+            }
+            {
+                __m256i _tmp0, _tmp1, _tmp2, _tmp3;
+                _tmp0 = _mm256_unpacklo_epi32(_sum04_15, _sum14_05);
+                _tmp1 = _mm256_unpacklo_epi32(_sum06_17, _sum16_07);
+                _tmp2 = _mm256_unpackhi_epi32(_sum04_15, _sum14_05);
+                _tmp3 = _mm256_unpackhi_epi32(_sum06_17, _sum16_07);
+                _sum04_15 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
+                _sum14_05 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
+                _sum06_17 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
+                _sum16_07 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
+            }
+
+            _sum00_11 = _mm256_add_epi32(_sum00_11, _sum10_01);
+            _sum02_13 = _mm256_add_epi32(_sum02_13, _sum12_03);
+            _sum00_11 = _mm256_add_epi32(_sum00_11, _sum02_13);
+
+            _sum04_15 = _mm256_add_epi32(_sum04_15, _sum14_05);
+            _sum06_17 = _mm256_add_epi32(_sum06_17, _sum16_07);
+            _sum04_15 = _mm256_add_epi32(_sum04_15, _sum06_17);
+
+            __m256i _perm_mask = _mm256_set_epi32(6, 3, 4, 1, 7, 2, 5, 0);
+            _sum00_11 = _mm256_permutevar8x32_epi32(_sum00_11, _perm_mask);
+            _sum04_15 = _mm256_permutevar8x32_epi32(_sum04_15, _perm_mask);
+
+            int sum[16];
+            _mm256_storeu_si256((__m256i*)sum, _sum00_11);
+            _mm256_storeu_si256((__m256i*)(sum + 8), _sum04_15);
+
+            outptr0[0] = sum[0];
+            outptr1[0] = sum[1];
+            outptr2[0] = sum[2];
+            outptr3[0] = sum[3];
+            outptr0[1] = sum[4];
+            outptr1[1] = sum[5];
+            outptr2[1] = sum[6];
+            outptr3[1] = sum[7];
+            outptr0[2] = sum[8];
+            outptr1[2] = sum[9];
+            outptr2[2] = sum[10];
+            outptr3[2] = sum[11];
+            outptr0[3] = sum[12];
+            outptr1[3] = sum[13];
+            outptr2[3] = sum[14];
+            outptr3[3] = sum[15];
+            outptr0 += 4;
+            outptr1 += 4;
+            outptr2 += 4;
+            outptr3 += 4;
+        }
+#endif
+        for (; i + 1 < size; i += 2)
+        {
+#if __AVX2__
+            const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
+#else
+            const signed char* tmpptr = tmp.channel(i / 2);
+#endif
+            const signed char* kptr0 = kernel.channel(p / 4);
+
+            int nn = inch * maxk; // inch always > 0
+
+#if __AVX2__
+            __m256i _sum00_11 = _mm256_setzero_si256();
+            __m256i _sum10_01 = _mm256_setzero_si256();
+            __m256i _sum02_13 = _mm256_setzero_si256();
+            __m256i _sum12_03 = _mm256_setzero_si256();
+#else
+            __m128i _sum00 = _mm_setzero_si128();
+            __m128i _sum01 = _mm_setzero_si128();
+            __m128i _sum02 = _mm_setzero_si128();
+            __m128i _sum03 = _mm_setzero_si128();
+            __m128i _sum10 = _mm_setzero_si128();
+            __m128i _sum11 = _mm_setzero_si128();
+            __m128i _sum12 = _mm_setzero_si128();
+            __m128i _sum13 = _mm_setzero_si128();
+#endif
+
+            int j = 0;
+            for (; j < nn; j++)
+            {
+#if __AVX2__
+                __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                __m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
+
+                __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                __m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
+                __m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
+                __m256i _w23_16 = _mm256_cvtepi8_epi16(_w23);
+
+                __m256i _val10_16 = _mm256_permute4x64_epi64(_val01_16, 78);
+
+                __m256i _sl00_11 = _mm256_mullo_epi16(_val01_16, _w01_16);
+                __m256i _sh00_11 = _mm256_mulhi_epi16(_val01_16, _w01_16);
+                __m256i _sl10_01 = _mm256_mullo_epi16(_val10_16, _w01_16);
+                __m256i _sh10_01 = _mm256_mulhi_epi16(_val10_16, _w01_16);
+                __m256i _sl02_13 = _mm256_mullo_epi16(_val01_16, _w23_16);
+                __m256i _sh02_13 = _mm256_mulhi_epi16(_val01_16, _w23_16);
+                __m256i _sl12_03 = _mm256_mullo_epi16(_val10_16, _w23_16);
+                __m256i _sh12_03 = _mm256_mulhi_epi16(_val10_16, _w23_16);
+
+                _sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpacklo_epi16(_sl00_11, _sh00_11));
+                _sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpacklo_epi16(_sl10_01, _sh10_01));
+                _sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpacklo_epi16(_sl02_13, _sh02_13));
+                _sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpacklo_epi16(_sl12_03, _sh12_03));
+                _sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpackhi_epi16(_sl00_11, _sh00_11));
+                _sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpackhi_epi16(_sl10_01, _sh10_01));
+                _sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpackhi_epi16(_sl02_13, _sh02_13));
+                _sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpackhi_epi16(_sl12_03, _sh12_03));
+#else
+                // TODO use _mm_cvtepi8_epi16 on sse4.1
+                __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                __m128i _extval01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _val01);
+                __m128i _val0 = _mm_unpacklo_epi8(_val01, _extval01);
+                __m128i _val1 = _mm_unpackhi_epi8(_val01, _extval01);
+
+                // TODO use _mm_cvtepi8_epi16 on sse4.1
+                __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                __m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
+                __m128i _extw01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w01);
+                __m128i _extw23 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w23);
+                __m128i _w0 = _mm_unpacklo_epi8(_w01, _extw01);
+                __m128i _w1 = _mm_unpackhi_epi8(_w01, _extw01);
+                __m128i _w2 = _mm_unpacklo_epi8(_w23, _extw23);
+                __m128i _w3 = _mm_unpackhi_epi8(_w23, _extw23);
+
+                __m128i _sl00 = _mm_mullo_epi16(_val0, _w0);
+                __m128i _sh00 = _mm_mulhi_epi16(_val0, _w0);
+                __m128i _sl01 = _mm_mullo_epi16(_val0, _w1);
+                __m128i _sh01 = _mm_mulhi_epi16(_val0, _w1);
+                __m128i _sl02 = _mm_mullo_epi16(_val0, _w2);
+                __m128i _sh02 = _mm_mulhi_epi16(_val0, _w2);
+                __m128i _sl03 = _mm_mullo_epi16(_val0, _w3);
+                __m128i _sh03 = _mm_mulhi_epi16(_val0, _w3);
+                __m128i _sl10 = _mm_mullo_epi16(_val1, _w0);
+                __m128i _sh10 = _mm_mulhi_epi16(_val1, _w0);
+                __m128i _sl11 = _mm_mullo_epi16(_val1, _w1);
+                __m128i _sh11 = _mm_mulhi_epi16(_val1, _w1);
+                __m128i _sl12 = _mm_mullo_epi16(_val1, _w2);
+                __m128i _sh12 = _mm_mulhi_epi16(_val1, _w2);
+                __m128i _sl13 = _mm_mullo_epi16(_val1, _w3);
+                __m128i _sh13 = _mm_mulhi_epi16(_val1, _w3);
+
+                _sum00 = _mm_add_epi32(_sum00, _mm_unpacklo_epi16(_sl00, _sh00));
+                _sum01 = _mm_add_epi32(_sum01, _mm_unpacklo_epi16(_sl01, _sh01));
+                _sum02 = _mm_add_epi32(_sum02, _mm_unpacklo_epi16(_sl02, _sh02));
+                _sum03 = _mm_add_epi32(_sum03, _mm_unpacklo_epi16(_sl03, _sh03));
+                _sum00 = _mm_add_epi32(_sum00, _mm_unpackhi_epi16(_sl00, _sh00));
+                _sum01 = _mm_add_epi32(_sum01, _mm_unpackhi_epi16(_sl01, _sh01));
+                _sum02 = _mm_add_epi32(_sum02, _mm_unpackhi_epi16(_sl02, _sh02));
+                _sum03 = _mm_add_epi32(_sum03, _mm_unpackhi_epi16(_sl03, _sh03));
+                _sum10 = _mm_add_epi32(_sum10, _mm_unpacklo_epi16(_sl10, _sh10));
+                _sum11 = _mm_add_epi32(_sum11, _mm_unpacklo_epi16(_sl11, _sh11));
+                _sum12 = _mm_add_epi32(_sum12, _mm_unpacklo_epi16(_sl12, _sh12));
+                _sum13 = _mm_add_epi32(_sum13, _mm_unpacklo_epi16(_sl13, _sh13));
+                _sum10 = _mm_add_epi32(_sum10, _mm_unpackhi_epi16(_sl10, _sh10));
+                _sum11 = _mm_add_epi32(_sum11, _mm_unpackhi_epi16(_sl11, _sh11));
+                _sum12 = _mm_add_epi32(_sum12, _mm_unpackhi_epi16(_sl12, _sh12));
+                _sum13 = _mm_add_epi32(_sum13, _mm_unpackhi_epi16(_sl13, _sh13));
+#endif
+
+                tmpptr += 16;
+                kptr0 += 32;
+            }
+
+#if __AVX2__
+            // transpose 4x8
+            {
+                __m256i _tmp0, _tmp1, _tmp2, _tmp3;
+                _tmp0 = _mm256_unpacklo_epi32(_sum00_11, _sum10_01);
+                _tmp1 = _mm256_unpacklo_epi32(_sum02_13, _sum12_03);
+                _tmp2 = _mm256_unpackhi_epi32(_sum00_11, _sum10_01);
+                _tmp3 = _mm256_unpackhi_epi32(_sum02_13, _sum12_03);
+                _sum00_11 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
+                _sum10_01 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
+                _sum02_13 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
+                _sum12_03 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
+            }
+
+            _sum00_11 = _mm256_add_epi32(_sum00_11, _sum10_01);
+            _sum02_13 = _mm256_add_epi32(_sum02_13, _sum12_03);
+            _sum00_11 = _mm256_add_epi32(_sum00_11, _sum02_13);
+
+            __m256i _perm_mask = _mm256_set_epi32(6, 3, 4, 1, 7, 2, 5, 0);
+            _sum00_11 = _mm256_permutevar8x32_epi32(_sum00_11, _perm_mask);
+
+            int sum[8];
+            _mm256_storeu_si256((__m256i*)sum, _sum00_11);
+#else
+            // transpose 4x4
+            {
+                __m128i _tmp0, _tmp1, _tmp2, _tmp3;
+                _tmp0 = _mm_unpacklo_epi32(_sum00, _sum01);
+                _tmp1 = _mm_unpacklo_epi32(_sum02, _sum03);
+                _tmp2 = _mm_unpackhi_epi32(_sum00, _sum01);
+                _tmp3 = _mm_unpackhi_epi32(_sum02, _sum03);
+                _sum00 = _mm_unpacklo_epi64(_tmp0, _tmp1);
+                _sum01 = _mm_unpackhi_epi64(_tmp0, _tmp1);
+                _sum02 = _mm_unpacklo_epi64(_tmp2, _tmp3);
+                _sum03 = _mm_unpackhi_epi64(_tmp2, _tmp3);
+            }
+            {
+                __m128i _tmp0, _tmp1, _tmp2, _tmp3;
+                _tmp0 = _mm_unpacklo_epi32(_sum10, _sum11);
+                _tmp1 = _mm_unpacklo_epi32(_sum12, _sum13);
+                _tmp2 = _mm_unpackhi_epi32(_sum10, _sum11);
+                _tmp3 = _mm_unpackhi_epi32(_sum12, _sum13);
+                _sum10 = _mm_unpacklo_epi64(_tmp0, _tmp1);
+                _sum11 = _mm_unpackhi_epi64(_tmp0, _tmp1);
+                _sum12 = _mm_unpacklo_epi64(_tmp2, _tmp3);
+                _sum13 = _mm_unpackhi_epi64(_tmp2, _tmp3);
+            }
+
+            _sum00 = _mm_add_epi32(_sum00, _sum01);
+            _sum02 = _mm_add_epi32(_sum02, _sum03);
+            _sum10 = _mm_add_epi32(_sum10, _sum11);
+            _sum12 = _mm_add_epi32(_sum12, _sum13);
+
+            _sum00 = _mm_add_epi32(_sum00, _sum02);
+            _sum10 = _mm_add_epi32(_sum10, _sum12);
+
+            int sum[8];
+            _mm_storeu_si128((__m128i*)sum, _sum00);
+            _mm_storeu_si128((__m128i*)(sum + 4), _sum10);
+#endif
+
+            outptr0[0] = sum[0];
+            outptr1[0] = sum[1];
+            outptr2[0] = sum[2];
+            outptr3[0] = sum[3];
+            outptr0[1] = sum[4];
+            outptr1[1] = sum[5];
+            outptr2[1] = sum[6];
+            outptr3[1] = sum[7];
+            outptr0 += 2;
+            outptr1 += 2;
+            outptr2 += 2;
+            outptr3 += 2;
+        }
+        for (; i < size; i++)
+        {
+#if __AVX2__
+            const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
+#else
+            const signed char* tmpptr = tmp.channel(i / 2 + i % 2);
+#endif
+            const signed char* kptr0 = kernel.channel(p / 4);
+
+            int nn = inch * maxk; // inch always > 0
+
+            __m128i _sum0 = _mm_setzero_si128();
+            __m128i _sum1 = _mm_setzero_si128();
+            __m128i _sum2 = _mm_setzero_si128();
+            __m128i _sum3 = _mm_setzero_si128();
+
+            int j = 0;
+            for (; j < nn; j++)
+            {
+                // TODO use _mm_cvtepi8_epi16 on sse4.1
+                __m128i _val = _mm_loadl_epi64((const __m128i*)tmpptr);
+                _val = _mm_unpacklo_epi8(_val, _mm_cmpgt_epi8(_mm_setzero_si128(), _val));
+
+                // TODO use _mm_cvtepi8_epi16 on sse4.1
+                __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                __m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
+                __m128i _extw01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w01);
+                __m128i _extw23 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w23);
+                __m128i _w0 = _mm_unpacklo_epi8(_w01, _extw01);
+                __m128i _w1 = _mm_unpackhi_epi8(_w01, _extw01);
+                __m128i _w2 = _mm_unpacklo_epi8(_w23, _extw23);
+                __m128i _w3 = _mm_unpackhi_epi8(_w23, _extw23);
+
+                __m128i _sl0 = _mm_mullo_epi16(_val, _w0);
+                __m128i _sh0 = _mm_mulhi_epi16(_val, _w0);
+                __m128i _sl1 = _mm_mullo_epi16(_val, _w1);
+                __m128i _sh1 = _mm_mulhi_epi16(_val, _w1);
+                __m128i _sl2 = _mm_mullo_epi16(_val, _w2);
+                __m128i _sh2 = _mm_mulhi_epi16(_val, _w2);
+                __m128i _sl3 = _mm_mullo_epi16(_val, _w3);
+                __m128i _sh3 = _mm_mulhi_epi16(_val, _w3);
+
+                _sum0 = _mm_add_epi32(_sum0, _mm_unpacklo_epi16(_sl0, _sh0));
+                _sum1 = _mm_add_epi32(_sum1, _mm_unpacklo_epi16(_sl1, _sh1));
+                _sum2 = _mm_add_epi32(_sum2, _mm_unpacklo_epi16(_sl2, _sh2));
+                _sum3 = _mm_add_epi32(_sum3, _mm_unpacklo_epi16(_sl3, _sh3));
+                _sum0 = _mm_add_epi32(_sum0, _mm_unpackhi_epi16(_sl0, _sh0));
+                _sum1 = _mm_add_epi32(_sum1, _mm_unpackhi_epi16(_sl1, _sh1));
+                _sum2 = _mm_add_epi32(_sum2, _mm_unpackhi_epi16(_sl2, _sh2));
+                _sum3 = _mm_add_epi32(_sum3, _mm_unpackhi_epi16(_sl3, _sh3));
+
+                tmpptr += 8;
+                kptr0 += 32;
+            }
+
+            // transpose 4x4
+            {
+                __m128i _tmp0, _tmp1, _tmp2, _tmp3;
+                _tmp0 = _mm_unpacklo_epi32(_sum0, _sum1);
+                _tmp1 = _mm_unpacklo_epi32(_sum2, _sum3);
+                _tmp2 = _mm_unpackhi_epi32(_sum0, _sum1);
+                _tmp3 = _mm_unpackhi_epi32(_sum2, _sum3);
+                _sum0 = _mm_unpacklo_epi64(_tmp0, _tmp1);
+                _sum1 = _mm_unpackhi_epi64(_tmp0, _tmp1);
+                _sum2 = _mm_unpacklo_epi64(_tmp2, _tmp3);
+                _sum3 = _mm_unpackhi_epi64(_tmp2, _tmp3);
+            }
+
+            _sum0 = _mm_add_epi32(_sum0, _sum1);
+            _sum2 = _mm_add_epi32(_sum2, _sum3);
+
+            _sum0 = _mm_add_epi32(_sum0, _sum2);
+
+            int sum[4];
+            _mm_storeu_si128((__m128i*)sum, _sum0);
+
+            outptr0[0] = sum[0];
+            outptr1[0] = sum[1];
+            outptr2[0] = sum[2];
+            outptr3[0] = sum[3];
+            outptr0 += 1;
+            outptr1 += 1;
+            outptr2 += 1;
+            outptr3 += 1;
+        }
+    }
+
+    remain_outch_start += nn_outch << 2;
+
+    #pragma omp parallel for num_threads(opt.num_threads)
+    for (int p = remain_outch_start; p < outch; p++)
+    {
+        int* outptr0 = top_blob.channel(p);
+
+        int i = 0;
+#if __AVX2__
+        for (; i + 3 < size; i += 4)
+        {
+            const signed char* tmpptr = tmp.channel(i / 4);
+            const signed char* kptr0 = kernel.channel(p / 4 + p % 4);
+
+            int nn = inch * maxk; // inch always > 0
+
+            __m256i _sum0_2 = _mm256_setzero_si256();
+            __m256i _sum1_3 = _mm256_setzero_si256();
+            __m256i _sum4_6 = _mm256_setzero_si256();
+            __m256i _sum5_7 = _mm256_setzero_si256();
+
+            int j = 0;
+            for (; j < nn; j++)
+            {
+                __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                __m128i _val23 = _mm_loadu_si128((const __m128i*)(tmpptr + 16));
+                __m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
+                __m256i _val23_16 = _mm256_cvtepi8_epi16(_val23);
+
+                __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                __m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
+                _w01_16 = _mm256_permute4x64_epi64(_w01_16, _MM_SHUFFLE(1, 0, 1, 0));
+
+                __m256i _sl00_10 = _mm256_mullo_epi16(_val01_16, _w01_16);
+                __m256i _sh00_10 = _mm256_mulhi_epi16(_val01_16, _w01_16);
+                __m256i _sl20_30 = _mm256_mullo_epi16(_val23_16, _w01_16);
+                __m256i _sh20_30 = _mm256_mulhi_epi16(_val23_16, _w01_16);
+
+                _sum0_2 = _mm256_add_epi32(_sum0_2, _mm256_unpacklo_epi16(_sl00_10, _sh00_10));
+                _sum1_3 = _mm256_add_epi32(_sum1_3, _mm256_unpackhi_epi16(_sl00_10, _sh00_10));
+                _sum4_6 = _mm256_add_epi32(_sum4_6, _mm256_unpacklo_epi16(_sl20_30, _sh20_30));
+                _sum5_7 = _mm256_add_epi32(_sum5_7, _mm256_unpackhi_epi16(_sl20_30, _sh20_30));
+
+                tmpptr += 32;
+                kptr0 += 8;
+            }
+
+            _sum0_2 = _mm256_add_epi32(_sum0_2, _sum1_3);
+            _sum4_6 = _mm256_add_epi32(_sum4_6, _sum5_7);
+            __m128i _sum0 = _mm256_extracti128_si256(_sum0_2, 0);
+            __m128i _sum2 = _mm256_extracti128_si256(_sum0_2, 1);
+            __m128i _sum4 = _mm256_extracti128_si256(_sum4_6, 1);
+            __m128i _sum6 = _mm256_extracti128_si256(_sum4_6, 1);
+
+            outptr0[0] = _mm_reduce_add_epi32(_sum0);
+            outptr0[1] = _mm_reduce_add_epi32(_sum2);
+            outptr0[2] = _mm_reduce_add_epi32(_sum4);
+            outptr0[3] = _mm_reduce_add_epi32(_sum6);
+            outptr0 += 4;
+        }
+#endif
+        for (; i + 1 < size; i += 2)
+        {
+#if __AVX2__
+            const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
+#else
+            const signed char* tmpptr = tmp.channel(i / 2);
+#endif
+            const signed char* kptr0 = kernel.channel(p / 4 + p % 4);
+
+            int nn = inch * maxk; // inch always > 0
+
+#if __AVX2__
+            __m256i _sum0_2 = _mm256_setzero_si256();
+            __m256i _sum1_3 = _mm256_setzero_si256();
+#else
+            __m128i _sum0 = _mm_setzero_si128();
+            __m128i _sum1 = _mm_setzero_si128();
+            __m128i _sum2 = _mm_setzero_si128();
+            __m128i _sum3 = _mm_setzero_si128();
+#endif
+
+            int j = 0;
+            for (; j < nn; j++)
+            {
+#if __AVX2__
+                __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                __m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
+
+                __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                __m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
+                _w01_16 = _mm256_permute4x64_epi64(_w01_16, _MM_SHUFFLE(1, 0, 1, 0));
+
+                __m256i _sl00_10 = _mm256_mullo_epi16(_val01_16, _w01_16);
+                __m256i _sh00_10 = _mm256_mulhi_epi16(_val01_16, _w01_16);
+
+                _sum0_2 = _mm256_add_epi32(_sum0_2, _mm256_unpacklo_epi16(_sl00_10, _sh00_10));
+                _sum1_3 = _mm256_add_epi32(_sum1_3, _mm256_unpackhi_epi16(_sl00_10, _sh00_10));
+#else
+                // TODO use _mm_cvtepi8_epi16 on sse4.1
+                __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                __m128i _extval01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _val01);
+                __m128i _val0 = _mm_unpacklo_epi8(_val01, _extval01);
+                __m128i _val1 = _mm_unpackhi_epi8(_val01, _extval01);
+
+                // TODO use _mm_cvtepi8_epi16 on sse4.1
+                __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                __m128i _extw01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w01);
+                __m128i _w0 = _mm_unpacklo_epi8(_w01, _extw01);
+
+                __m128i _sl00 = _mm_mullo_epi16(_val0, _w0);
+                __m128i _sh00 = _mm_mulhi_epi16(_val0, _w0);
+                __m128i _sl10 = _mm_mullo_epi16(_val1, _w0);
+                __m128i _sh10 = _mm_mulhi_epi16(_val1, _w0);
+
+                _sum0 = _mm_add_epi32(_sum0, _mm_unpacklo_epi16(_sl00, _sh00));
+                _sum1 = _mm_add_epi32(_sum1, _mm_unpackhi_epi16(_sl00, _sh00));
+                _sum2 = _mm_add_epi32(_sum2, _mm_unpacklo_epi16(_sl10, _sh10));
+                _sum3 = _mm_add_epi32(_sum3, _mm_unpackhi_epi16(_sl10, _sh10));
+#endif
+
+                tmpptr += 16;
+                kptr0 += 8;
+            }
+
+#if __AVX2__
+            _sum0_2 = _mm256_add_epi32(_sum0_2, _sum1_3);
+            __m128i _sum0 = _mm256_extracti128_si256(_sum0_2, 0);
+            __m128i _sum2 = _mm256_extracti128_si256(_sum0_2, 1);
+#else
+            _sum0 = _mm_add_epi32(_sum0, _sum1);
+            _sum2 = _mm_add_epi32(_sum2, _sum3);
+#endif
+
+            outptr0[0] = _mm_reduce_add_epi32(_sum0);
+            outptr0[1] = _mm_reduce_add_epi32(_sum2);
+            outptr0 += 2;
+        }
+        for (; i < size; i++)
+        {
+#if __AVX2__
+            const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
+#else
+            const signed char* tmpptr = tmp.channel(i / 2 + i % 2);
+#endif
+            const signed char* kptr0 = kernel.channel(p / 4 + p % 4);
+
+            int nn = inch * maxk; // inch always > 0
+
+            __m128i _sum0 = _mm_setzero_si128();
+            __m128i _sum1 = _mm_setzero_si128();
+
+            int j = 0;
+            for (; j < nn; j++)
+            {
+                // TODO use _mm_cvtepi8_epi16 on sse4.1
+                __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                __m128i _extval01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _val01);
+                __m128i _val0 = _mm_unpacklo_epi8(_val01, _extval01);
+
+                // TODO use _mm_cvtepi8_epi16 on sse4.1
+                __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                __m128i _extw01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w01);
+                __m128i _w0 = _mm_unpacklo_epi8(_w01, _extw01);
+
+                __m128i _sl00 = _mm_mullo_epi16(_val0, _w0);
+                __m128i _sh00 = _mm_mulhi_epi16(_val0, _w0);
+
+                _sum0 = _mm_add_epi32(_sum0, _mm_unpacklo_epi16(_sl00, _sh00));
+                _sum1 = _mm_add_epi32(_sum1, _mm_unpackhi_epi16(_sl00, _sh00));
+
+                tmpptr += 8;
+                kptr0 += 8;
+            }
+
+            _sum0 = _mm_add_epi32(_sum0, _sum1);
+
+            outptr0[0] = _mm_reduce_add_epi32(_sum0);
+            outptr0 += 1;
+        }
+    }
+}
+
+static void convolution_im2col_sgemm_transform_kernel_pack8to1_int8_sse(const Mat& _kernel, Mat& kernel_tm, int inch, int outch, int kernel_w, int kernel_h)
+{
+    const int maxk = kernel_w * kernel_h;
+
+    // interleave
+    // src = maxk-inch-outch
+    // dst = 8a-4b-maxk-inch/8a-outch/4b
+    Mat kernel = _kernel.reshape(maxk, inch, outch);
+    if (outch >= 4)
+        kernel_tm.create(32 * maxk, inch / 8, outch / 4 + outch % 4, (size_t)1u);
+    else
+        kernel_tm.create(8 * maxk, inch / 8, outch, (size_t)1u);
+
+    int q = 0;
+    for (; q + 3 < outch; q += 4)
+    {
+        signed char* g00 = kernel_tm.channel(q / 4);
+
+        for (int p = 0; p + 7 < inch; p += 8)
+        {
+            for (int k = 0; k < maxk; k++)
+            {
+                for (int i = 0; i < 4; i++)
+                {
+                    for (int j = 0; j < 8; j++)
+                    {
+                        const signed char* k00 = kernel.channel(q + i).row<const signed char>(p + j);
+
+                        g00[0] = k00[k];
+
+                        g00++;
+                    }
+                }
+            }
+        }
+    }
+    // TODO unroll 2
+    for (; q < outch; q++)
+    {
+        signed char* g00 = kernel_tm.channel(q / 4 + q % 4);
+
+        for (int p = 0; p + 7 < inch; p += 8)
+        {
+            for (int k = 0; k < maxk; k++)
+            {
+                for (int j = 0; j < 8; j++)
+                {
+                    const signed char* k00 = kernel.channel(q).row<const signed char>(p + j);
+
+                    g00[0] = k00[k];
+
+                    g00++;
+                }
+            }
+        }
+    }
+}
+
+static void convolution_im2col_sgemm_pack8to1_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, int kernel_w, int kernel_h, int dilation_w, int dilation_h, int stride_w, int stride_h, const Option& opt)
+{
+    int w = bottom_blob.w;
+    int inch = bottom_blob.c;
+
+    int outw = top_blob.w;
+    int outh = top_blob.h;
+    const int size = outw * outh;
+
+    const int maxk = kernel_w * kernel_h;
+
+    // im2col
+    Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator);
+    {
+        const int gap = w * stride_h - outw * stride_w;
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int p = 0; p < inch; p++)
+        {
+            const Mat img = bottom_blob.channel(p);
+            int64_t* ptr = bottom_im2col.channel(p);
+
+            for (int u = 0; u < kernel_h; u++)
+            {
+                for (int v = 0; v < kernel_w; v++)
+                {
+                    const int64_t* sptr = img.row<const int64_t>(dilation_h * u) + dilation_w * v;
+
+                    for (int i = 0; i < outh; i++)
+                    {
+                        int j = 0;
+                        for (; j < outw; j++)
+                        {
+                            ptr[0] = sptr[0];
+
+                            sptr += stride_w;
+                            ptr += 1;
+                        }
+
+                        sptr += gap;
+                    }
+                }
+            }
+        }
+    }
+
+    im2col_sgemm_pack8to1_int8_sse(bottom_im2col, top_blob, kernel, opt);
+}

src/layer/x86/convolution_sgemm_pack8to4_int8.h

@@ -24,20 +24,62 @@ static void im2col_sgemm_pack8to4_int8_sse(const Mat& bottom_im2col, Mat& top_bl
 
     // permute
     Mat tmp;
+#if __AVX2__
+    if (size >= 4)
+        tmp.create(4 * maxk, inch, size / 4 + (size % 4) / 2 + size % 2, 8u, 8, opt.workspace_allocator);
+    else if (size >= 2)
+        tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
+    else
+        tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
+#else
     if (size >= 2)
         tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
     else
         tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
+#endif
     {
+#if __AVX2__
+        int remain_size_start = 0;
+        int nn_size = size >> 2;
+
+        #pragma omp parallel for num_threads(opt.num_threads)
+        for (int ii = 0; ii < nn_size; ii++)
+        {
+            int i = remain_size_start + ii * 4;
+
+            int64_t* tmpptr = tmp.channel(i / 4);
+
+            for (int q = 0; q < inch; q++)
+            {
+                const int64_t* img0 = (const int64_t*)bottom_im2col.channel(q) + i;
+
+                for (int k = 0; k < maxk; k++)
+                {
+                    __m256i _v = _mm256_loadu_si256((const __m256i*)img0);
+                    _mm256_storeu_si256((__m256i*)tmpptr, _v);
+                    tmpptr += 4;
+                    img0 += size;
+                }
+            }
+        }
+
+        remain_size_start += nn_size << 2;
+        nn_size = (size - remain_size_start) >> 1;
+#else
         int remain_size_start = 0;
         int nn_size = size >> 1;
+#endif
 
         #pragma omp parallel for num_threads(opt.num_threads)
         for (int ii = 0; ii < nn_size; ii++)
         {
             int i = remain_size_start + ii * 2;
 
+#if __AVX2__
+            int64_t* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
+#else
             int64_t* tmpptr = tmp.channel(i / 2);
+#endif
 
             for (int q = 0; q < inch; q++)
             {
@@ -58,7 +100,11 @@ static void im2col_sgemm_pack8to4_int8_sse(const Mat& bottom_im2col, Mat& top_bl
         #pragma omp parallel for num_threads(opt.num_threads)
         for (int i = remain_size_start; i < size; i++)
         {
+#if __AVX2__
+            int64_t* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
+#else
             int64_t* tmpptr = tmp.channel(i / 2 + i % 2);
+#endif
 
             for (int q = 0; q < inch; q++)
             {
@@ -80,13 +126,139 @@ static void im2col_sgemm_pack8to4_int8_sse(const Mat& bottom_im2col, Mat& top_bl
         int* outptr0 = top_blob.channel(p);
 
         int i = 0;
+#if __AVX2__
+        for (; i + 3 < size; i += 4)
+        {
+            const signed char* tmpptr = tmp.channel(i / 4);
+            const signed char* kptr0 = kernel.channel(p);
+
+            int nn = inch * maxk; // inch always > 0
+
+            __m256i _sum00_11 = _mm256_setzero_si256();
+            __m256i _sum10_01 = _mm256_setzero_si256();
+            __m256i _sum02_13 = _mm256_setzero_si256();
+            __m256i _sum12_03 = _mm256_setzero_si256();
+
+            __m256i _sum04_15 = _mm256_setzero_si256();
+            __m256i _sum14_05 = _mm256_setzero_si256();
+            __m256i _sum06_17 = _mm256_setzero_si256();
+            __m256i _sum16_07 = _mm256_setzero_si256();
+
+            int j = 0;
+            for (; j < nn; j++)
+            {
+                __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                __m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
+
+                __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                __m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
+                __m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
+                __m256i _w23_16 = _mm256_cvtepi8_epi16(_w23);
+
+                __m256i _val10_16 = _mm256_permute4x64_epi64(_val01_16, 78);
+
+                __m256i _sl00_11 = _mm256_mullo_epi16(_val01_16, _w01_16);
+                __m256i _sh00_11 = _mm256_mulhi_epi16(_val01_16, _w01_16);
+                __m256i _sl10_01 = _mm256_mullo_epi16(_val10_16, _w01_16);
+                __m256i _sh10_01 = _mm256_mulhi_epi16(_val10_16, _w01_16);
+                __m256i _sl02_13 = _mm256_mullo_epi16(_val01_16, _w23_16);
+                __m256i _sh02_13 = _mm256_mulhi_epi16(_val01_16, _w23_16);
+                __m256i _sl12_03 = _mm256_mullo_epi16(_val10_16, _w23_16);
+                __m256i _sh12_03 = _mm256_mulhi_epi16(_val10_16, _w23_16);
+
+                _sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpacklo_epi16(_sl00_11, _sh00_11));
+                _sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpacklo_epi16(_sl10_01, _sh10_01));
+                _sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpacklo_epi16(_sl02_13, _sh02_13));
+                _sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpacklo_epi16(_sl12_03, _sh12_03));
+                _sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpackhi_epi16(_sl00_11, _sh00_11));
+                _sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpackhi_epi16(_sl10_01, _sh10_01));
+                _sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpackhi_epi16(_sl02_13, _sh02_13));
+                _sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpackhi_epi16(_sl12_03, _sh12_03));
+
+                __m128i _val23 = _mm_loadu_si128((const __m128i*)(tmpptr + 16));
+                __m256i _val23_16 = _mm256_cvtepi8_epi16(_val23);
+                __m256i _val32_16 = _mm256_permute4x64_epi64(_val23_16, 78);
+
+                __m256i _sl04_15 = _mm256_mullo_epi16(_val23_16, _w01_16);
+                __m256i _sh04_15 = _mm256_mulhi_epi16(_val23_16, _w01_16);
+                __m256i _sl14_05 = _mm256_mullo_epi16(_val32_16, _w01_16);
+                __m256i _sh14_05 = _mm256_mulhi_epi16(_val32_16, _w01_16);
+                __m256i _sl06_17 = _mm256_mullo_epi16(_val23_16, _w23_16);
+                __m256i _sh06_17 = _mm256_mulhi_epi16(_val23_16, _w23_16);
+                __m256i _sl16_07 = _mm256_mullo_epi16(_val32_16, _w23_16);
+                __m256i _sh16_07 = _mm256_mulhi_epi16(_val32_16, _w23_16);
+
+                _sum04_15 = _mm256_add_epi32(_sum04_15, _mm256_unpacklo_epi16(_sl04_15, _sh04_15));
+                _sum14_05 = _mm256_add_epi32(_sum14_05, _mm256_unpacklo_epi16(_sl14_05, _sh14_05));
+                _sum06_17 = _mm256_add_epi32(_sum06_17, _mm256_unpacklo_epi16(_sl06_17, _sh06_17));
+                _sum16_07 = _mm256_add_epi32(_sum16_07, _mm256_unpacklo_epi16(_sl16_07, _sh16_07));
+                _sum04_15 = _mm256_add_epi32(_sum04_15, _mm256_unpackhi_epi16(_sl04_15, _sh04_15));
+                _sum14_05 = _mm256_add_epi32(_sum14_05, _mm256_unpackhi_epi16(_sl14_05, _sh14_05));
+                _sum06_17 = _mm256_add_epi32(_sum06_17, _mm256_unpackhi_epi16(_sl06_17, _sh06_17));
+                _sum16_07 = _mm256_add_epi32(_sum16_07, _mm256_unpackhi_epi16(_sl16_07, _sh16_07));
+
+                tmpptr += 32;
+                kptr0 += 32;
+            }
+
+            // transpose 4x8
+            {
+                __m256i _tmp0, _tmp1, _tmp2, _tmp3;
+                _tmp0 = _mm256_unpacklo_epi32(_sum00_11, _sum10_01);
+                _tmp1 = _mm256_unpacklo_epi32(_sum02_13, _sum12_03);
+                _tmp2 = _mm256_unpackhi_epi32(_sum00_11, _sum10_01);
+                _tmp3 = _mm256_unpackhi_epi32(_sum02_13, _sum12_03);
+                _sum00_11 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
+                _sum10_01 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
+                _sum02_13 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
+                _sum12_03 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
+            }
+            {
+                __m256i _tmp0, _tmp1, _tmp2, _tmp3;
+                _tmp0 = _mm256_unpacklo_epi32(_sum04_15, _sum14_05);
+                _tmp1 = _mm256_unpacklo_epi32(_sum06_17, _sum16_07);
+                _tmp2 = _mm256_unpackhi_epi32(_sum04_15, _sum14_05);
+                _tmp3 = _mm256_unpackhi_epi32(_sum06_17, _sum16_07);
+                _sum04_15 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
+                _sum14_05 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
+                _sum06_17 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
+                _sum16_07 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
+            }
+
+            _sum00_11 = _mm256_add_epi32(_sum00_11, _sum10_01);
+            _sum02_13 = _mm256_add_epi32(_sum02_13, _sum12_03);
+            _sum00_11 = _mm256_add_epi32(_sum00_11, _sum02_13);
+
+            _sum04_15 = _mm256_add_epi32(_sum04_15, _sum14_05);
+            _sum06_17 = _mm256_add_epi32(_sum06_17, _sum16_07);
+            _sum04_15 = _mm256_add_epi32(_sum04_15, _sum06_17);
+
+            __m256i _perm_mask = _mm256_set_epi32(6, 3, 4, 1, 7, 2, 5, 0);
+            _sum00_11 = _mm256_permutevar8x32_epi32(_sum00_11, _perm_mask);
+            _sum04_15 = _mm256_permutevar8x32_epi32(_sum04_15, _perm_mask);
+
+            _mm256_storeu_si256((__m256i*)outptr0, _sum00_11);
+            _mm256_storeu_si256((__m256i*)(outptr0 + 8), _sum04_15);
+            outptr0 += 16;
+        }
+#endif
         for (; i + 1 < size; i += 2)
         {
+#if __AVX2__
+            const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
+#else
             const signed char* tmpptr = tmp.channel(i / 2);
+#endif
             const signed char* kptr0 = kernel.channel(p);
 
             int nn = inch * maxk; // inch always > 0
 
+#if __AVX2__
+            __m256i _sum00_11 = _mm256_setzero_si256();
+            __m256i _sum10_01 = _mm256_setzero_si256();
+            __m256i _sum02_13 = _mm256_setzero_si256();
+            __m256i _sum12_03 = _mm256_setzero_si256();
+#else
             __m128i _sum00 = _mm_setzero_si128();
             __m128i _sum01 = _mm_setzero_si128();
             __m128i _sum02 = _mm_setzero_si128();
@@ -95,10 +267,40 @@ static void im2col_sgemm_pack8to4_int8_sse(const Mat& bottom_im2col, Mat& top_bl
             __m128i _sum11 = _mm_setzero_si128();
             __m128i _sum12 = _mm_setzero_si128();
             __m128i _sum13 = _mm_setzero_si128();
+#endif
 
             int j = 0;
             for (; j < nn; j++)
             {
+#if __AVX2__
+                __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
+                __m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
+
+                __m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
+                __m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
+                __m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
+                __m256i _w23_16 = _mm256_cvtepi8_epi16(_w23);
+
+                __m256i _val10_16 = _mm256_permute4x64_epi64(_val01_16, 78);
+
+                __m256i _sl00_11 = _mm256_mullo_epi16(_val01_16, _w01_16);
+                __m256i _sh00_11 = _mm256_mulhi_epi16(_val01_16, _w01_16);
+                __m256i _sl10_01 = _mm256_mullo_epi16(_val10_16, _w01_16);
+                __m256i _sh10_01 = _mm256_mulhi_epi16(_val10_16, _w01_16);
+                __m256i _sl02_13 = _mm256_mullo_epi16(_val01_16, _w23_16);
+                __m256i _sh02_13 = _mm256_mulhi_epi16(_val01_16, _w23_16);
+                __m256i _sl12_03 = _mm256_mullo_epi16(_val10_16, _w23_16);
+                __m256i _sh12_03 = _mm256_mulhi_epi16(_val10_16, _w23_16);
+
+                _sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpacklo_epi16(_sl00_11, _sh00_11));
+                _sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpacklo_epi16(_sl10_01, _sh10_01));
+                _sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpacklo_epi16(_sl02_13, _sh02_13));
+                _sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpacklo_epi16(_sl12_03, _sh12_03));
+                _sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpackhi_epi16(_sl00_11, _sh00_11));
+                _sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpackhi_epi16(_sl10_01, _sh10_01));
+                _sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpackhi_epi16(_sl02_13, _sh02_13));
+                _sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpackhi_epi16(_sl12_03, _sh12_03));
+#else
                 // TODO use _mm_cvtepi8_epi16 on sse4.1
                 __m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
                 __m128i _extval01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _val01);
@@ -148,11 +350,35 @@ static void im2col_sgemm_pack8to4_int8_sse(const Mat& bottom_im2col, Mat& top_bl
                 _sum11 = _mm_add_epi32(_sum11, _mm_unpackhi_epi16(_sl11, _sh11));
                 _sum12 = _mm_add_epi32(_sum12, _mm_unpackhi_epi16(_sl12, _sh12));
                 _sum13 = _mm_add_epi32(_sum13, _mm_unpackhi_epi16(_sl13, _sh13));
+#endif
 
                 tmpptr += 16;
                 kptr0 += 32;
             }
 
+#if __AVX2__
+            // transpose 4x8
+            {
+                __m256i _tmp0, _tmp1, _tmp2, _tmp3;
+                _tmp0 = _mm256_unpacklo_epi32(_sum00_11, _sum10_01);
+                _tmp1 = _mm256_unpacklo_epi32(_sum02_13, _sum12_03);
+                _tmp2 = _mm256_unpackhi_epi32(_sum00_11, _sum10_01);
+                _tmp3 = _mm256_unpackhi_epi32(_sum02_13, _sum12_03);
+                _sum00_11 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
+                _sum10_01 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
+                _sum02_13 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
+                _sum12_03 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
+            }
+
+            _sum00_11 = _mm256_add_epi32(_sum00_11, _sum10_01);
+            _sum02_13 = _mm256_add_epi32(_sum02_13, _sum12_03);
+            _sum00_11 = _mm256_add_epi32(_sum00_11, _sum02_13);
+
+            __m256i _perm_mask = _mm256_set_epi32(6, 3, 4, 1, 7, 2, 5, 0);
+            _sum00_11 = _mm256_permutevar8x32_epi32(_sum00_11, _perm_mask);
+
+            _mm256_storeu_si256((__m256i*)outptr0, _sum00_11);
+#else
             // transpose 4x4
             {
                 __m128i _tmp0, _tmp1, _tmp2, _tmp3;
@@ -187,11 +413,16 @@ static void im2col_sgemm_pack8to4_int8_sse(const Mat& bottom_im2col, Mat& top_bl
 
             _mm_storeu_si128((__m128i*)outptr0, _sum00);
             _mm_storeu_si128((__m128i*)(outptr0 + 4), _sum10);
+#endif
             outptr0 += 8;
         }
         for (; i < size; i++)
         {
+#if __AVX2__
+            const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
+#else
             const signed char* tmpptr = tmp.channel(i / 2 + i % 2);
+#endif
             const signed char* kptr0 = kernel.channel(p);
 
             int nn = inch * maxk; // inch always > 0

src/layer/x86/convolution_x86.cpp

@@ -49,7 +49,13 @@ namespace ncnn {
 #include "convolution_pack1to4_int8.h"
 #include "convolution_pack8to1_int8.h"
 #include "convolution_sgemm_pack8to4_int8.h"
+#include "convolution_sgemm_pack1to4_int8.h"
+#include "convolution_sgemm_pack8to1_int8.h"
 #include "convolution_1x1_pack8to4_int8.h"
+#include "convolution_1x1_pack1to4_int8.h"
+#include "convolution_1x1_pack8to1_int8.h"
+#include "convolution_3x3_pack1to4_int8.h"
+#include "convolution_7x7_pack1to4_int8.h"
 #endif // NCNN_INT8
 
 #if __AVX__
@@ -1133,36 +1139,9 @@ int Convolution_x86::forward(const std::vector<Mat>& bottom_blobs, std::vector<M
 }
 
 #if NCNN_INT8
-int Convolution_x86::create_pipeline_int8_x86(const Option& opt)
+static void convolution_transform_kernel_packed_int8_sse(const Mat& weight_data, Mat& weight_data_int8, int num_input, int num_output, int kernel_w, int kernel_h, int elempack, int out_elempack)
 {
     const int maxk = kernel_w * kernel_h;
-    const int num_input = weight_data_size / maxk / num_output;
-
-    int elempack = 1;
-    int out_elempack = 1;
-
-#if __SSE2__
-    if (opt.use_packing_layout)
-    {
-        elempack = num_input % 8 == 0 ? 8 : 1;
-        out_elempack = num_output % 4 == 0 ? 4 : 1;
-    }
-#endif // __SSE2__
-
-    if (elempack == 1 && out_elempack == 1)
-    {
-        if (opt.use_winograd_convolution && kernel_w == 3 && kernel_h == 3 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1 && num_input >= 16 && num_output >= 16)
-        {
-            conv3x3s1_winograd23_transform_kernel_int8_sse(weight_data, weight_data_3x3_winograd23_int8, num_input, num_output, opt);
-            //         conv3x3s1_winograd43_transform_kernel_int8_sse(weight_data, weight_data_3x3_winograd23_int8, num_input, num_output, opt);
-        }
-        else
-        {
-            // TODO offline transform weight
-        }
-
-        return 0;
-    }
 
     // src = kw-kh-inch-outch
     // dst = pa-pb-kw-kh-inch/pa-outch/pb
@@ -1181,11 +1160,11 @@ int Convolution_x86::create_pipeline_int8_x86(const Option& opt)
 
                 for (int k = 0; k < maxk; k++)
                 {
-                    for (int j = 0; j < out_elempack; j++)
+                    for (int i = 0; i < out_elempack; i++)
                     {
-                        for (int i = 0; i < elempack; i++)
+                        for (int j = 0; j < elempack; j++)
                         {
-                            const signed char* k00 = weight_data_r2.channel(q + j).row<const signed char>(p + i);
+                            const signed char* k00 = weight_data_r2.channel(q + i).row<const signed char>(p + j);
 
                             g00[0] = k00[k];
 
@@ -1196,25 +1175,121 @@ int Convolution_x86::create_pipeline_int8_x86(const Option& opt)
             }
         }
     }
+}
+
+int Convolution_x86::create_pipeline_int8_x86(const Option& opt)
+{
+    const int maxk = kernel_w * kernel_h;
+    const int num_input = weight_data_size / maxk / num_output;
+
+    int elempack = 1;
+    int out_elempack = 1;
+#if __SSE2__
+    if (opt.use_packing_layout)
+    {
+        elempack = num_input % 8 == 0 ? 8 : 1;
+        out_elempack = num_output % 4 == 0 ? 4 : 1;
+    }
+#endif // __SSE2__
 
 #if __SSE2__
     if (elempack == 8 && out_elempack == 4)
     {
         if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
         {
-            convolution_im2col_sgemm_transform_kernel_pack8to4_int8_sse(weight_data, weight_data_int8, num_input, num_output, kernel_w, kernel_h);
+            convolution_im2col_sgemm_transform_kernel_pack8to4_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
         }
         else if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
         {
-            convolution_im2col_sgemm_transform_kernel_pack8to4_int8_sse(weight_data, weight_data_int8, num_input, num_output, kernel_w, kernel_h);
+            convolution_im2col_sgemm_transform_kernel_pack8to4_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
         }
         else if (opt.use_sgemm_convolution)
         {
-            convolution_im2col_sgemm_transform_kernel_pack8to4_int8_sse(weight_data, weight_data_int8, num_input, num_output, kernel_w, kernel_h);
+            convolution_im2col_sgemm_transform_kernel_pack8to4_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else
+        {
+            convolution_transform_kernel_packed_int8_sse(weight_data, weight_data_int8, num_input, num_output, kernel_w, kernel_h, elempack, out_elempack);
+        }
+    }
+
+    if (elempack == 1 && out_elempack == 4)
+    {
+        if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
+        {
+            convolution_im2col_sgemm_transform_kernel_pack1to4_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
+        {
+            convolution_im2col_sgemm_transform_kernel_pack1to4_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else if (kernel_w == 3 && kernel_h == 3 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
+        {
+            convolution_im2col_sgemm_transform_kernel_pack1to4_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else if (kernel_w == 3 && kernel_h == 3 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
+        {
+            convolution_im2col_sgemm_transform_kernel_pack1to4_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else if (kernel_w == 7 && kernel_h == 7 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
+        {
+            convolution_im2col_sgemm_transform_kernel_pack1to4_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else if (opt.use_sgemm_convolution) // TODO better condition && num_input >= 8 && num_output >= 8)
+        {
+            convolution_im2col_sgemm_transform_kernel_pack1to4_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else
+        {
+            convolution_transform_kernel_packed_int8_sse(weight_data, weight_data_int8, num_input, num_output, kernel_w, kernel_h, elempack, out_elempack);
+        }
+    }
+
+    if (elempack == 8 && out_elempack == 1)
+    {
+        if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
+        {
+            convolution_im2col_sgemm_transform_kernel_pack8to1_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
+        {
+            convolution_im2col_sgemm_transform_kernel_pack8to1_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else if (opt.use_sgemm_convolution) // TODO better condition && num_input >= 8 && num_output >= 8)
+        {
+            convolution_im2col_sgemm_transform_kernel_pack8to1_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else
+        {
+            convolution_transform_kernel_packed_int8_sse(weight_data, weight_data_int8, num_input, num_output, kernel_w, kernel_h, elempack, out_elempack);
         }
     }
 #endif // __SSE2__
 
+    if (elempack == 1 && out_elempack == 1)
+    {
+        if (opt.use_winograd_convolution && kernel_w == 3 && kernel_h == 3 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1 && num_input >= 16 && num_output >= 16)
+        {
+            conv3x3s1_winograd23_transform_kernel_int8_sse(weight_data, weight_data_3x3_winograd23_int8, num_input, num_output, opt);
+            //         conv3x3s1_winograd43_transform_kernel_int8_sse(weight_data, weight_data_3x3_winograd23_int8, num_input, num_output, opt);
+        }
+
+        if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
+        {
+            convolution_im2col_sgemm_transform_kernel_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
+        {
+            convolution_im2col_sgemm_transform_kernel_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+        else if (opt.use_sgemm_convolution)
+        {
+            convolution_im2col_sgemm_transform_kernel_int8_sse(weight_data, weight_sgemm_data, num_input, num_output, kernel_w, kernel_h);
+        }
+
+        return 0;
+    }
+
     return 0;
 }
 
@@ -1287,15 +1362,15 @@ int Convolution_x86::forward_int8_x86(const Mat& bottom_blob, Mat& top_blob, con
     {
         if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
         {
-            conv1x1s1_sgemm_pack8to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_data_int8, opt);
+            conv1x1s1_sgemm_pack8to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
         }
         else if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
         {
-            conv1x1s2_pack8to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_data_int8, opt);
+            conv1x1s2_sgemm_pack8to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
         }
         else if (opt.use_sgemm_convolution)
         {
-            convolution_im2col_sgemm_pack8to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_data_int8, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
+            convolution_im2col_sgemm_pack8to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
         }
         else
         {
@@ -1332,7 +1407,34 @@ int Convolution_x86::forward_int8_x86(const Mat& bottom_blob, Mat& top_blob, con
 
     if (elempack == 1 && out_elempack_int32 == 4)
     {
-        convolution_pack1to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_data_int8, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
+        if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
+        {
+            conv1x1s1_sgemm_pack1to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
+        }
+        else if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
+        {
+            conv1x1s2_sgemm_pack1to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
+        }
+        else if (kernel_w == 3 && kernel_h == 3 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
+        {
+            conv3x3s1_pack1to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
+        }
+        else if (kernel_w == 3 && kernel_h == 3 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
+        {
+            conv3x3s2_pack1to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
+        }
+        else if (kernel_w == 7 && kernel_h == 7 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
+        {
+            conv7x7s2_pack1to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
+        }
+        else if (opt.use_sgemm_convolution) // TODO better condition && num_input >= 8 && num_output >= 8)
+        {
+            convolution_im2col_sgemm_pack1to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
+        }
+        else
+        {
+            convolution_pack1to4_int8_sse(bottom_blob_bordered, top_blob_int32, weight_data_int8, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
+        }
 
         Mat scale_in_data(num_output);
         for (int p = 0; p < num_output; p++)
@@ -1364,7 +1466,22 @@ int Convolution_x86::forward_int8_x86(const Mat& bottom_blob, Mat& top_blob, con
 
     if (elempack == 8 && out_elempack_int32 == 1)
     {
-        convolution_pack8to1_int8_sse(bottom_blob_bordered, top_blob_int32, weight_data_int8, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
+        if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
+        {
+            conv1x1s1_sgemm_pack8to1_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
+        }
+        else if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
+        {
+            conv1x1s2_sgemm_pack8to1_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
+        }
+        else if (opt.use_sgemm_convolution) // TODO better condition && num_input >= 8 && num_output >= 8)
+        {
+            convolution_im2col_sgemm_pack8to1_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
+        }
+        else
+        {
+            convolution_pack8to1_int8_sse(bottom_blob_bordered, top_blob_int32, weight_data_int8, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
+        }
 
         Mat scale_in_data(num_output);
         for (int p = 0; p < num_output; p++)
@@ -1397,111 +1514,53 @@ int Convolution_x86::forward_int8_x86(const Mat& bottom_blob, Mat& top_blob, con
 
     if (elempack == 1 && out_elempack_int32 == 1)
     {
-        if (opt.use_winograd_convolution && kernel_w == 3 && kernel_h == 3 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1 && num_input >= 16 && num_output >= 16)
+        if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
+        {
+            conv1x1s1_sgemm_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
+        }
+        else if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 2 && stride_h == 2)
+        {
+            conv1x1s2_sgemm_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, opt);
+        }
+        else if (opt.use_winograd_convolution && kernel_w == 3 && kernel_h == 3 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1 && num_input >= 16 && num_output >= 16)
         {
             conv3x3s1_winograd23_int8_sse(bottom_blob_bordered, top_blob_int32, weight_data_3x3_winograd23_int8, opt);
             //             conv3x3s1_winograd43_int8_sse(bottom_blob_bordered, top_blob_int32, weight_data_3x3_winograd23_int8, opt);
-
-            Mat scale_in_data(num_output);
-            for (int p = 0; p < num_output; p++)
-            {
-                // requantize and relu
-                float scale_in;
-                if (weight_data_int8_scales[p] == 0)
-                    scale_in = 0;
-                else
-                    scale_in = 1.f / (bottom_blob_int8_scales[0] * weight_data_int8_scales[p]);
-
-                scale_in_data[p] = scale_in;
-            }
-
-            if (use_int8_requantize)
-            {
-                requantize_from_int32_to_int8(top_blob_int32, top_blob, scale_in_data, top_blob_int8_scales, bias_data, activation_type, activation_params, opt);
-            }
-            else
-            {
-                dequantize_from_int32(top_blob_int32, top_blob, scale_in_data, bias_data, opt);
-
-                if (activation)
-                {
-                    activation->forward_inplace(top_blob, opt);
-                }
-            }
         }
-        else if (opt.use_sgemm_convolution && dilation_w == 1 && dilation_h == 1 && (activation_type == 0 || activation_type == 1))
+        else if (opt.use_sgemm_convolution)
         {
-            if (use_int8_requantize)
-            {
-                std::vector<float> requantize_scales;
-                for (int p = 0; p < num_output; p++)
-                {
-                    float scale_in;
-                    if (weight_data_int8_scales[p] == 0)
-                        scale_in = 0;
-                    else
-                        scale_in = 1.f / (bottom_blob_int8_scales[0] * weight_data_int8_scales[p]);
-
-                    float scale_out = top_blob_int8_scales[0];
-
-                    requantize_scales.push_back(scale_in);
-                    requantize_scales.push_back(scale_out);
-                }
+            convolution_im2col_sgemm_int8_sse(bottom_blob_bordered, top_blob_int32, weight_sgemm_data, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
+        }
+        else
+        {
+            //         convolution_int8(bottom_blob_bordered, top_blob_int32, weight_data_int8, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
+            convolution_int8(bottom_blob_bordered, top_blob_int32, weight_data, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
+        }
 
-                conv_im2col_sgemm_int8_requant_sse(bottom_blob_bordered, top_blob, weight_data, kernel_w, kernel_h, stride_w, stride_h, bias_data, requantize_scales, opt);
-            }
+        Mat scale_in_data(num_output);
+        for (int p = 0; p < num_output; p++)
+        {
+            // requantize and relu
+            float scale_in;
+            if (weight_data_int8_scales[p] == 0)
+                scale_in = 0;
             else
-            {
-                std::vector<float> dequantize_scales;
-                for (int p = 0; p < num_output; p++)
-                {
-                    float scale_in;
-                    if (weight_data_int8_scales[p] == 0)
-                        scale_in = 0;
-                    else
-                        scale_in = 1.f / (bottom_blob_int8_scales[0] * weight_data_int8_scales[p]);
-
-                    dequantize_scales.push_back(scale_in);
-                }
+                scale_in = 1.f / (bottom_blob_int8_scales[0] * weight_data_int8_scales[p]);
 
-                conv_im2col_sgemm_int8_dequant_sse(bottom_blob_bordered, top_blob, weight_data, kernel_w, kernel_h, stride_w, stride_h, bias_data, dequantize_scales, opt);
-            }
+            scale_in_data[p] = scale_in;
+        }
 
-            if (activation)
-            {
-                activation->forward_inplace(top_blob, opt);
-            }
+        if (use_int8_requantize)
+        {
+            requantize_from_int32_to_int8(top_blob_int32, top_blob, scale_in_data, top_blob_int8_scales, bias_data, activation_type, activation_params, opt);
         }
         else
         {
-            //         convolution_int8(bottom_blob_bordered, top_blob_int32, weight_data_int8, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
-            convolution_int8(bottom_blob_bordered, top_blob_int32, weight_data, kernel_w, kernel_h, dilation_w, dilation_h, stride_w, stride_h, opt);
-
-            Mat scale_in_data(num_output);
-            for (int p = 0; p < num_output; p++)
-            {
-                // requantize and relu
-                float scale_in;
-                if (weight_data_int8_scales[p] == 0)
-                    scale_in = 0;
-                else
-                    scale_in = 1.f / (bottom_blob_int8_scales[0] * weight_data_int8_scales[p]);
-
-                scale_in_data[p] = scale_in;
-            }
+            dequantize_from_int32(top_blob_int32, top_blob, scale_in_data, bias_data, opt);
 
-            if (use_int8_requantize)
-            {
-                requantize_from_int32_to_int8(top_blob_int32, top_blob, scale_in_data, top_blob_int8_scales, bias_data, activation_type, activation_params, opt);
-            }
-            else
+            if (activation)
             {
-                dequantize_from_int32(top_blob_int32, top_blob, scale_in_data, bias_data, opt);
-
-                if (activation)
-                {
-                    activation->forward_inplace(top_blob, opt);
-                }
+                activation->forward_inplace(top_blob, opt);
             }
         }
     }

src/layer/x86/convolution_x86.h

@@ -41,13 +41,16 @@ protected:
 public:
     Layer* activation;
 
-    Mat weight_data_packed;
+    Mat weight_sgemm_data;
     Mat weight_data_3x3_winograd23;
     Mat weight_data_3x3_winograd63;
 
     // forwardDilation
     Layer* convolution_dilation1;
 
+    // pack4/8
+    Mat weight_data_packed;
+
 #if NCNN_INT8
     // int8
     Mat weight_data_int8;

src/layer/x86/x86_usability.h

@@ -15,6 +15,13 @@
 #ifndef X86_USABILITY_H
 #define X86_USABILITY_H
 
+#if __SSE2__
+#include <emmintrin.h>
+#if __AVX__
+#include <immintrin.h>
+#endif
+#endif // __SSE2__
+
 static NCNN_FORCEINLINE signed char float2int8(float v)
 {
     int int32 = (int)round(v);
@@ -24,8 +31,6 @@ static NCNN_FORCEINLINE signed char float2int8(float v)
 }
 
 #if __SSE2__
-#include <emmintrin.h>
-
 static NCNN_FORCEINLINE float _mm_reduce_add_ps(__m128 x128)
 {
     const __m128 x64 = _mm_add_ps(x128, _mm_movehl_ps(x128, x128));
@@ -33,6 +38,15 @@ static NCNN_FORCEINLINE float _mm_reduce_add_ps(__m128 x128)
     return _mm_cvtss_f32(x32);
 }
 
+static NCNN_FORCEINLINE int _mm_reduce_add_epi32(__m128i x)
+{
+    __m128i hi64 = _mm_unpackhi_epi64(x, x);
+    __m128i sum64 = _mm_add_epi32(hi64, x);
+    __m128i hi32 = _mm_shuffle_epi32(sum64, _MM_SHUFFLE(2, 3, 0, 1));
+    __m128i sum32 = _mm_add_epi32(sum64, hi32);
+    return _mm_cvtsi128_si32(sum32);
+}
+
 static NCNN_FORCEINLINE int32_t float2int8_sse(const __m128& _v0)
 {
     // _MM_ROUND_NEAREST round to even
@@ -120,7 +134,7 @@ static NCNN_FORCEINLINE __m128i float2int8_sse(const __m128& _v0, const __m128&
 
     return _v8;
 }
-#if __SSE2__
+
 #ifndef __AVX2__
 
 static NCNN_FORCEINLINE __m128 _mm_comp_fmadd_ps(__m128 _a, const __m128 _b, const __m128 _c)
@@ -128,9 +142,8 @@ static NCNN_FORCEINLINE __m128 _mm_comp_fmadd_ps(__m128 _a, const __m128 _b, con
     return _mm_add_ps(_mm_mul_ps(_a, _b), _c);
 }
 #endif
-#endif
+
 #if __AVX__
-#include <immintrin.h>
 #ifndef __AVX2__
 static NCNN_FORCEINLINE __m256 _mm256_comp_fmadd_ps(__m256 _a, const __m256 _b, const __m256 _c)
 {
@@ -152,13 +165,14 @@ static NCNN_FORCEINLINE __m256 _mm256_comp_fmadd_ps(__m256 _a, const __m256 _b,
     return _mm256_fmadd_ps(_a, _b, _c);
 }
 #endif
-#if __AVX2__
 
+#if __AVX2__
 static NCNN_FORCEINLINE __m256 loadfp16(const unsigned short* ptr)
 {
     return _mm256_cvtph_ps(_mm_lddqu_si128((__m128i*)(ptr)));
 }
 #endif
+
 static NCNN_FORCEINLINE __m256 _mm256_fmadd_1_ps(__m256 a, __m256 b, float c)
 {
     return _mm256_comp_fmadd_ps(b, _mm256_set1_ps(c), a);