fix(dnn/arm): fix nchw_nchw44 dot stride1 support

GitOrigin-RevId: c8d3d55b25

dnn/src/arm_common/conv_bias/block_helper.h

@@ -0,0 +1,36 @@
+/**
+ * \file dnn/src/arm_common/conv_bias/block_helper.h
+ * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
+ *
+ * Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or
+ * implied.
+ */
+
+#include "src/common/utils.h"
+namespace megdnn {
+namespace {
+// block_helper is used to calculate oh block size
+static inline int l2_block_helper(const int nthread, const int amount,
+                                  const int size_per_unit) {
+    constexpr int l2_cache_size = 256 * 1024;
+    const int block_per_thread = div_ceil(amount, nthread);
+    const int best_block = std::min(
+            amount, (l2_cache_size + size_per_unit / 2) / size_per_unit);
+    const int max_block_num = div_ceil(block_per_thread, best_block);
+    const int min_block_num = std::max(max_block_num - 1, 1);
+    const int max_block = div_ceil(block_per_thread, max_block_num);
+    const int min_block = div_ceil(block_per_thread, min_block_num);
+    const int max_loss = std::abs(max_block_num * max_block - block_per_thread);
+    const int min_loss = std::abs(min_block_num * min_block - block_per_thread);
+    int block = max_loss > min_loss ? min_block : max_block;
+    return block;
+}
+
+}  // namespace
+}  // namespace megdnn
+
+// vim: syntax=cpp.doxygen

dnn/src/arm_common/conv_bias/fp32/f32_direct_nchw44_algo.cpp

@@ -11,6 +11,7 @@
  */
 
 #include "megdnn/oprs.h"
+#include "src/arm_common/conv_bias/block_helper.h"
 #include "src/arm_common/conv_bias/fp32/algos.h"
 #include "src/arm_common/conv_bias/fp32/f32_direct_stride1_nchw44_kern.h"
 #include "src/arm_common/conv_bias/fp32/f32_direct_stride2_nchw44_kern.h"
@@ -26,22 +27,7 @@ using conv_fun = std::function<void(
         const CpuNDRange& workspace_ids, const CpuNDRange& ncb_range)>;
 MIDOUT_DECL(megdnn_arm_common_conv_bias_fp32_nchw44_stride1)
 namespace {
-// block_helper is used to calculate oh block size
-static inline int block_helper(const int nthread, const int amount,
-                               const int size_per_unit) {
-    constexpr int l2_cache_size = 256 * 1024;
-    const int block_per_thread = div_ceil(amount, nthread);
-    const int best_block = std::min(
-            amount, (l2_cache_size + size_per_unit / 2) / size_per_unit);
-    const int max_block_num = div_ceil(block_per_thread, best_block);
-    const int min_block_num = std::max(max_block_num - 1, 1);
-    const int max_block = div_ceil(block_per_thread, max_block_num);
-    const int min_block = div_ceil(block_per_thread, min_block_num);
-    const int max_loss = std::abs(max_block_num * max_block - block_per_thread);
-    const int min_loss = std::abs(min_block_num * min_block - block_per_thread);
-    int block = max_loss > min_loss ? min_block : max_block;
-    return block;
-}
+
 static inline size_t get_perthread_cache_bytes(const int ic, const int ih2,
                                                const int iw2) {
     // border_size is used to avoid read illegal memory
@@ -60,7 +46,7 @@ static void get_rectified_size(
     ow2 = ow;
     constexpr int cacheline = 64 / sizeof(float);
     int block_oh =
-            block_helper(param.nr_threads, oh, ic * iw * sizeof(float) * 2);
+            l2_block_helper(param.nr_threads, oh, ic * iw * sizeof(float) * 2);
     auto&& fm = param.filter_meta;
     const int stride_h = static_cast<int>(fm.stride[0]);
     const int filter_h = static_cast<int>(fm.spatial[0]);
@@ -106,8 +92,8 @@ static void do_conv_kern(WorkspaceBundle bundle,
     const int group_id = ncb_index.ndrange_id[1];
     constexpr int oc_idx = 0;
     int oc_block = oc;
-    int oh_block = block_helper(kern_param.nr_threads, oh2,
-                                ic * iw * sizeof(float) * stride_h);
+    int oh_block = l2_block_helper(kern_param.nr_threads, oh2,
+                                   ic * iw * sizeof(float) * stride_h);
     const int oh_idx = ncb_index.ndrange_id[2];
     const int oh_block_real = std::min(oh - oh_idx * oh_block, oh_block);
     const int ih_real = oh_block_real * stride_h + fh - stride_h;
@@ -298,8 +284,8 @@ ConvBiasImpl::AlgoF32DirectNCHW44::dispatch_kerns(
     int ic = param.filter_meta.icpg;
     int iw = param.isz[1];
     int stride_h = param.filter_meta.stride[0];
-    int oh_block = block_helper(param.nr_threads, oh,
-                                ic * iw * sizeof(float) * stride_h);
+    int oh_block = l2_block_helper(param.nr_threads, oh,
+                                   ic * iw * sizeof(float) * stride_h);
     CpuNDRange ncb_range = {static_cast<size_t>(batch),
                             static_cast<size_t>(group),
                             static_cast<size_t>(div_ceil(oh, oh_block))};

dnn/src/arm_common/conv_bias/int8/algos.h

@@ -133,6 +133,21 @@ public:
 };
 
 #if __ARM_FEATURE_DOTPROD
+
+class ConvBiasImpl::AlgoDotS8DirectNCHWNCHW44 final : public AlgoBase {
+public:
+    bool is_reproducible() const override { return true; }
+    const char* name() const override { return "ARMDOTS8_NCHW_NCHW44"; }
+    bool usable(FallbackConvBiasImpl*, const NCBKernSizeParam&,
+                AlgoSelectionStrategy algo_selection_strategy) const override;
+
+    size_t get_workspace(FallbackConvBiasImpl*,
+                         const NCBKernSizeParam&) const override;
+    virtual SmallVector<NCBKern> dispatch_kerns(
+            fallback::ConvBiasImpl* opr,
+            const NCBKernSizeParam& param) const override;
+};
+
 class ConvBiasImpl::AlgoDotS8DirectStride1 final : public AlgoBase {
     bool m_large_group;
 

dnn/src/arm_common/conv_bias/int8/dot_direct_nchw_nchw44_algo.cpp

@@ -0,0 +1,321 @@
+/**
+ * \file
+ * dnn/src/arm_common/conv_bias/int8/dot_direct_nchw_nchw44_algo.cpp
+ * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
+ *
+ * Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express
+ * or implied.
+ */
+#if __ARM_FEATURE_DOTPROD
+#include "megdnn/oprs.h"
+#include "src/arm_common/conv_bias/block_helper.h"
+#include "src/arm_common/conv_bias/int8/algos.h"
+#include "src/arm_common/conv_bias/int8/dot_direct_nchw_nchw44_kern.h"
+#include "src/arm_common/elemwise_op.h"
+
+#include "midout.h"
+
+using namespace megdnn;
+using namespace arm_common;
+using conv_fun = std::function<void(
+        WorkspaceBundle bundle, const ConvBiasImpl::NCBKernParam& kern_param,
+        const ConvBiasImpl::NCBKernIndex& ncb_index,
+        const CpuNDRange& workspace_ids, const CpuNDRange& ncb_range)>;
+MIDOUT_DECL(megdnn_arm_common_conv_bias_int8_nchw44_dot)
+namespace {
+static inline size_t get_perthread_cache_bytes(const int ic, const int ih2,
+                                               const int iw2,
+                                               const int stride) {
+    //! border_size is used to avoid read illegal memory
+    constexpr int cacheline_size = 64;
+    constexpr int border_size = 2 * cacheline_size;
+    const int pack_iw_len = stride == 1 ? 4 : 1;
+    return round_up(
+            ic * ih2 * iw2 * pack_iw_len * (int)sizeof(int8_t) + border_size,
+            cacheline_size);
+}
+static inline size_t get_temp_bytes(const int iw, const int pw) {
+    //! border_size is used to avoid read illegal memory
+    constexpr int cacheline_size = 64;
+    constexpr int border_size = 1 * cacheline_size;
+
+    return round_up(iw + pw * 2, cacheline_size) + border_size;
+}
+static void get_rectified_size(
+        const megdnn::fallback::ConvBiasImpl::NCBKernSizeParam& param, int& ih2,
+        int& iw2) {
+    auto&& fm = param.filter_meta;
+    const int stride_h = static_cast<int>(fm.stride[0]);
+    const int filter_h = static_cast<int>(fm.spatial[0]);
+    int ic = param.filter_meta.icpg;
+    int iw = param.isz[1];
+    int oh = param.osz[0];
+    int block_oh = l2_block_helper(param.nr_threads, oh,
+                                   ic * iw * sizeof(int8_t) * stride_h);
+    ih2 = block_oh * stride_h + filter_h - stride_h;
+    iw2 = iw + 2 * static_cast<int>(fm.padding[1]);
+}
+
+static WorkspaceBundle get_bundle(const ConvBiasImpl::NCBKernSizeParam& param) {
+    auto&& fm = param.filter_meta;
+    int ic = fm.icpg;
+    int fh = fm.spatial[0];
+    int fw = fm.spatial[1];
+    int iw = param.isz[1];
+    int pw = param.filter_meta.padding[1];
+    int stride_w = param.filter_meta.stride[1];
+    int ih2, iw2;
+    get_rectified_size(param, ih2, iw2);
+
+    size_t src_size = get_perthread_cache_bytes(ic, ih2, iw2, stride_w);
+    size_t weight_size = fm.group * fm.icpg * fm.ocpg * fh * round_up(fw, 4);
+    size_t temp_size = 0;
+    if (fm.stride[0] == 1) {
+        temp_size = get_temp_bytes(iw, pw);
+    }
+    return {nullptr,
+            {src_size * param.nr_threads, weight_size,
+             temp_size * param.nr_threads}};
+};
+
+void do_weight_trans(WorkspaceBundle bundle,
+                     const ConvBiasImpl::NCBKernParam& kern_param,
+                     const ConvBiasImpl::NCBKernIndex&, const CpuNDRange&) {
+    const int ic = kern_param.filter_meta.icpg;
+    const int oc = kern_param.filter_meta.ocpg;
+    const int fh = kern_param.filter_meta.spatial[0];
+    const int fw = kern_param.filter_meta.spatial[1];
+    const int fw2 = round_up(fw, 4);
+    bundle.set(kern_param.workspace_ptr);
+    auto packed_weight = reinterpret_cast<int8_t*>(bundle.get(1));
+    auto origin_weight = kern_param.filter<dt_int8>();
+    pack_weight_int8_nchw_nchw44_dot(packed_weight, origin_weight, oc, ic, fh,
+                                     fw, fw2);
+}
+
+template <size_t filter, BiasMode bias_mode, typename Op, int stride>
+static void do_conv_kern(WorkspaceBundle bundle,
+                         const ConvBiasImpl::NCBKernParam& kern_param,
+                         const ConvBiasImpl::NCBKernIndex& ncb_index,
+                         const CpuNDRange&, const CpuNDRange&) {
+    const int oh = kern_param.osz[0];
+    const int ow = kern_param.osz[1];
+    const int fh = kern_param.filter_meta.spatial[0];
+    const int fw = kern_param.filter_meta.spatial[1];
+    const int ic = kern_param.filter_meta.icpg;
+    const int oc = kern_param.filter_meta.ocpg;
+    const int ih = kern_param.isz[0];
+    const int iw = kern_param.isz[1];
+    const int stride_h = kern_param.filter_meta.stride[0];
+    const int stride_w = kern_param.filter_meta.stride[1];
+    const int ph = kern_param.filter_meta.padding[0];
+    const int pw = kern_param.filter_meta.padding[1];
+    int ih2 = 0;
+    int iw2 = 0;
+    get_rectified_size(kern_param, ih2, iw2);
+    bundle.set(kern_param.workspace_ptr);
+
+    constexpr int pack_c = 4;
+    const int batch_id = ncb_index.ndrange_id[0];
+    const int group_id = ncb_index.ndrange_id[1];
+    constexpr int oc_idx = 0;
+    int oc_block = oc;
+    int oh_block = l2_block_helper(kern_param.nr_threads, oh,
+                                   ic * iw * sizeof(int8_t) * stride_h);
+    const int oh_idx = ncb_index.ndrange_id[2];
+    const int oh_block_real = std::min(oh - oh_idx * oh_block, oh_block);
+    const int ih_real = oh_block_real * stride_h + fh - stride_h;
+    const int src_top_pad = std::max(ph - oh_idx * oh_block * stride_h, 0);
+    const int src_bottom_pad = std::max(
+            (oh_idx * oh_block + oh_block_real - 1) * stride_h + fh - ih - ph,
+            0);
+    const int remain_right_pad = std::max(iw2 - iw - pw, 0);
+    const int src_offset = std::max(oh_idx * oh_block * stride_h - ph, 0) * iw;
+    const int8_t* origin_sptr =
+            static_cast<const int8_t*>(
+                    kern_param.src<int8_t>(batch_id, group_id, 0, 1, 1)) +
+            src_offset;
+    const size_t src_size = get_perthread_cache_bytes(ic, ih2, iw2, stride_w);
+    int8_t* sptr = reinterpret_cast<int8_t*>(bundle.get(0)) +
+                   ncb_index.thread_id * src_size;
+    int8_t* tmp_ptr = nullptr;
+    if (stride == 1) {
+        const size_t tmp_size = get_temp_bytes(iw, pw);
+        tmp_ptr = reinterpret_cast<int8_t*>(bundle.get(2)) +
+                  ncb_index.thread_id * tmp_size;
+    }
+    pack_src_int8_nchw_nchw44_dot<stride>(
+            sptr, origin_sptr, ph, pw, remain_right_pad,
+            ih_real - src_top_pad - src_bottom_pad, iw, iw2, src_top_pad,
+            src_bottom_pad, ic, ih * iw, tmp_ptr);
+
+    const int8_t* fptr =
+            reinterpret_cast<int8_t*>(bundle.get(1)) + oc_idx * fh * fw * ic;
+    int8_t* dst = kern_param.dst<int8_t>(batch_id, group_id) +
+                  oh_idx * oh_block * ow * pack_c;
+
+    const int bias_offset = oc_idx;
+    const int32_t* bptr =
+            kern_param.bias<dt_int32>(batch_id, group_id) + bias_offset;
+
+    float scale_bias = kern_param.bias_type.param<dtype::QuantizedS32>().scale;
+    float scale_dst = kern_param.dst_type.param<dtype::QuantizedS8>().scale;
+    Op op(scale_bias, scale_dst);
+    conv_direct_int8_nchw_nchw44_dot<bias_mode, Op, filter, stride>(
+            sptr, fptr, bptr, nullptr, dst, oc_block, ic, ih_real, iw2, oh,
+            oh_block_real, ow, op);
+}
+
+}  // namespace
+
+bool ConvBiasImpl::AlgoDotS8DirectNCHWNCHW44::usable(
+        fallback::ConvBiasImpl*, const NCBKernSizeParam& param,
+        AlgoSelectionStrategy) const {
+    auto&& fm = param.filter_meta;
+    auto fh = fm.spatial[0];
+    int oc = fm.ocpg;
+    int ic = fm.icpg;
+    bool ok_type = ((param.src_type.enumv() == DTypeEnum::QuantizedS8 &&
+                     param.filter_type.enumv() == DTypeEnum::QuantizedS8 &&
+                     (param.dst_type.enumv() == DTypeEnum::QuantizedS8))) &&
+                   (fm.format == param::Convolution::Format::NCHW44);
+    bool ok_src_dst = (oc % 4 == 0 && oc >= 4 && ic < 4);
+    bool ok_filter = fm.spatial_ndim == 2 && fh == fm.spatial[1] &&
+                     (fh == 2 || fh == 3 || fh == 5 || fh == 7);
+    bool ok_slide = fm.dilation[0] == 1 && fm.dilation[1] == 1 &&
+                    fm.stride[0] == fm.stride[1] &&
+                    (fm.stride[0] == 1 || fm.stride[0] == 2);
+    bool ok_conv = !fm.should_flip && param.bias_mode != BiasMode::BIAS;
+    bool avaible = ok_type && ok_src_dst && ok_filter && ok_slide && ok_conv;
+    return avaible;
+}
+
+size_t ConvBiasImpl::AlgoDotS8DirectNCHWNCHW44::get_workspace(
+        fallback::ConvBiasImpl*, const NCBKernSizeParam& param) const {
+    return get_bundle(param).total_size_in_bytes();
+}
+
+SmallVector<ConvBiasImpl::NCBKern>
+ConvBiasImpl::AlgoDotS8DirectNCHWNCHW44::dispatch_kerns(
+        fallback::ConvBiasImpl*, const NCBKernSizeParam& param) const {
+    auto fm = param.filter_meta;
+    const int batch = param.n;
+    const int group = fm.group;
+    WorkspaceBundle wbundle = get_bundle(param);
+    conv_fun do_conv_fun = nullptr;
+    // NOTE: remain_w is not used to gen hash of midout for compatible with
+// shape runtime
+#define DO_CONV_KERN_FUN(stride, filter, bias_mode, op)              \
+    MIDOUT_BEGIN(megdnn_arm_common_conv_bias_int8_nchw44_dot,        \
+                 midout_iv(#stride #filter #bias_mode #op##_hash)) { \
+        do_conv_fun = do_conv_kern<filter, bias_mode, op, stride>;   \
+    }                                                                \
+    MIDOUT_END();
+
+#define GET_OP_PARAM(stride, filter, bias_mode)                          \
+    switch (param.nonlineMode) {                                         \
+        case param::ConvBias::NonlineMode::IDENTITY:                     \
+            DO_CONV_KERN_FUN(stride, filter, bias_mode,                  \
+                             TypeCvtOp<dt_qint32 MEGDNN_COMMA dt_qint8>) \
+            break;                                                       \
+        case param::ConvBias::NonlineMode::RELU:                         \
+            DO_CONV_KERN_FUN(stride, filter, bias_mode,                  \
+                             ReluOp<dt_qint32 MEGDNN_COMMA dt_qint8>)    \
+            break;                                                       \
+        case param::ConvBias::NonlineMode::H_SWISH:                      \
+            DO_CONV_KERN_FUN(stride, filter, bias_mode,                  \
+                             HSwishOp<dt_qint32 MEGDNN_COMMA dt_qint8>)  \
+            break;                                                       \
+        default:                                                         \
+            megdnn_assert(0);                                            \
+            break;                                                       \
+    }
+
+#define GET_BIAS_MODE_PARAM(stride, filter)                                \
+    switch (param.bias_mode) {                                             \
+        case BiasMode::NO_BIAS:                                            \
+            GET_OP_PARAM(stride, filter, BiasMode::NO_BIAS)                \
+            break;                                                         \
+        case BiasMode::BROADCAST_CHANNEL_BIAS:                             \
+            GET_OP_PARAM(stride, filter, BiasMode::BROADCAST_CHANNEL_BIAS) \
+            break;                                                         \
+        default:                                                           \
+            megdnn_assert(0);                                              \
+            break;                                                         \
+    }
+
+#define DISPATCH_CONV_KERN(stride)          \
+    switch (param.filter_meta.spatial[0]) { \
+        case 2:                             \
+            GET_BIAS_MODE_PARAM(stride, 2)  \
+            break;                          \
+        case 3:                             \
+            GET_BIAS_MODE_PARAM(stride, 3)  \
+            break;                          \
+        case 5:                             \
+            GET_BIAS_MODE_PARAM(stride, 5)  \
+            break;                          \
+        case 7:                             \
+            GET_BIAS_MODE_PARAM(stride, 7)  \
+            break;                          \
+        default:                            \
+            megdnn_assert(0);               \
+            break;                          \
+    }
+
+    switch (param.filter_meta.stride[0]) {
+        case 1:
+            DISPATCH_CONV_KERN(1);
+            break;
+        case 2:
+            DISPATCH_CONV_KERN(2);
+            break;
+        default:
+            megdnn_assert(0);
+            break;
+    }
+
+#undef DO_CONV_KERN_FUN
+#undef GET_REMAIN_W_PARAM
+#undef GET_OP_PARAM
+#undef GET_BIAS_MODE_PARAM
+#undef DISPATCH_CONV_KERN
+
+    megdnn_assert(do_conv_fun);
+
+    SmallVector<ConvBiasImpl::NCBKern> ret_kerns;
+    WorkspaceBundle bundle = wbundle;
+    int oh = param.osz[0];
+    int ic = param.filter_meta.icpg;
+    int iw = param.isz[1];
+    int stride_h = param.filter_meta.stride[0];
+
+    int oh_block = l2_block_helper(param.nr_threads, oh,
+                                   ic * iw * sizeof(int8_t) * stride_h);
+
+    CpuNDRange ncb_range = {static_cast<size_t>(batch),
+                            static_cast<size_t>(group),
+                            static_cast<size_t>(div_ceil(oh, oh_block))};
+
+    auto do_trans_weight = [bundle](const NCBKernParam& kern_param,
+                                    const NCBKernIndex& ncb_index) {
+        do_weight_trans(bundle, kern_param, ncb_index, ncb_index.ndrange_id);
+    };
+    ret_kerns.push_back({do_trans_weight, {1}});
+
+    auto do_conv = [bundle, do_conv_fun, ncb_range](
+                           const NCBKernParam& kern_param,
+                           const NCBKernIndex& ncb_index) {
+        do_conv_fun(bundle, kern_param, ncb_index, ncb_index.ndrange_id,
+                    ncb_range);
+    };
+    ret_kerns.push_back({do_conv, ncb_range});
+    return ret_kerns;
+}
+#endif
+
+// vim: syntax=cpp.doxygen

dnn/src/arm_common/conv_bias/int8/dot_direct_nchw_nchw44_kern.h

@@ -0,0 +1,779 @@
+/**
+ * \file
+ * dnn/src/arm_common/conv_bias/int8/dot_direct_nchw_nchw44_kern.h
+ * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
+ *
+ * Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or
+ * implied.
+ */
+#pragma once
+#if __ARM_FEATURE_DOTPROD
+
+#include "src/arm_common/conv_bias/intrinsic_helper.h"
+#include "src/arm_common/elemwise_op.h"
+#include "src/arm_common/simd_macro/marm_neon.h"
+#include "src/common/unroll_macro.h"
+#include "src/common/utils.h"
+#include "src/fallback/conv_bias/common.h"
+
+using namespace megdnn;
+using namespace arm_common;
+namespace {
+template <int src_idx, int weight_idx, int c_dim, typename Func, int ow_block,
+          int stride, typename T, typename T2, typename T3, typename T4>
+struct ShiftCalHelper {
+    static void impl(T& c, T2& src, T3& weight);
+};
+
+template <int src_idx, int weight_idx, typename Func, int stride, typename T,
+          typename T2, typename T3, typename T4>
+struct ShiftCalHelper<src_idx, weight_idx, 2, Func, 8, stride, T, T2, T3, T4> {
+    static void impl(T& c, T2& src, T3& weight) {
+#define cb(step)                                                    \
+    c[0][step * 2] = Func::template impl<(src_idx + step) % 4>(     \
+            c[0][step * 2], weight[0][weight_idx],                  \
+            src[0][(src_idx + step) / 4]);                          \
+    c[1][step * 2] = Func::template impl<(src_idx + step) % 4>(     \
+            c[1][step * 2], weight[1][weight_idx],                  \
+            src[0][(src_idx + step) / 4]);                          \
+    c[0][step * 2 + 1] = Func::template impl<(src_idx + step) % 4>( \
+            c[0][step * 2 + 1], weight[0][weight_idx],              \
+            src[1][(src_idx + step) / 4]);                          \
+    c[1][step * 2 + 1] = Func::template impl<(src_idx + step) % 4>( \
+            c[1][step * 2 + 1], weight[1][weight_idx],              \
+            src[1][(src_idx + step) / 4]);
+
+        UNROLL_CALL_RAW(4, cb);
+#undef cb
+    }
+};
+
+template <int src_idx, int weight_idx, typename Func, int stride, typename T,
+          typename T2, typename T3, typename T4>
+struct ShiftCalHelper<src_idx, weight_idx, 1, Func, 8, stride, T, T2, T3, T4> {
+    static void impl(T& c, T2& src, T3& weight) {
+#define cb(step)                                                    \
+    c[0][step * 2] = Func::template impl<(src_idx + step) % 4>(     \
+            c[0][step * 2], weight[0][weight_idx],                  \
+            src[0][(src_idx + step) / 4]);                          \
+    c[0][step * 2 + 1] = Func::template impl<(src_idx + step) % 4>( \
+            c[0][step * 2 + 1], weight[0][weight_idx],              \
+            src[1][(src_idx + step) / 4]);
+
+        UNROLL_CALL_RAW(4, cb);
+#undef cb
+    }
+};
+
+template <int src_idx, int weight_idx, typename Func, typename T, typename T2,
+          typename T3, typename T4>
+struct ShiftCalHelper<src_idx, weight_idx, 2, Func, 8, 1, T, T2, T3, T4> {
+    static void impl(T& c, T2& src, T3& weight) {
+#define cb(step)                                                           \
+    c[0][step] = Func::template impl<(src_idx + step) % 4>(                \
+            c[0][step], weight[0][weight_idx], src[(src_idx + step) / 4]); \
+    c[1][step] = Func::template impl<(src_idx + step) % 4>(                \
+            c[1][step], weight[1][weight_idx], src[(src_idx + step) / 4]);
+
+        UNROLL_CALL_RAW(8, cb);
+#undef cb
+    }
+};
+
+template <int src_idx, int weight_idx, typename Func, typename T, typename T2,
+          typename T3, typename T4>
+struct ShiftCalHelper<src_idx, weight_idx, 1, Func, 8, 1, T, T2, T3, T4> {
+    static void impl(T& c, T2& src, T3& weight) {
+#define cb(step)                                            \
+    c[0][step] = Func::template impl<(src_idx + step) % 4>( \
+            c[0][step], weight[0][weight_idx], src[(src_idx + step) / 4]);
+
+        UNROLL_CALL_RAW(8, cb);
+#undef cb
+    }
+};
+
+template <int src_idx, int weight_idx, int c_dim, typename FUNC, int ow_block,
+          int stride, typename T, typename T2, typename T3>
+inline void cal_helper(T& c, T2& src, T3& weight) {
+    ShiftCalHelper<src_idx, weight_idx, c_dim, FUNC, ow_block, stride, T, T2,
+                   T3, int>::impl(c, src, weight);
+};
+//! OCHelper is used to trans oc_block to row number of result regs
+template <int oc>
+struct OCHelper {
+public:
+    static const int val = -1;
+};
+
+template <>
+struct OCHelper<4> {
+public:
+    static const int val = 1;
+};
+#if MEGDNN_AARCH64
+template <>
+struct OCHelper<8> {
+public:
+    static const int val = 2;
+};
+#endif
+/**
+ *  oc8_ow8(m = 8, n = 8) and oc4_ow8(m = 4, n = 8) gemm like kernel
+ * */
+template <BiasMode bias_mode, typename Op, int remain_w, int filter_size,
+          int oc_block, int ow_block, int stride>
+struct KerNeonDotXXs2Nchw44Int8 {
+    static void impl(const int8_t* src_ptr, const int8_t* weight_ptr,
+                     const int32_t* bias_ptr, int8_t* dst_ptr, int ic, int ih,
+                     int iw, int ld_dst_oc, const Op& op);
+};
+
+template <BiasMode bias_mode, typename Op, int remain_w, int oc_block,
+          int ow_block, int stride>
+struct KerNeonDotXXs2Nchw44Int8<bias_mode, Op, remain_w, 2, oc_block, ow_block,
+                                stride> {
+    static void impl(const int8_t* src_ptr, const int8_t* weight_ptr,
+                     const int32_t* bias_ptr, int8_t* dst_ptr, int ic, int ih,
+                     int iw, int ld_dst_oc, const Op& op) {
+        constexpr int filter_hight = 2;
+        constexpr int filter_width = 4;
+        constexpr int weight_reg = 1;
+        constexpr int src_reg = 1;
+
+        constexpr int oc_step = 4;
+        constexpr int ic_step = 1;
+        constexpr int pack_iw_len = 1;
+        constexpr int simd_len = 16;
+
+        const int ld_bias = oc_step;
+        const int ic_stride = ih * iw * pack_iw_len;
+        const int ld_weight_oc = oc_step * filter_hight * filter_width * ic;
+        constexpr int c_dim = OCHelper<oc_block>::val;
+
+        int32x4_t c[c_dim][8];
+        init_ocx_ow8<c_dim, bias_mode, ow_block>(c, bias_ptr, ld_bias);
+        for (int ic_idx = 0; ic_idx < ic; ic_idx += ic_step) {
+            int8x16_t src[2][src_reg];
+            int8x16_t weight[c_dim][weight_reg];
+            // row 0
+            load_helper<src_reg, 0, simd_len, 2, Vld1q_s8>(
+                    src, src_ptr + 0 * iw, stride);
+            load_helper<weight_reg, 0, simd_len, c_dim, Vld1q_s8>(
+                    weight, weight_ptr, ld_weight_oc);
+            cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,
+                                                                       weight);
+            // row 1
+            load_helper<src_reg, 0, simd_len, 2, Vld1q_s8>(
+                    src, src_ptr + 1 * iw, stride);
+            load_helper<weight_reg, 1 * simd_len, simd_len, c_dim, Vld1q_s8>(
+                    weight, weight_ptr, ld_weight_oc);
+            cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,
+                                                                       weight);
+
+            src_ptr += ic_stride;
+            weight_ptr += filter_hight * filter_width * oc_step;
+        }
+        store_ocx_ow8_remain_static_dt<c_dim, remain_w, Op, dt_qint8*>(
+                c, op, dst_ptr, ld_dst_oc);
+    }
+};
+
+template <BiasMode bias_mode, typename Op, int remain_w, int oc_block,
+          int ow_block, int stride>
+struct KerNeonDotXXs2Nchw44Int8<bias_mode, Op, remain_w, 3, oc_block, ow_block,
+                                stride> {
+    static void impl(const int8_t* src_ptr, const int8_t* weight_ptr,
+                     const int32_t* bias_ptr, int8_t* dst_ptr, int ic, int ih,
+                     int iw, int ld_dst_oc, const Op& op) {
+        constexpr int filter_hight = 3;
+        constexpr int filter_width = 4;
+        constexpr int weight_reg = 1;
+        constexpr int src_reg = 1;
+
+        constexpr int oc_step = 4;
+        constexpr int ic_step = 1;
+        constexpr int pack_iw_len = 1;
+        constexpr int simd_len = 16;
+
+        const int ld_bias = oc_step;
+        const int ic_stride = ih * iw * pack_iw_len;
+        const int ld_weight_oc = oc_step * filter_hight * filter_width * ic;
+        constexpr int c_dim = OCHelper<oc_block>::val;
+
+        int32x4_t c[c_dim][8];
+        init_ocx_ow8<c_dim, bias_mode, ow_block>(c, bias_ptr, ld_bias);
+        for (int ic_idx = 0; ic_idx < ic; ic_idx += ic_step) {
+            int8x16_t src[2][src_reg];
+            int8x16_t weight[c_dim][weight_reg];
+            // row 0
+            load_helper<src_reg, 0, simd_len, 2, Vld1q_s8>(
+                    src, src_ptr + 0 * iw, stride);
+            load_helper<weight_reg, 0, simd_len, c_dim, Vld1q_s8>(
+                    weight, weight_ptr, ld_weight_oc);
+            cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,
+                                                                       weight);
+            // row 1
+            load_helper<src_reg, 0, simd_len, 2, Vld1q_s8>(
+                    src, src_ptr + 1 * iw, stride);
+            load_helper<weight_reg, 1 * simd_len, simd_len, c_dim, Vld1q_s8>(
+                    weight, weight_ptr, ld_weight_oc);
+            cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,
+                                                                       weight);
+            // row 2
+            load_helper<src_reg, 0, simd_len, 2, Vld1q_s8>(
+                    src, src_ptr + 2 * iw, stride);
+            load_helper<weight_reg, 2 * simd_len, simd_len, c_dim, Vld1q_s8>(
+                    weight, weight_ptr, ld_weight_oc);
+            cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,
+                                                                       weight);
+
+            src_ptr += ic_stride;
+            weight_ptr += filter_hight * filter_width * oc_step;
+        }
+        store_ocx_ow8_remain_static_dt<c_dim, remain_w, Op, dt_qint8*>(
+                c, op, dst_ptr, ld_dst_oc);
+    }
+};
+
+template <BiasMode bias_mode, typename Op, int remain_w, int oc_block,
+          int ow_block, int stride>
+struct KerNeonDotXXs2Nchw44Int8<bias_mode, Op, remain_w, 5, oc_block, ow_block,
+                                stride> {
+    static void impl(const int8_t* src_ptr, const int8_t* weight_ptr,
+                     const int32_t* bias_ptr, int8_t* dst_ptr, int ic, int ih,
+                     int iw, int ld_dst_oc, const Op& op) {
+        constexpr int filter_hight = 5;
+        constexpr int filter_width = 8;
+        constexpr int src_reg = 2;
+        constexpr int weight_reg = 2;
+
+        constexpr int oc_step = 4;
+        constexpr int ic_step = 1;
+        constexpr int pack_iw_len = 1;
+        constexpr int simd_len = 16;
+
+        const int ld_bias = oc_step;
+        const int ic_stride = ih * iw * pack_iw_len;
+        const int ld_weight_oc = oc_step * filter_hight * filter_width * ic;
+        constexpr int c_dim = OCHelper<oc_block>::val;
+
+        int32x4_t c[c_dim][8];
+        init_ocx_ow8<c_dim, bias_mode, ow_block>(c, bias_ptr, ld_bias);
+
+        for (int ic_idx = 0; ic_idx < ic; ic_idx += ic_step) {
+            int8x16_t src[2][src_reg];
+            int8x16_t weight[c_dim][weight_reg];
+#define cb(step)                                                             \
+    load_helper<src_reg, 0, simd_len, 2, Vld1q_s8>(src, src_ptr + step * iw, \
+                                                   stride);                  \
+    load_helper<weight_reg, 0, simd_len, c_dim, Vld1q_s8>(                   \
+            weight, weight_ptr + step * 2 * simd_len, ld_weight_oc);         \
+    cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,       \
+                                                               weight);      \
+    cal_helper<1, 1, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src, weight);
+            UNROLL_CALL_RAW(5, cb);
+#undef cb
+            src_ptr += ic_stride;
+            weight_ptr += 5 * 32;
+        }
+        store_ocx_ow8_remain_static_dt<c_dim, remain_w, Op, dt_qint8*>(
+                c, op, dst_ptr, ld_dst_oc);
+    }
+};
+
+/**
+ * oc = 8, ow = 8
+ * dot 4 element, pad last filter and do twice dot every row filter, filter like
+ * below
+ * --------------------------
+ * |x, x, x, x,| x, x, x, 0 |
+ * --------------------------
+ **/
+template <BiasMode bias_mode, typename Op, int remain_w, int oc_block,
+          int ow_block, int stride>
+struct KerNeonDotXXs2Nchw44Int8<bias_mode, Op, remain_w, 7, oc_block, ow_block,
+                                stride> {
+    static void impl(const int8_t* src_ptr, const int8_t* weight_ptr,
+                     const int32_t* bias_ptr, int8_t* dst_ptr, int ic, int ih,
+                     int iw, int ld_dst_oc, const Op& op) {
+        constexpr int filter_hight = 7;
+        constexpr int filter_width = 8;
+        constexpr int src_reg = 2;
+        constexpr int weight_reg = 2;
+
+        constexpr int oc_step = 4;
+        constexpr int ic_step = 1;
+        constexpr int pack_iw_len = 1;
+        constexpr int simd_len = 16;
+
+        const int ld_bias = oc_step;
+        const int ic_stride = ih * iw * pack_iw_len;
+        const int ld_weight_oc = oc_step * filter_hight * filter_width * ic;
+        constexpr int c_dim = OCHelper<oc_block>::val;
+
+        int32x4_t c[c_dim][8];
+        init_ocx_ow8<c_dim, bias_mode, ow_block>(c, bias_ptr, ld_bias);
+
+        for (int ic_idx = 0; ic_idx < ic; ic_idx += ic_step) {
+            int8x16_t src[2][src_reg];
+            int8x16_t weight[c_dim][weight_reg];
+#define cb(step)                                                             \
+    load_helper<src_reg, 0, simd_len, 2, Vld1q_s8>(src, src_ptr + step * iw, \
+                                                   stride);                  \
+    load_helper<weight_reg, 0, simd_len, c_dim, Vld1q_s8>(                   \
+            weight, weight_ptr + step * 2 * simd_len, ld_weight_oc);         \
+    cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,       \
+                                                               weight);      \
+    cal_helper<1, 1, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src, weight);
+            UNROLL_CALL_RAW(7, cb);
+#undef cb
+            src_ptr += ic_stride;
+            weight_ptr += 7 * 32;
+        }
+        store_ocx_ow8_remain_static_dt<c_dim, remain_w, Op, dt_qint8*>(
+                c, op, dst_ptr, ld_dst_oc);
+    }
+};
+////////////////////stride 1///////////////////
+template <BiasMode bias_mode, typename Op, int remain_w, int oc_block,
+          int ow_block>
+struct KerNeonDotXXs2Nchw44Int8<bias_mode, Op, remain_w, 2, oc_block, ow_block,
+                                1> {
+    static void impl(const int8_t* src_ptr, const int8_t* weight_ptr,
+                     const int32_t* bias_ptr, int8_t* dst_ptr, int ic, int ih,
+                     int iw, int ld_dst_oc, const Op& op) {
+        constexpr int stride = 1;
+        constexpr int filter_hight = 2;
+        constexpr int filter_width = 4;
+        constexpr int weight_reg = 2;
+        constexpr int src_reg = 2;
+
+        constexpr int oc_step = 4;
+        constexpr int ic_step = 1;
+        constexpr int pack_iw_len = 4;
+        constexpr int simd_len = 16;
+
+        const int ld_bias = oc_step;
+        const int ic_stride = ih * iw * pack_iw_len;
+        const int ld_weight_oc = oc_step * filter_hight * filter_width * ic;
+        constexpr int c_dim = OCHelper<oc_block>::val;
+
+        int32x4_t c[c_dim][8];
+        init_ocx_ow8<c_dim, bias_mode, ow_block>(c, bias_ptr, ld_bias);
+        for (int ic_idx = 0; ic_idx < ic; ic_idx += ic_step) {
+            int8x16_t src[src_reg];
+            int8x16_t weight[c_dim][weight_reg];
+            // row 0
+            load_helper<src_reg, 0, simd_len, 0, Vld1q_s8>(
+                    src, src_ptr + 0 * iw * pack_iw_len, 0);
+            load_helper<weight_reg, 0, simd_len, c_dim, Vld1q_s8>(
+                    weight, weight_ptr, ld_weight_oc);
+            cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,
+                                                                       weight);
+            // row 1
+            load_helper<src_reg, 0, simd_len, 0, Vld1q_s8>(
+                    src, src_ptr + 1 * iw * pack_iw_len, 0);
+            cal_helper<0, 1, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,
+                                                                       weight);
+
+            src_ptr += ic_stride;
+            weight_ptr += filter_hight * filter_width * oc_step;
+        }
+        store_ocx_ow8_remain_static_dt<c_dim, remain_w, Op, dt_qint8*>(
+                c, op, dst_ptr, ld_dst_oc);
+    }
+};
+template <BiasMode bias_mode, typename Op, int remain_w, int oc_block,
+          int ow_block>
+struct KerNeonDotXXs2Nchw44Int8<bias_mode, Op, remain_w, 3, oc_block, ow_block,
+                                1> {
+    static void impl(const int8_t* src_ptr, const int8_t* weight_ptr,
+                     const int32_t* bias_ptr, int8_t* dst_ptr, int ic, int ih,
+                     int iw, int ld_dst_oc, const Op& op) {
+        constexpr int stride = 1;
+        constexpr int filter_hight = 3;
+        constexpr int filter_width = 4;
+        constexpr int weight_reg = 3;
+        constexpr int src_reg = 2;
+
+        constexpr int oc_step = 4;
+        constexpr int ic_step = 1;
+        constexpr int pack_iw_len = 4;
+        constexpr int simd_len = 16;
+
+        const int ld_bias = oc_step;
+        const int ic_stride = ih * iw * pack_iw_len;
+        const int ld_weight_oc = oc_step * filter_hight * filter_width * ic;
+        constexpr int c_dim = OCHelper<oc_block>::val;
+
+        int32x4_t c[c_dim][8];
+        init_ocx_ow8<c_dim, bias_mode, ow_block>(c, bias_ptr, ld_bias);
+        for (int ic_idx = 0; ic_idx < ic; ic_idx += ic_step) {
+            int8x16_t src[src_reg];
+            int8x16_t weight[c_dim][weight_reg];
+            // row 0
+            load_helper<src_reg, 0, simd_len, 0, Vld1q_s8>(
+                    src, src_ptr + 0 * iw * pack_iw_len, 0);
+            load_helper<weight_reg, 0, simd_len, c_dim, Vld1q_s8>(
+                    weight, weight_ptr, ld_weight_oc);
+            cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,
+                                                                       weight);
+            // row 1
+            load_helper<src_reg, 0, simd_len, 0, Vld1q_s8>(
+                    src, src_ptr + 1 * iw * pack_iw_len, 0);
+            cal_helper<0, 1, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,
+                                                                       weight);
+            // row 2
+            load_helper<src_reg, 0, simd_len, 0, Vld1q_s8>(
+                    src, src_ptr + 2 * iw * pack_iw_len, 0);
+            cal_helper<0, 2, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,
+                                                                       weight);
+
+            src_ptr += ic_stride;
+            weight_ptr += filter_hight * filter_width * oc_step;
+        }
+        store_ocx_ow8_remain_static_dt<c_dim, remain_w, Op, dt_qint8*>(
+                c, op, dst_ptr, ld_dst_oc);
+    }
+};
+
+template <BiasMode bias_mode, typename Op, int remain_w, int oc_block,
+          int ow_block>
+struct KerNeonDotXXs2Nchw44Int8<bias_mode, Op, remain_w, 5, oc_block, ow_block,
+                                1> {
+    static void impl(const int8_t* src_ptr, const int8_t* weight_ptr,
+                     const int32_t* bias_ptr, int8_t* dst_ptr, int ic, int ih,
+                     int iw, int ld_dst_oc, const Op& op) {
+        constexpr int stride = 1;
+        constexpr int filter_hight = 5;
+        constexpr int filter_width = 8;
+        constexpr int src_reg = 3;
+        constexpr int weight_reg = 2;
+
+        constexpr int oc_step = 4;
+        constexpr int ic_step = 1;
+        constexpr int pack_iw_len = 4;
+        constexpr int simd_len = 16;
+
+        const int ld_bias = oc_step;
+        const int ic_stride = ih * iw * pack_iw_len;
+        const int ld_weight_oc = oc_step * filter_hight * filter_width * ic;
+        constexpr int c_dim = OCHelper<oc_block>::val;
+
+        int32x4_t c[c_dim][8];
+        init_ocx_ow8<c_dim, bias_mode, ow_block>(c, bias_ptr, ld_bias);
+
+        for (int ic_idx = 0; ic_idx < ic; ic_idx += ic_step) {
+            int8x16_t src[src_reg];
+            int8x16_t weight[c_dim][weight_reg];
+#define cb(step)                                                        \
+    load_helper<src_reg, 0, simd_len, 0, Vld1q_s8>(                     \
+            src, src_ptr + step * iw * pack_iw_len, 0);                 \
+    load_helper<weight_reg, 0, simd_len, c_dim, Vld1q_s8>(              \
+            weight, weight_ptr + step * 2 * simd_len, ld_weight_oc);    \
+    cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,  \
+                                                               weight); \
+    cal_helper<4, 1, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src, weight);
+
+            UNROLL_CALL_RAW(5, cb);
+#undef cb
+            src_ptr += ic_stride;
+            weight_ptr += filter_hight * filter_width * oc_step;
+        }
+        store_ocx_ow8_remain_static_dt<c_dim, remain_w, Op, dt_qint8*>(
+                c, op, dst_ptr, ld_dst_oc);
+    }
+};
+
+template <BiasMode bias_mode, typename Op, int remain_w, int oc_block,
+          int ow_block>
+struct KerNeonDotXXs2Nchw44Int8<bias_mode, Op, remain_w, 7, oc_block, ow_block,
+                                1> {
+    static void impl(const int8_t* src_ptr, const int8_t* weight_ptr,
+                     const int32_t* bias_ptr, int8_t* dst_ptr, int ic, int ih,
+                     int iw, int ld_dst_oc, const Op& op) {
+        constexpr int stride = 1;
+        constexpr int filter_hight = 7;
+        constexpr int filter_width = 8;
+        constexpr int src_reg = 3;
+        constexpr int weight_reg = 2;
+
+        constexpr int oc_step = 4;
+        constexpr int ic_step = 1;
+        constexpr int pack_iw_len = 4;
+        constexpr int simd_len = 16;
+
+        const int ld_bias = oc_step;
+        const int ic_stride = ih * iw * pack_iw_len;
+        const int ld_weight_oc = oc_step * filter_hight * filter_width * ic;
+        constexpr int c_dim = OCHelper<oc_block>::val;
+
+        int32x4_t c[c_dim][8];
+        init_ocx_ow8<c_dim, bias_mode, ow_block>(c, bias_ptr, ld_bias);
+
+        for (int ic_idx = 0; ic_idx < ic; ic_idx += ic_step) {
+            int8x16_t src[src_reg];
+            int8x16_t weight[c_dim][weight_reg];
+#define cb(step)                                                        \
+    load_helper<src_reg, 0, simd_len, 0, Vld1q_s8>(                     \
+            src, src_ptr + step * iw * pack_iw_len, 0);                 \
+    load_helper<weight_reg, 0, simd_len, c_dim, Vld1q_s8>(              \
+            weight, weight_ptr + step * 2 * simd_len, ld_weight_oc);    \
+    cal_helper<0, 0, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src,  \
+                                                               weight); \
+    cal_helper<4, 1, c_dim, Vdotq_laneq_s32, ow_block, stride>(c, src, weight);
+
+            UNROLL_CALL_RAW(7, cb);
+#undef cb
+            src_ptr += ic_stride;
+            weight_ptr += filter_hight * filter_width * oc_step;
+        }
+        store_ocx_ow8_remain_static_dt<c_dim, remain_w, Op, dt_qint8*>(
+                c, op, dst_ptr, ld_dst_oc);
+    }
+};
+
+template <int stride>
+void pack_src_int8_nchw_nchw44_dot(int8_t* sptr_base, const int8_t* sptr_origin,
+                                   const int, const int pw, const int,
+                                   const int ih, const int iw, const int iw2,
+                                   const int pad_top, const int pad_bottom,
+                                   const int ic, const int ic_stride, int8_t*) {
+    constexpr int ic_step = 1;
+    rep_step(ic_idx, ic, ic_step) {
+        const int8_t* sptr = sptr_origin + ic_idx * ic_stride;
+        memset(sptr_base, 0,
+               sizeof(int8_t) * ic_step * iw2 * (ih + pad_top + pad_bottom));
+        sptr_base += iw2 * pad_top * ic_step;
+        rep(ih_idx, ih) {
+            memcpy(sptr_base + pw * ic_step, sptr,
+                   sizeof(int8_t) * iw * ic_step);
+            sptr_base += iw2 * ic_step;
+            sptr += iw * ic_step;
+        }
+        sptr_base += iw2 * pad_bottom * ic_step;
+    }
+}
+
+template <>
+void pack_src_int8_nchw_nchw44_dot<1>(int8_t* sptr_base,
+                                      const int8_t* sptr_origin, const int,
+                                      const int pw, const int, const int ih,
+                                      const int iw, const int iw2,
+                                      const int pad_top, const int pad_bottom,
+                                      const int ic, const int ic_stride,
+                                      int8_t* temp_ptr) {
+    static uint8_t reorder_idx[16] = {0, 1, 2, 3, 1, 2, 3, 4,
+                                      2, 3, 4, 5, 3, 4, 5, 6};
+    uint8x16_t tbl_idx = vld1q_u8(&reorder_idx[0]);
+
+    constexpr int iw_step = 16;
+    constexpr int pack_iw_len = 4;
+    const int iw_with_pad = iw + 2 * pw;
+    const int iw_with_pad_end = iw_with_pad / iw_step * iw_step;
+    rep(ic_idx, ic) {
+        const int8_t* sptr = sptr_origin + ic_idx * ic_stride;
+        memset(sptr_base, 0,
+               sizeof(int8_t) * iw2 * (ih + pad_top + pad_bottom) *
+                       pack_iw_len);
+        sptr_base += iw2 * pad_top * pack_iw_len;
+        rep(ih_idx, ih) {
+            memset(temp_ptr, 0, iw_with_pad * sizeof(int8_t));
+            memcpy(temp_ptr + pw, sptr, sizeof(int8_t) * iw);
+            for (int iw_idx = 0; iw_idx < iw_with_pad_end; iw_idx += iw_step) {
+                int8x16_t src[4];
+                int8x16_t dst[4];
+                src[0] = vld1q_s8(temp_ptr + iw_idx);
+                src[1] = vld1q_s8(temp_ptr + iw_idx + 4);
+                src[2] = vld1q_s8(temp_ptr + iw_idx + 8);
+                src[3] = vld1q_s8(temp_ptr + iw_idx + 12);
+                dst[0] = vqtbl1q_s8(src[0], tbl_idx);
+                dst[1] = vqtbl1q_s8(src[1], tbl_idx);
+                dst[2] = vqtbl1q_s8(src[2], tbl_idx);
+                dst[3] = vqtbl1q_s8(src[3], tbl_idx);
+                vst1q_s8(sptr_base + iw_idx * pack_iw_len + 0, dst[0]);
+                vst1q_s8(sptr_base + iw_idx * pack_iw_len + 16, dst[1]);
+                vst1q_s8(sptr_base + iw_idx * pack_iw_len + 32, dst[2]);
+                vst1q_s8(sptr_base + iw_idx * pack_iw_len + 48, dst[3]);
+            }
+            for (int iw_idx = iw_with_pad_end; iw_idx < iw_with_pad; ++iw_idx) {
+                *(sptr_base + iw_idx * pack_iw_len + 0) =
+                        *(temp_ptr + iw_idx + 0);
+                *(sptr_base + iw_idx * pack_iw_len + 1) =
+                        *(temp_ptr + iw_idx + 1);
+                *(sptr_base + iw_idx * pack_iw_len + 2) =
+                        *(temp_ptr + iw_idx + 2);
+                *(sptr_base + iw_idx * pack_iw_len + 3) =
+                        *(temp_ptr + iw_idx + 3);
+            }
+            sptr_base += iw2 * pack_iw_len;
+            sptr += iw;
+        }
+        sptr_base += iw2 * pad_bottom * pack_iw_len;
+    }
+}
+
+static inline void pack_weight_int8_nchw_nchw44_dot(int8_t* dst_ptr,
+                                                    const int8_t* src_ptr,
+                                                    const int oc, const int ic,
+                                                    const int fh, const int fw,
+                                                    const int fw2) {
+    constexpr int oc_step = 4;
+    const int fw_remain = fw2 - fw;
+    const int dst_ic_stride = fh * fw2;
+    const int oc_step_stride = fh * fw2 * ic * oc_step;
+    static const uint8_t transpose_4x4_idx[16] = {0, 4, 8,  12, 1, 5, 9,  13,
+                                                  2, 6, 10, 14, 3, 7, 11, 15};
+    uint8x16_t tbl_transpose_4x4 = vld1q_u8(&transpose_4x4_idx[0]);
+    rep_step(oc_idx, oc, oc_step) {
+        int32_t* dst_temp_ptr =
+                reinterpret_cast<int32_t*>(dst_ptr + oc_idx * ic * fh * fw2);
+        const int32_t* src_temp_ptr = reinterpret_cast<const int32_t*>(
+                src_ptr + oc_idx * ic * fh * fw);
+        // transpose ic and pad
+        rep(fh_idx, fh) {
+            rep(fw_idx, fw) {
+                rep(ic_idx, ic) {
+                    *(dst_temp_ptr + ic_idx * dst_ic_stride) = *src_temp_ptr;
+                    src_temp_ptr++;
+                }
+                dst_temp_ptr++;
+            }
+            rep(ic_idx, ic) {
+                memset(dst_temp_ptr + ic_idx * dst_ic_stride, 0,
+                       sizeof(int8_t) * oc_step * fw_remain);
+            }
+            dst_temp_ptr += fw_remain;
+        }
+        // transpose fw oc
+        int8_t* trans_dst_temp_ptr =
+                reinterpret_cast<int8_t*>(dst_ptr + oc_idx * ic * fh * fw2);
+
+        rep_step(idx, oc_step_stride, 16) {
+            int8x16_t temp = vld1q_s8(trans_dst_temp_ptr + idx);
+            vst1q_s8(trans_dst_temp_ptr + idx,
+                     vqtbl1q_s8(temp, tbl_transpose_4x4));
+        }
+    }
+}
+
+template <BiasMode bias_mode, typename Op, int filter_size, int stride>
+static void conv_direct_int8_nchw_nchw44_dot(
+        const int8_t* src, const int8_t* filter, const int32_t* bias,
+        int32_t* temp, int8_t* dst, const int oc, const int ic, const int ih,
+        const int iw, const int oh, const int oh_block, const int ow,
+        const Op& op) {
+    MEGDNN_MARK_USED_VAR(temp);
+    constexpr int fh = filter_size;
+    constexpr int fw = (filter_size + 3) / 4 * 4;
+#if MEGDNN_AARCH64
+    constexpr int big_oc_step = 8;
+#else
+    constexpr int big_oc_step = 4;
+#endif
+    constexpr int oc_step = 4;
+    constexpr int ih_step = 1;
+    constexpr int oh_step = 1;
+    constexpr int ow_step = 8;
+    constexpr int stride_h = stride;
+    constexpr int stride_w = stride;
+    constexpr int pack_iw_len = stride == 2 ? 1 : 4;
+
+    const int img_stride = oh * ow;
+    const int ow_end = ow / ow_step * ow_step;
+    const int ow_remain = ow - ow_end;
+    const int oc_end = oc / big_oc_step * big_oc_step;
+    const int oc_remain = oc - oc_end;
+    const int ld_dst_oc = oc_step * img_stride;
+
+    using remain_fun =
+            std::function<void(const int8_t* src_ptr, const int8_t* weight_ptr,
+                               const int32_t* bias_ptr, int8_t* dst_ptr, int ic,
+                               int ih, int iw, int ld_dst_oc, const Op& op)>;
+    remain_fun kern_big_oc_remain = nullptr;
+    remain_fun kern_small_oc_remain = nullptr;
+    switch (ow_remain) {
+#define cb(step)                                                              \
+    case step:                                                                \
+        kern_big_oc_remain =                                                  \
+                KerNeonDotXXs2Nchw44Int8<bias_mode, Op, step, filter_size,    \
+                                         big_oc_step, ow_step, stride>::impl; \
+        kern_small_oc_remain =                                                \
+                KerNeonDotXXs2Nchw44Int8<bias_mode, Op, step, filter_size,    \
+                                         oc_step, ow_step, stride>::impl;     \
+        break;
+
+        UNROLL_CALL_RAW(8, cb);
+        default:
+            megdnn_assert(0, "no remain %d for kern", ow_remain);
+    }
+
+    for (int oc_idx = 0; oc_idx < oc_end; oc_idx += big_oc_step) {
+        const int weight_offset = oc_idx * ic * fh * fw;
+        for (int oh_idx = 0; oh_idx < oh_block; oh_idx += oh_step) {
+            for (int ow_idx = 0; ow_idx < ow_end; ow_idx += ow_step) {
+                const int src_offset =
+                        (oh_idx * stride_h * iw + ow_idx * stride_w * ih_step) *
+                        pack_iw_len;
+                const int dst_offset =
+                        oc_idx * img_stride + (oh_idx * ow + ow_idx) * oc_step;
+                KerNeonDotXXs2Nchw44Int8<bias_mode, Op, ow_step, filter_size,
+                                         big_oc_step, ow_step,
+                                         stride>::impl(src + src_offset,
+                                                       filter + weight_offset,
+                                                       bias + oc_idx,
+                                                       dst + dst_offset, ic, ih,
+                                                       iw, ld_dst_oc, op);
+            }
+            if (ow_remain > 0) {
+                const int src_offset =
+                        (oh_idx * stride_h * iw + ow_end * stride_w * ih_step) *
+                        pack_iw_len;
+                const int dst_offset =
+                        oc_idx * img_stride + (oh_idx * ow + ow_end) * oc_step;
+                kern_big_oc_remain(src + src_offset, filter + weight_offset,
+                                   bias + oc_idx, dst + dst_offset, ic, ih, iw,
+                                   ld_dst_oc, op);
+            }
+        }
+    }
+    if (oc_remain > 0) {
+        int oc_idx = oc_end;
+        const int weight_offset = oc_idx * ic * fh * fw;
+        for (int oh_idx = 0; oh_idx < oh_block; oh_idx += oh_step) {
+            for (int ow_idx = 0; ow_idx < ow_end; ow_idx += ow_step) {
+                const int src_offset =
+                        (oh_idx * stride_h * iw + ow_idx * stride_w * ih_step) *
+                        pack_iw_len;
+                const int dst_offset =
+                        oc_idx * img_stride + (oh_idx * ow + ow_idx) * oc_step;
+                KerNeonDotXXs2Nchw44Int8<bias_mode, Op, ow_step, filter_size,
+                                         oc_step, ow_step,
+                                         stride>::impl(src + src_offset,
+                                                       filter + weight_offset,
+                                                       bias + oc_idx,
+                                                       dst + dst_offset, ic, ih,
+                                                       iw, ld_dst_oc, op);
+            }
+            if (ow_remain > 0) {
+                const int src_offset =
+                        (oh_idx * stride_h * iw + ow_end * stride_w * ih_step) *
+                        pack_iw_len;
+                const int dst_offset =
+                        oc_idx * img_stride + (oh_idx * ow + ow_end) * oc_step;
+                kern_small_oc_remain(src + src_offset, filter + weight_offset,
+                                     bias + oc_idx, dst + dst_offset, ic, ih,
+                                     iw, ld_dst_oc, op);
+            }
+        }
+    }
+}
+
+}  // namespace
+#endif
+// vim: syntax=cpp.doxygen

dnn/src/arm_common/conv_bias/intrinsic_helper.h

@@ -176,187 +176,202 @@ inline void store_ocx_ow4_remain_static(T& c, const Op& op, int8_t* dst_ptr,
     StoreOcxOw4Remain<c_dim, ow_remain, Op, T>::impl(c, op, dst_ptr, ld_dst_oc);
 }
 ////////////////////Store_OCX_OW8_Remain/////////////////////////
-template <int c_dim, int ow_remain, typename Op, typename T>
+template <int c_dim, int ow_remain, typename Op, typename T, typename T2,
+          typename T3>
 struct StoreOcxOw8Remain {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int ld_dst_oc);
+    static void impl(T& c, const Op& op, T2 dst_ptr, int ld_dst_oc);
 };
 
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<2, 0, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int ld_dst_oc) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
-        op({{c[0][4], c[0][5]}}, dst_ptr + 16);
-        op({{c[0][6], c[0][7]}}, dst_ptr + 24);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<2, 0, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int ld_dst_oc) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
+        op({{c[0][4], c[0][5]}}, reinterpret_cast<T3>(dst_ptr + 16));
+        op({{c[0][6], c[0][7]}}, reinterpret_cast<T3>(dst_ptr + 24));
 
-        op({{c[1][0], c[1][1]}}, dst_ptr + ld_dst_oc);
-        op({{c[1][2], c[1][3]}}, dst_ptr + ld_dst_oc + 8);
-        op({{c[1][4], c[1][5]}}, dst_ptr + ld_dst_oc + 16);
-        op({{c[1][6], c[1][7]}}, dst_ptr + ld_dst_oc + 24);
+        op({{c[1][0], c[1][1]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc));
+        op({{c[1][2], c[1][3]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 8));
+        op({{c[1][4], c[1][5]}},
+           reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 16));
+        op({{c[1][6], c[1][7]}},
+           reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 24));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<2, 8, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int ld_dst_oc) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
-        op({{c[0][4], c[0][5]}}, dst_ptr + 16);
-        op({{c[0][6], c[0][7]}}, dst_ptr + 24);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<2, 8, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int ld_dst_oc) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
+        op({{c[0][4], c[0][5]}}, reinterpret_cast<T3>(dst_ptr + 16));
+        op({{c[0][6], c[0][7]}}, reinterpret_cast<T3>(dst_ptr + 24));
 
-        op({{c[1][0], c[1][1]}}, dst_ptr + ld_dst_oc);
-        op({{c[1][2], c[1][3]}}, dst_ptr + ld_dst_oc + 8);
-        op({{c[1][4], c[1][5]}}, dst_ptr + ld_dst_oc + 16);
-        op({{c[1][6], c[1][7]}}, dst_ptr + ld_dst_oc + 24);
+        op({{c[1][0], c[1][1]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc));
+        op({{c[1][2], c[1][3]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 8));
+        op({{c[1][4], c[1][5]}},
+           reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 16));
+        op({{c[1][6], c[1][7]}},
+           reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 24));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<2, 7, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int ld_dst_oc) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
-        op({{c[0][4], c[0][5]}}, dst_ptr + 16);
-        op(c[0][6], dst_ptr + 24);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<2, 7, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int ld_dst_oc) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
+        op({{c[0][4], c[0][5]}}, reinterpret_cast<T3>(dst_ptr + 16));
+        op(c[0][6], reinterpret_cast<T3>(dst_ptr + 24));
 
-        op({{c[1][0], c[1][1]}}, dst_ptr + ld_dst_oc);
-        op({{c[1][2], c[1][3]}}, dst_ptr + ld_dst_oc + 8);
-        op({{c[1][4], c[1][5]}}, dst_ptr + ld_dst_oc + 16);
-        op(c[1][6], dst_ptr + ld_dst_oc + 24);
+        op({{c[1][0], c[1][1]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc));
+        op({{c[1][2], c[1][3]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 8));
+        op({{c[1][4], c[1][5]}},
+           reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 16));
+        op(c[1][6], reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 24));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<2, 6, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int ld_dst_oc) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
-        op({{c[0][4], c[0][5]}}, dst_ptr + 16);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<2, 6, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int ld_dst_oc) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
+        op({{c[0][4], c[0][5]}}, reinterpret_cast<T3>(dst_ptr + 16));
 
-        op({{c[1][0], c[1][1]}}, dst_ptr + ld_dst_oc);
-        op({{c[1][2], c[1][3]}}, dst_ptr + ld_dst_oc + 8);
-        op({{c[1][4], c[1][5]}}, dst_ptr + ld_dst_oc + 16);
+        op({{c[1][0], c[1][1]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc));
+        op({{c[1][2], c[1][3]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 8));
+        op({{c[1][4], c[1][5]}},
+           reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 16));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<2, 5, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int ld_dst_oc) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
-        op(c[0][4], dst_ptr + 16);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<2, 5, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int ld_dst_oc) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
+        op(c[0][4], reinterpret_cast<T3>(dst_ptr + 16));
 
-        op({{c[1][0], c[1][1]}}, dst_ptr + ld_dst_oc);
-        op({{c[1][2], c[1][3]}}, dst_ptr + ld_dst_oc + 8);
-        op(c[1][4], dst_ptr + ld_dst_oc + 16);
+        op({{c[1][0], c[1][1]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc));
+        op({{c[1][2], c[1][3]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 8));
+        op(c[1][4], reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 16));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<2, 4, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int ld_dst_oc) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<2, 4, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int ld_dst_oc) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
 
-        op({{c[1][0], c[1][1]}}, dst_ptr + ld_dst_oc);
-        op({{c[1][2], c[1][3]}}, dst_ptr + ld_dst_oc + 8);
+        op({{c[1][0], c[1][1]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc));
+        op({{c[1][2], c[1][3]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 8));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<2, 3, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int ld_dst_oc) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op(c[0][2], dst_ptr + 8);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<2, 3, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int ld_dst_oc) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op(c[0][2], reinterpret_cast<T3>(dst_ptr + 8));
 
-        op({{c[1][0], c[1][1]}}, dst_ptr + ld_dst_oc);
-        op(c[1][2], dst_ptr + ld_dst_oc + 8);
+        op({{c[1][0], c[1][1]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc));
+        op(c[1][2], reinterpret_cast<T3>(dst_ptr + ld_dst_oc + 8));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<2, 2, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int ld_dst_oc) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[1][0], c[1][1]}}, dst_ptr + ld_dst_oc);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<2, 2, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int ld_dst_oc) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[1][0], c[1][1]}}, reinterpret_cast<T3>(dst_ptr + ld_dst_oc));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<2, 1, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int ld_dst_oc) {
-        op(c[0][0], dst_ptr);
-        op(c[1][0], dst_ptr + ld_dst_oc);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<2, 1, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int ld_dst_oc) {
+        op(c[0][0], reinterpret_cast<T3>(dst_ptr));
+        op(c[1][0], reinterpret_cast<T3>(dst_ptr + ld_dst_oc));
     }
 };
 
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<1, 0, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
-        op({{c[0][4], c[0][5]}}, dst_ptr + 16);
-        op({{c[0][6], c[0][7]}}, dst_ptr + 24);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<1, 0, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
+        op({{c[0][4], c[0][5]}}, reinterpret_cast<T3>(dst_ptr + 16));
+        op({{c[0][6], c[0][7]}}, reinterpret_cast<T3>(dst_ptr + 24));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<1, 8, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
-        op({{c[0][4], c[0][5]}}, dst_ptr + 16);
-        op({{c[0][6], c[0][7]}}, dst_ptr + 24);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<1, 8, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
+        op({{c[0][4], c[0][5]}}, reinterpret_cast<T3>(dst_ptr + 16));
+        op({{c[0][6], c[0][7]}}, reinterpret_cast<T3>(dst_ptr + 24));
     }
 };
 
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<1, 7, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
-        op({{c[0][4], c[0][5]}}, dst_ptr + 16);
-        op(c[0][6], dst_ptr + 24);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<1, 7, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
+        op({{c[0][4], c[0][5]}}, reinterpret_cast<T3>(dst_ptr + 16));
+        op(c[0][6], reinterpret_cast<T3>(dst_ptr + 24));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<1, 6, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
-        op({{c[0][4], c[0][5]}}, dst_ptr + 16);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<1, 6, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
+        op({{c[0][4], c[0][5]}}, reinterpret_cast<T3>(dst_ptr + 16));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<1, 5, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
-        op(c[0][4], dst_ptr + 16);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<1, 5, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
+        op(c[0][4], reinterpret_cast<T3>(dst_ptr + 16));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<1, 4, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op({{c[0][2], c[0][3]}}, dst_ptr + 8);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<1, 4, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op({{c[0][2], c[0][3]}}, reinterpret_cast<T3>(dst_ptr + 8));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<1, 3, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
-        op(c[0][2], dst_ptr + 8);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<1, 3, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
+        op(c[0][2], reinterpret_cast<T3>(dst_ptr + 8));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<1, 2, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int) {
-        op({{c[0][0], c[0][1]}}, dst_ptr);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<1, 2, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int) {
+        op({{c[0][0], c[0][1]}}, reinterpret_cast<T3>(dst_ptr));
     }
 };
-template <typename Op, typename T>
-struct StoreOcxOw8Remain<1, 1, Op, T> {
-    static void impl(T& c, const Op& op, float32_t* dst_ptr, int) {
-        op(c[0][0], dst_ptr);
+template <typename Op, typename T, typename T2, typename T3>
+struct StoreOcxOw8Remain<1, 1, Op, T, T2, T3> {
+    static void impl(T& c, const Op& op, T2 dst_ptr, int) {
+        op(c[0][0], reinterpret_cast<T3>(dst_ptr));
     }
 };
 
-template <int c_dim, int ow_remain, typename Op, typename T>
-inline void store_ocx_ow8_remain_static(T& c, const Op& op, float32_t* dst_ptr,
+template <int c_dim, int ow_remain, typename Op, typename T, typename T2>
+inline void store_ocx_ow8_remain_static(T& c, const Op& op, T2 dst_ptr,
                                         int ld_dst_oc) {
-    StoreOcxOw8Remain<c_dim, ow_remain, Op, T>::impl(c, op, dst_ptr, ld_dst_oc);
+    StoreOcxOw8Remain<c_dim, ow_remain, Op, T, T2, T2>::impl(c, op, dst_ptr,
+                                                             ld_dst_oc);
+}
+template <int c_dim, int ow_remain, typename Op, typename T3, typename T,
+          typename T2>
+inline void store_ocx_ow8_remain_static_dt(T& c, const Op& op, T2 dst_ptr,
+                                           int ld_dst_oc) {
+    StoreOcxOw8Remain<c_dim, ow_remain, Op, T, T2, T3>::impl(c, op, dst_ptr,
+                                                             ld_dst_oc);
 }
 ////////////////////Store_OC8_OW8_Remain/////////////////////////
 
@@ -522,68 +537,84 @@ inline void init_oc8_ow8(int32x4_t c[2][8], const int32_t* bias_ptr,
     }
 }
 /////////////////////////init_ocx_ow8////////////////////
+
+inline float32x4_t neon_vdupq_n(float val) {
+    return vdupq_n_f32(val);
+}
+
+inline int32x4_t neon_vdupq_n(int val) {
+    return vdupq_n_s32(val);
+}
+inline float32x4_t neon_vld1q(const float* ptr) {
+    return vld1q_f32(ptr);
+}
+
+inline int32x4_t neon_vld1q(const int* ptr) {
+    return vld1q_s32(ptr);
+}
+
 template <int c_dim, BiasMode bias_mode, int ow_block, typename T, typename T2>
 struct InitOcxOw8 {
-    static void impl(T& c, T2 bias_ptr, int oc_step);
+    static void impl(T& c, const T2* bias_ptr, int oc_step);
 };
 template <typename T, typename T2>
 struct InitOcxOw8<2, BiasMode::NO_BIAS, 8, T, T2> {
-    static void impl(T& c, const float32_t*, int) {
-#define BAIS_INIT(step)          \
-    c[0][step] = vdupq_n_f32(0); \
-    c[1][step] = vdupq_n_f32(0);
+    static void impl(T& c, const T2*, int) {
+#define BAIS_INIT(step)                            \
+    c[0][step] = neon_vdupq_n(static_cast<T2>(0)); \
+    c[1][step] = neon_vdupq_n(static_cast<T2>(0));
         UNROLL_CALL_RAW(8, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 template <typename T, typename T2>
 struct InitOcxOw8<2, BiasMode::NO_BIAS, 4, T, T2> {
-    static void impl(T& c, const float32_t*, int) {
-#define BAIS_INIT(step)          \
-    c[0][step] = vdupq_n_f32(0); \
-    c[1][step] = vdupq_n_f32(0);
+    static void impl(T& c, const T2*, int) {
+#define BAIS_INIT(step)                            \
+    c[0][step] = neon_vdupq_n(static_cast<T2>(0)); \
+    c[1][step] = neon_vdupq_n(static_cast<T2>(0));
         UNROLL_CALL_RAW(4, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 template <typename T, typename T2>
 struct InitOcxOw8<2, BiasMode::BROADCAST_CHANNEL_BIAS, 8, T, T2> {
-    static void impl(T& c, const float32_t* bias_ptr, int oc_step) {
-#define BAIS_INIT(step)               \
-    c[0][step] = vld1q_f32(bias_ptr); \
-    c[1][step] = vld1q_f32(bias_ptr + oc_step);
+    static void impl(T& c, const T2* bias_ptr, int oc_step) {
+#define BAIS_INIT(step)                \
+    c[0][step] = neon_vld1q(bias_ptr); \
+    c[1][step] = neon_vld1q(bias_ptr + oc_step);
         UNROLL_CALL_RAW(8, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 template <typename T, typename T2>
 struct InitOcxOw8<2, BiasMode::BROADCAST_CHANNEL_BIAS, 4, T, T2> {
-    static void impl(T& c, const float32_t* bias_ptr, int oc_step) {
-#define BAIS_INIT(step)               \
-    c[0][step] = vld1q_f32(bias_ptr); \
-    c[1][step] = vld1q_f32(bias_ptr + oc_step);
+    static void impl(T& c, const T2* bias_ptr, int oc_step) {
+#define BAIS_INIT(step)                \
+    c[0][step] = neon_vld1q(bias_ptr); \
+    c[1][step] = neon_vld1q(bias_ptr + oc_step);
         UNROLL_CALL_RAW(4, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 template <typename T, typename T2>
 struct InitOcxOw8<2, BiasMode::BIAS, 8, T, T2> {
-    static void impl(T& c, const float32_t* bias_ptr, int oc_step) {
+    static void impl(T& c, const T2* bias_ptr, int oc_step) {
         constexpr int simd_len = 4;
-#define BAIS_INIT(step)                                 \
-    c[0][step] = vld1q_f32(bias_ptr + step * simd_len); \
-    c[1][step] = vld1q_f32(bias_ptr + oc_step + step * simd_len);
+#define BAIS_INIT(step)                                  \
+    c[0][step] = neon_vld1q(bias_ptr + step * simd_len); \
+    c[1][step] = neon_vld1q(bias_ptr + oc_step + step * simd_len);
         UNROLL_CALL_RAW(8, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 template <typename T, typename T2>
 struct InitOcxOw8<2, BiasMode::BIAS, 4, T, T2> {
-    static void impl(T& c, const float32_t* bias_ptr, int oc_step) {
+    static void impl(T& c, const T2* bias_ptr, int oc_step) {
         constexpr int simd_len = 4;
-#define BAIS_INIT(step)                                 \
-    c[0][step] = vld1q_f32(bias_ptr + step * simd_len); \
-    c[1][step] = vld1q_f32(bias_ptr + oc_step + step * simd_len);
+#define BAIS_INIT(step)                                  \
+    c[0][step] = neon_vld1q(bias_ptr + step * simd_len); \
+    c[1][step] = neon_vld1q(bias_ptr + oc_step + step * simd_len);
         UNROLL_CALL_RAW(4, BAIS_INIT);
 #undef BAIS_INIT
     }
@@ -591,57 +622,57 @@ struct InitOcxOw8<2, BiasMode::BIAS, 4, T, T2> {
 
 template <typename T, typename T2>
 struct InitOcxOw8<1, BiasMode::NO_BIAS, 8, T, T2> {
-    static void impl(T& c, const float32_t*, int) {
-#define BAIS_INIT(step) c[0][step] = vdupq_n_f32(0);
+    static void impl(T& c, const T2*, int) {
+#define BAIS_INIT(step) c[0][step] = neon_vdupq_n(static_cast<T2>(0));
         UNROLL_CALL_RAW(8, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 template <typename T, typename T2>
 struct InitOcxOw8<1, BiasMode::NO_BIAS, 4, T, T2> {
-    static void impl(T& c, const float32_t*, int) {
-#define BAIS_INIT(step) c[0][step] = vdupq_n_f32(0);
+    static void impl(T& c, const T2*, int) {
+#define BAIS_INIT(step) c[0][step] = neon_vdupq_n(static_cast<T2>(0));
         UNROLL_CALL_RAW(4, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 template <typename T, typename T2>
 struct InitOcxOw8<1, BiasMode::BROADCAST_CHANNEL_BIAS, 8, T, T2> {
-    static void impl(T& c, const float32_t* bias_ptr, int) {
-#define BAIS_INIT(step) c[0][step] = vld1q_f32(bias_ptr);
+    static void impl(T& c, const T2* bias_ptr, int) {
+#define BAIS_INIT(step) c[0][step] = neon_vld1q(bias_ptr);
         UNROLL_CALL_RAW(8, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 template <typename T, typename T2>
 struct InitOcxOw8<1, BiasMode::BROADCAST_CHANNEL_BIAS, 4, T, T2> {
-    static void impl(T& c, const float32_t* bias_ptr, int) {
-#define BAIS_INIT(step) c[0][step] = vld1q_f32(bias_ptr);
+    static void impl(T& c, const T2* bias_ptr, int) {
+#define BAIS_INIT(step) c[0][step] = neon_vld1q(bias_ptr);
         UNROLL_CALL_RAW(4, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 template <typename T, typename T2>
 struct InitOcxOw8<1, BiasMode::BIAS, 8, T, T2> {
-    static void impl(T& c, const float32_t* bias_ptr, int) {
+    static void impl(T& c, const T2* bias_ptr, int) {
         constexpr int simd_len = 4;
-#define BAIS_INIT(step) c[0][step] = vld1q_f32(bias_ptr + step * simd_len);
+#define BAIS_INIT(step) c[0][step] = neon_vld1q(bias_ptr + step * simd_len);
         UNROLL_CALL_RAW(8, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 template <typename T, typename T2>
 struct InitOcxOw8<1, BiasMode::BIAS, 4, T, T2> {
-    static void impl(T& c, const float32_t* bias_ptr, int) {
+    static void impl(T& c, const T2* bias_ptr, int) {
         constexpr int simd_len = 4;
-#define BAIS_INIT(step) c[0][step] = vld1q_f32(bias_ptr + step * simd_len);
+#define BAIS_INIT(step) c[0][step] = neon_vld1q(bias_ptr + step * simd_len);
         UNROLL_CALL_RAW(4, BAIS_INIT);
 #undef BAIS_INIT
     }
 };
 
 template <int c_dim, BiasMode bias_mode, int ow_block, typename T, typename T2>
-inline void init_ocx_ow8(T& c, T2 bias_ptr, int oc_step) {
+inline void init_ocx_ow8(T& c, const T2* bias_ptr, int oc_step) {
     InitOcxOw8<c_dim, bias_mode, ow_block, T, T2>::impl(c, bias_ptr, oc_step);
 }
 /////////////////////init_ocx_ow4/////////////////////

dnn/src/arm_common/conv_bias/opr_impl.cpp

@@ -55,6 +55,7 @@ class ConvBiasImpl::AlgoPack : NonCopyableObj {
     AlgoS8ChanWiseStride2NCHW44 s8_channel_wise_stride2_nchw44;
 
 #if __ARM_FEATURE_DOTPROD
+    AlgoDotS8DirectNCHWNCHW44 ds8_direct_stride2_nchw_nchw44;
     AlgoDotS8DirectStride1 ds8_direct_stride1_large_group{true};
     AlgoDotS8DirectStride1 ds8_direct_stride1_small_group{false};
     AlgoDotS8DirectStride2 ds8_direct_stride2_large_group{true};
@@ -93,6 +94,7 @@ class ConvBiasImpl::AlgoPack : NonCopyableObj {
 public:
     AlgoPack() {
 #if __ARM_FEATURE_DOTPROD
+        direct_algos.emplace_back(&ds8_direct_stride2_nchw_nchw44);
         direct_algos.emplace_back(&ds8_direct_stride1_large_group);
         direct_algos.emplace_back(&ds8_direct_stride1_small_group);
         direct_algos.emplace_back(&ds8_direct_stride2_large_group);

dnn/src/arm_common/conv_bias/opr_impl.h

@@ -62,6 +62,7 @@ private:
     class AlgoFP16WinogradF23_8x8;
 #endif
 #if __ARM_FEATURE_DOTPROD
+    class AlgoDotS8DirectNCHWNCHW44;
     class AlgoDotS8DirectStride1;
     class AlgoDotS8DirectStride2;
     class AlgoDotU8DirectStride1;

dnn/src/arm_common/neon_struct.h

@@ -60,6 +60,14 @@ struct Vfmaq_laneq_f32 {
         return vfmaq_laneq_f32(a, b, v, lane);
     }
 };
+#if __ARM_FEATURE_DOTPROD
+struct Vdotq_laneq_s32 {
+    template <const int lane>
+    static int32x4_t impl(int32x4_t a, int8x16_t b, int8x16_t v) {
+        return vdotq_laneq_s32(a, b, v, lane);
+    }
+};
+#endif
 
 }  // namespace
 }  // namespace megdnn

dnn/src/arm_common/simd_macro/marm_neon.h

@@ -481,37 +481,71 @@ UNROLL_CALL_RAW(4, cb);
 #define vdup_laneq_s16(vec, lane) Vdup_laneq_s16_armv7<lane>::impl(vec)
 namespace {
 template <int lane>
-struct Vfmap_laneq_f32_armv7 {
+struct Vfmaq_laneq_f32_armv7 {
     static float32x4_t impl(float32x4_t a, float32x4_t b, float32x4_t v);
 };
 
 template <>
-struct Vfmap_laneq_f32_armv7<0> {
+struct Vfmaq_laneq_f32_armv7<0> {
     static float32x4_t impl(float32x4_t a, float32x4_t b, float32x4_t v) {
         return vmlaq_lane_f32(a, b, vget_low_f32(v), 0);
     }
 };
 template <>
-struct Vfmap_laneq_f32_armv7<1> {
+struct Vfmaq_laneq_f32_armv7<1> {
     static float32x4_t impl(float32x4_t a, float32x4_t b, float32x4_t v) {
         return vmlaq_lane_f32(a, b, vget_low_f32(v), 1);
     }
 };
 template <>
-struct Vfmap_laneq_f32_armv7<2> {
+struct Vfmaq_laneq_f32_armv7<2> {
     static float32x4_t impl(float32x4_t a, float32x4_t b, float32x4_t v) {
         return vmlaq_lane_f32(a, b, vget_high_f32(v), 0);
     }
 };
 template <>
-struct Vfmap_laneq_f32_armv7<3> {
+struct Vfmaq_laneq_f32_armv7<3> {
     static float32x4_t impl(float32x4_t a, float32x4_t b, float32x4_t v) {
         return vmlaq_lane_f32(a, b, vget_high_f32(v), 1);
     }
 };
 }  // namespace
 #define vfmaq_laneq_f32(a, b, v, lane) \
-    Vfmap_laneq_f32_armv7<lane>::impl(a, b, v)
+    Vfmaq_laneq_f32_armv7<lane>::impl(a, b, v)
+
+#if __ARM_FEATURE_DOTPROD
+template <int lane>
+struct Vdotq_laneq_s32_armv7 {
+    static int32x4_t impl(int32x4_t a, int8x16_t b, int8x16_t v);
+};
+template <>
+struct Vdotq_laneq_s32_armv7<0> {
+    static int32x4_t impl(int32x4_t a, int8x16_t b, int8x16_t v) {
+        return vdotq_lane_s32(a, b, vget_low_s32(v), 0);
+    }
+};
+template <>
+struct Vdotq_laneq_s32_armv7<1> {
+    static int32x4_t impl(int32x4_t a, int8x16_t b, int8x16_t v) {
+        return vdotq_lane_s32(a, b, vget_low_s32(v), 1);
+    }
+};
+template <>
+struct Vdotq_laneq_s32_armv7<2> {
+    static int32x4_t impl(int32x4_t a, int8x16_t b, int8x16_t v) {
+        return vdotq_lane_s32(a, b, vget_high_s32(v), 0);
+    }
+};
+template <>
+struct Vdotq_laneq_s32_armv7<3> {
+    static int32x4_t impl(int32x4_t a, int8x16_t b, int8x16_t v) {
+        return vdotq_lane_s32(a, b, vget_high_f32(v), 1);
+    }
+};
+#define vdotq_laneq_s32(a, b, v, lane) \
+    Vdotq_laneq_s32_armv7<lane>::impl(a, b, v)
+
+#endif
 
 #endif
 

dnn/test/arm_common/conv_bias.cpp

@@ -109,14 +109,12 @@ static void benchmark_convbias(Handle* handle, bool is_fp32 = false) {
             .set_dtype(4, dtype::QuantizedS8(60.25))
             .set_display(false);
     benchmarker_int.set_before_exec_callback(
-            conv_bias::ConvBiasAlgoChecker<ConvBias>(
-                    "IM2COLMATMUL:AARCH64_INT8X8X32_K4X4X16:384"));
+            conv_bias::ConvBiasAlgoChecker<ConvBias>("IM2COLMATMUL:.+"));
 
     Benchmarker<ConvBias> benchmarker_float(handle);
     benchmarker_float.set_display(false).set_times(RUNS);
     benchmarker_float.set_before_exec_callback(
-            conv_bias::ConvBiasAlgoChecker<ConvBias>(
-                    "IM2COLMATMUL:AARCH64_F32K8X12X1:192"));
+            conv_bias::ConvBiasAlgoChecker<ConvBias>("IM2COLMATMUL:.+"));
 
     Benchmarker<ConvBias> benchmarker_nchw44(handle);
     if (is_fp32) {
@@ -213,6 +211,15 @@ static void benchmark_convbias(Handle* handle, bool is_fp32 = false) {
         run(1, 256, 256, 14, 14, 3, 1, false);
         run(1, 512, 512, 7, 7, 3, 1, false);
     } else {
+        run(1, 1, 4, 112, 112, 2, 2, true);
+        run(1, 3, 32, 224, 224, 3, 2, true);
+        run(1, 3, 32, 224, 224, 5, 2, true);
+        run(1, 3, 64, 224, 224, 7, 2, true);
+        run(1, 1, 4, 112, 112, 2, 1, true);
+        run(1, 3, 32, 224, 224, 3, 1, true);
+        run(1, 3, 32, 224, 224, 5, 1, true);
+        run(1, 3, 64, 224, 224, 7, 1, true);
+
         for (size_t stride : {1, 2}) {
             printf("stride %zu\n", stride);
             for (size_t filter_size : {2, 3, 5, 7}) {
@@ -228,9 +235,11 @@ static void benchmark_convbias(Handle* handle, bool is_fp32 = false) {
 }
 TEST_F(ARM_COMMON, BENCHMARK_CONVBIAS_NCHW44) {
     benchmark_convbias(handle(), true);
+    benchmark_convbias(handle(), false);
 }
 TEST_F(ARM_COMMON_MULTI_THREADS, BENCHMARK_CONVBIAS_NCHW44) {
     benchmark_convbias(handle(), true);
+    benchmark_convbias(handle(), false);
 }
 
 #endif

dnn/test/arm_common/conv_bias_multi_thread.cpp

@@ -557,6 +557,16 @@ TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_QUINT8_STRIDE2_SMALL_GROUP) {
 
 /****************************dot qint8 direct*************************/
 #if __ARM_FEATURE_DOTPROD
+TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_DOT_NCHW_NCHW44) {
+    checker_conv_bias_qint8x8x8(
+            get_nchw44_conv_bias_args({2, 3, 5, 7}, 2, false, false, false,
+                                      true),
+            handle(), "ARMDOTS8_NCHW_NCHW44");
+    checker_conv_bias_qint8x8x8(
+            get_nchw44_conv_bias_args({2, 3, 5, 7}, 1, false, false, false,
+                                      true),
+            handle(), "ARMDOTS8_NCHW_NCHW44");
+}
 TEST_F(ARM_COMMON_MULTI_THREADS,
        CONV_BIAS_INT8_STRIDE1_WITHDOTPROD_LARGE_GROUP) {
     checker_conv_bias_qint8x8x8(get_int8_quint8_conv_bias_args(