Add AICORE Flops profiling

mindspore/profiler/parser/flops_parser.py

@@ -0,0 +1,237 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# 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.
+# ============================================================================
+"""Memory Usage Parser."""
+import os
+import struct
+import json
+import stat
+
+from mindspore import log as logger
+from mindspore.profiler.common.exceptions.exceptions import ProfilerIOException, \
+    ProfilerFileNotFoundException, ProfilerRawFileException
+
+
+class FlopsParser:
+    """
+    The parser for parsing aicore file.
+
+    Args:
+        input_dir (str): directory(JOBXXX) where the original profiling data are located.
+        output_dir (str): directory(profiler-{timestamp}) where the parsed profiling files are located.
+        op_task_dict (dict): the mapping relation of task_id and op_full_name.
+        device_id (str): the device ID.
+    """
+    HEX = 16
+    PMU_COUNT = 8
+    AICORE_LOG_SIZE = 128  # the size of each struct is 128 Byte.
+    RUNTIME_COMMON = "BBHHHII10Q8I"
+
+    # If the task id is less than the task id threshold,
+    # the combination of task id and Stream id represents one operator,
+    # else the task id represents one operator.
+    _task_id_threshold = 25000
+
+    def __init__(self, input_dir, output_dir, op_task_dict, device_id):
+        self._input_dir = input_dir
+        self._output_dir = output_dir
+        self._op_task_dict = op_task_dict
+        self._device_id = device_id
+        self._flops_filename = f'flops_{self._device_id}.txt'
+        self._flops_summary_filename = f'flops_summary_{self._device_id}.json'
+        self._aicore_filename = f'aicore.data.{self._device_id}.slice_0'
+        self._optime_filename = f'output_op_compute_time_{self._device_id}.txt'
+        self._info_json = f'info.json.{device_id}'
+        self._flops_summary = {
+            'FLOPs': 0,
+            'FLOPS': 0,
+            'FLOPS_Utilization': 0
+        }
+
+    def execute(self):
+        """Get the flops of aicore operators and write to file."""
+        peak_flops = self._get_peak_flops()
+        read_count, all_log_struct = self._load_aicore_data()
+        op_avg_time_dict = self._get_op_avg_time_dict()
+        op_flops_list = []
+        op_name_set = set()
+
+        for idx in range(read_count):
+            log_struct = all_log_struct[idx * self.AICORE_LOG_SIZE:
+                                        (idx + 1) * self.AICORE_LOG_SIZE]
+            result = [hex(i) for i in struct.unpack(self.RUNTIME_COMMON, log_struct)]
+            op_name = self._get_op_name(result)
+            if op_name in op_name_set:
+                continue
+            # Convert the unit of task_fops to MFLOPs(1e6).
+            task_fops = self._compute_task_flops(result) * 1e-6
+            op_name = self._get_op_name(result)
+            op_avg_time = op_avg_time_dict[op_name]
+            # Time unit of op_avg_time is ms.
+            # The unit of gflop_per_second is GFLOPS(1e9).
+            gflop_per_second = task_fops / float(op_avg_time)
+            flops_utilization = (gflop_per_second * 1e9 / peak_flops) * 100
+            self._flops_summary['FLOPs'] += task_fops
+            self._flops_summary['FLOPS'] += gflop_per_second
+            self._flops_summary['FLOPS_Utilization'] += flops_utilization
+            op_flops = [op_name, str(task_fops), str(gflop_per_second), str(flops_utilization)]
+            op_flops_list.append(op_flops)
+            op_name_set.add(op_name)
+
+        self._flops_summary['FLOPS'] /= len(op_name_set)
+        self._flops_summary['FLOPS_Utilization'] /= len(op_name_set)
+
+        self._write_file(op_flops_list)
+
+    def _load_aicore_data(self):
+        """Load the original binary aicore data."""
+        aicore_file_path = os.path.join(
+            self._input_dir,
+            "data",
+            self._aicore_filename
+        )
+
+        if not os.path.exists(aicore_file_path):
+            logger.error(f'The file {aicore_file_path} does not exist.')
+            raise ProfilerFileNotFoundException('aicore.data')
+
+        file_size = os.path.getsize(aicore_file_path)
+        read_count = file_size // self.AICORE_LOG_SIZE
+
+        if not read_count:
+            logger.error(f'the file {aicore_file_path} '
+                         f'does not have enough content to be parsed.')
+            raise ProfilerRawFileException(
+                'aicore.data file does not have enough content to be parsed'
+            )
+
+        try:
+            with open(aicore_file_path, "rb") as aicore_file:
+                all_log_struct = aicore_file.read(self.AICORE_LOG_SIZE * read_count)
+        except (IOError, OSError) as err:
+            logger.error(f'Error occurred when read {aicore_file_path} file: {err}')
+            raise ProfilerIOException()
+
+        return read_count, all_log_struct
+
+    def _get_peak_flops(self):
+        """Get the peak FLOPS of current ascend device."""
+        info_json_file_path = os.path.join(
+            self._input_dir,
+            self._info_json
+        )
+
+        if not os.path.exists(info_json_file_path):
+            logger.error(f'The file {info_json_file_path} does not exist.')
+            raise ProfilerFileNotFoundException(info_json_file_path)
+
+        try:
+            with open(info_json_file_path, 'r', encoding='utf-8') as info_file:
+                device_info = json.load(info_file)['DeviceInfo'][0]
+                device_frequency = float(device_info["aic_frequency"])
+                ai_core_num = float(device_info["ai_core_num"])
+                # peak_flops formula (provided by Hisi): device_frequency * num_of_aicore * 4096 * 2.
+                peak_flops = device_frequency * 1e6 * ai_core_num * 4096 * 2
+        except (IOError, OSError, json.JSONDecodeError) as err:
+            logger.error(f'Error occurred when read {info_json_file_path} file: {err}')
+            raise ProfilerIOException()
+
+        return peak_flops
+
+    def _compute_task_flops(self, log_result):
+        """Compute the FLOPs of each task."""
+        pmu_cnt = list(
+            int(i.replace('0x', ''), self.HEX)
+            for i in log_result[9:17]
+        )
+        cube_fp16_exec = pmu_cnt[0]
+        cube_int8_exec = pmu_cnt[1]
+        vec_fp32 = pmu_cnt[2]
+        vec_fp16_128lane_exec = pmu_cnt[3]
+        vec_fp16_64lane_exec = pmu_cnt[4]
+        vec_int32_exec = pmu_cnt[5]
+        vec_misc_exec = pmu_cnt[6]
+
+        # These formula is provided by HISI profiling.
+        # a cube_fp16 instruction has (16**3)*2 float point operation.
+        # a cube_fp16 instruction has 16*16*32*2 float point operation.
+        cube_fops = cube_fp16_exec*(16**3)*2 + cube_int8_exec*16*16*32*2
+        vec_fops = vec_fp32*32 + vec_fp16_128lane_exec*128 + \
+                   vec_fp16_64lane_exec*64 + vec_int32_exec*64 + vec_misc_exec*32
+        task_fops = cube_fops + vec_fops
+
+        return task_fops
+
+    def _get_op_name(self, log_result):
+        """Get the operator name for current task_id."""
+        task_id = int(log_result[4].replace('0x', ''), self.HEX)
+        stream_id = int(log_result[17].replace('0x', ''), self.HEX)
+        if task_id < self._task_id_threshold:
+            task_id = '_'.join([str(stream_id), str(task_id)])
+        op_name = self._op_task_dict[str(task_id)]
+
+        return op_name
+
+    def _get_op_avg_time_dict(self):
+        """get the op average execution time."""
+        op_avg_time_dict = {}
+        optime_file_path = os.path.join(self._output_dir, self._optime_filename)
+
+        if not os.path.exists(optime_file_path):
+            logger.error(f'The {optime_file_path} file does not exist.')
+            raise ProfilerFileNotFoundException(optime_file_path)
+
+        try:
+            with open(optime_file_path, 'r') as f:
+                lines = f.readlines()
+                op_avg_time_lines = lines[3:]  # the first three lines are table header.
+                for line in op_avg_time_lines:
+                    op_name, avg_time = line.split()[:2]
+                    op_avg_time_dict[op_name] = avg_time
+        except (IOError, OSError) as err:
+            logger.error(f'Error occurred when read {optime_file_path} file: {err}')
+            raise ProfilerIOException()
+
+        return op_avg_time_dict
+
+    def _write_file(self, op_flops_list):
+        """Write the operator's flops related information into file."""
+        output_file_path = os.path.join(
+            self._output_dir,
+            self._flops_filename
+        )
+        output_summary_file_path = os.path.join(
+            self._output_dir,
+            self._flops_summary_filename
+        )
+
+        try:
+            with open(output_file_path, 'w') as f:
+                header = "op_full_name, MFLOPs(10^6), GFLOPS(10^9), FLOPS utilization(%) \n"
+                f.writelines(header)
+                for op_flops in op_flops_list:
+                    line = ", ".join(op_flops)
+                    f.writelines(line + '\n')
+            os.chmod(output_file_path, stat.S_IREAD | stat.S_IWRITE)
+        except (IOError, OSError) as err:
+            logger.error(f'Error occurred when writing {output_file_path} file: {err}')
+            raise ProfilerIOException()
+
+        try:
+            with open(output_summary_file_path, 'w') as json_file:
+                json.dump(self._flops_summary, json_file)
+            os.chmod(output_summary_file_path, stat.S_IREAD | stat.S_IWRITE)
+        except (IOError, OSError) as err:
+            logger.error(f'Error occurred when write {output_summary_file_path} file: {err}')
+            raise ProfilerIOException()

mindspore/profiler/parser/integrator.py

@@ -45,7 +45,7 @@ class Integrator:
                            'percent']
     _header_aicore_detail = ['full_op_name', 'execution_time']
     _header_aicpu = ['serial_number', 'op_type', 'total_time', 'dispatch_time',
-                     'run_start', 'run_end']
+                     'execution_time', 'run_start', 'run_end']
 
     _file_name_aicore_type_time = 'aicore_intermediate_{}_type.csv'
     _file_name_aicore_detail_info = 'aicore_intermediate_{}_detail.csv'

mindspore/profiler/profiling.py

@@ -37,6 +37,7 @@ from mindspore.profiler.parser.integrator import GpuTimelineGenerator, AscendTim
 from mindspore.profiler.parser.memory_usage_parser import MemoryUsageParser
 from mindspore.profiler.parser.minddata_parser import MinddataParser
 from mindspore.profiler.parser.minddata_analyzer import MinddataProfilingAnalyzer
+from mindspore.profiler.parser.flops_parser import FlopsParser
 from mindspore.profiler.parser.minddata_pipeline_parser import \
     MinddataPipelineParser
 from mindspore.profiler.parser.optime_parser import OPComputeTimeParser
@@ -239,6 +240,10 @@ class Profiler:
         aicpu_data_parser = DataPreProcessParser(source_path, output_data_preprocess_aicpu)
         aicpu_data_parser.execute()
 
+        # get op FLOPs from aicore.data.x.slice.0 file, and compute FLOPS, write output_op_flops_x.txt
+        flops_parser = FlopsParser(source_path, self._output_path, op_task_dict, self._dev_id)
+        flops_parser.execute()
+
         # Parsing minddata AICPU profiling
         MinddataParser.execute(source_path, self._output_path, self._dev_id)