-
guoshzhao authored
**Description** Generate the summarized output files from all nodes. For each metric, do the reduce operation according to the `reduce_op` **Major Revision** - Generate the summarized json file per node: For microbenchmark, the format is `{benchmark_name}/[{run_count}/]{metric_name}[:rank]` For modelbenchmark, the format is `{benchmark_name}/{sub_benchmark_name}/[{run_count}/]{metric_name}` `[]` means optional. ``` { "kernel-launch/overhead_event:0": 0.00583, "kernel-launch/overhead_event:1": 0.00545, "kernel-launch/overhead_event:2": 0.00581, "kernel-launch/overhead_event:3": 0.00572, "kernel-launch/overhead_event:4": 0.00559, "kernel-launch/overhead_event:5": 0.00591, "kernel-launch/overhead_event:6": 0.00562, "kernel-launch/overhead_event:7": 0.00586, "resnet_models/pytorch-resnet50/steptime-train-float32": 544.0827468410134, "resnet_models/pytorch-resnet50/throughput-train-float32": 353.7607016465773, "resnet_models/pytorch-resnet50/steptime-train-float16": 425.40482617914677, "resnet_models/pytorch-resnet50/throughput-train-float16": 454.0142363793973, "pytorch-sharding-matmul/0/allreduce": 10.561786651611328, "pytorch-sharding-matmul/1/allreduce": 10.561786651611328, "pytorch-sharding-matmul/0/allgather": 10.088025093078613, "pytorch-sharding-matmul/1/allgather": 10.088025093078613 } ``` - Generate the summarized jsonl file for all nodes, each line is the result from one node in json format.7595d794