Release - SuperBench v0.7.0 (#468)
**Description** Cherry-pick bug fixes from v0.7.0 to main. **Major Revisions** * Benchmarks - Fix missing include in FP8 benchmark (#460) * Fix bug in TE BERT model (#461) * Doc - Update benchmark doc (#465) * Bug: Fix bug for incorrect datatype judgement in cublas-function source code (#464) * Support `sb deploy` without pulling image (#466) * Docs - Upgrade version and release note (#467) Co-authored-by: Russell J. Hewett <russell.j.hewett@gmail.com> Co-authored-by: Yuting Jiang <yutingjiang@microsoft.com>
This commit is contained in:
Yifan Xiong
GitHub
Родитель
f380bc5eff
Коммит
b07fda155e
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@ -15,7 +15,7 @@
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__SuperBench__ is a validation and profiling tool for AI infrastructure.
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📢 [v0.6.0](https://github.com/microsoft/superbenchmark/releases/tag/v0.6.0) has been released!
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📢 [v0.7.0](https://github.com/microsoft/superbenchmark/releases/tag/v0.7.0) has been released!
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## _Check [aka.ms/superbench](https://aka.ms/superbench) for more details._
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@ -97,6 +97,7 @@ sb deploy [--docker-image]
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[--host-list]
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[--host-password]
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[--host-username]
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[--no-image-pull]
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[--output-dir]
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[--private-key]
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```
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@ -112,6 +113,7 @@ sb deploy [--docker-image]
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| `--host-list` `-l` | `None` | Comma separated host list. |
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| `--host-password` | `None` | Host password or key passphase if needed. |
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| `--host-username` | `None` | Host username if needed. |
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| `--no-image-pull` | `False` | Skip pull and use local Docker image. |
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| `--output-dir` | `None` | Path to output directory, outputs/{datetime} will be used if not specified. |
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| `--private-key` | `None` | Path to private key if needed. |
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@ -61,7 +61,7 @@ You can clone the source from GitHub and build it.
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:::note Note
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You should checkout corresponding tag to use release version, for example,
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`git clone -b v0.6.0 https://github.com/microsoft/superbenchmark`
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`git clone -b v0.7.0 https://github.com/microsoft/superbenchmark`
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:::
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```bash
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@ -27,7 +27,7 @@ sb deploy -f remote.ini --host-password [password]
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:::note Note
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You should deploy corresponding Docker image to use release version, for example,
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`sb deploy -f local.ini -i superbench/superbench:v0.6.0-cuda11.1.1`
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`sb deploy -f local.ini -i superbench/superbench:v0.7.0-cuda11.1.1`
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You should note that version of git repo only determines version of sb CLI, and not the sb container. You should define the container version even if you specified a release version for the git clone.
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@ -70,7 +70,7 @@ superbench:
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<TabItem value='example'>
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```yaml
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version: v0.6
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version: v0.7
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superbench:
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enable: benchmark_1
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monitor:
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@ -471,4 +471,3 @@ Available variables in formatted string includes:
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+ `ibnetdiscover(str)`: the path of ibnetdiscover output `ibnetdiscover_file.txt`, required in `topo-aware` pattern.
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+ `min_dist(int)`: minimum distance of VM pair, required in `topo-aware` pattern.
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+ `max_dist(int)`: maximum distance of VM pair, required in `topo-aware` pattern.
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@ -66,9 +66,9 @@ Measure the GEMM performance of [`cublasLtMatmul`](https://docs.nvidia.com/cuda/
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#### Metrics
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| Name | Unit | Description |
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|---------------------------------|----------------|---------------------------------|
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| cublaslt-gemm/dtype_m_n_k_flops | FLOPS (TFLOPS) | TFLOPS of measured GEMM kernel. |
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| Name | Unit | Description |
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|------------------------------------------------|----------------|---------------------------------|
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| cublaslt-gemm/${dtype}\_${m}\_${n}\_${k}_flops | FLOPS (TFLOPS) | TFLOPS of measured GEMM kernel. |
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### `cublas-function`
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@ -86,9 +86,11 @@ The supported functions for cuBLAS are as follows:
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#### Metrics
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| Name | Unit | Description |
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|----------------------------------------------------------|-----------|-------------------------------------------------------------------|
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| cublas-function/name_${function_name}_${parameters}_time | time (us) | The mean time to execute the cublas function with the parameters. |
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| Name | Unit | Description |
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|-------------------------------------------------------------------|-----------|----------------------------------------------------------------------------------------------------------------------------------------------|
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| cublas-function/name\_${function_name}\_${parameters}_time | time (us) | The mean time to execute the cublas function with the parameters. |
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| cublas-function/name\_${function_name}\_${parameters}_correctness | | Whether the calculation results of executing the cublas function with the parameters pass the correctness check if enable correctness check. |
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| cublas-function/name\_${function_name}\_${parameters}_error | | The error ratio of the calculation results of executing the cublas function with the parameters if enable correctness check. |
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### `cudnn-function`
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@ -103,9 +105,9 @@ The supported functions for cuDNN are as follows:
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#### Metrics
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| Name | Unit | Description |
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|---------------------------------------------------------|-----------|------------------------------------------------------------------|
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| cudnn-function/name_${function_name}_${parameters}_time | time (us) | The mean time to execute the cudnn function with the parameters. |
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| Name | Unit | Description |
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|-----------------------------------------------------------|-----------|------------------------------------------------------------------|
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| cudnn-function/name\_${function_name}\_${parameters}_time | time (us) | The mean time to execute the cudnn function with the parameters. |
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### `tensorrt-inference`
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@ -264,9 +266,10 @@ Support the following traffic patterns:
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| rccl-bw/${operation}_${msg_size}_algbw | bandwidth (GB/s) | RCCL operation algorithm bandwidth with given message size. |
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| rccl-bw/${operation}_${msg_size}_busbw | bandwidth (GB/s) | RCCL operation bus bandwidth with given message size. |
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If traffic pattern is specified, the metrics pattern will change to `nccl-bw/${operation}_${serial_index)_${parallel_index):${msg_size}_time`
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If mpi mode is enable and traffic pattern is specified, the metrics pattern will change to `nccl-bw/${operation}_${serial_index)_${parallel_index):${msg_size}_time`
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- `serial_index` represents the serial index of the host group in serial.
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- `parallel_index` represents the parallel index of the host list in parallel.
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### `tcp-connectivity`
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#### Introduction
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@ -30,19 +30,15 @@ including the following categories:
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For inference, supported percentiles include
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50<sup>th</sup>, 90<sup>th</sup>, 95<sup>th</sup>, 99<sup>th</sup>, and 99.9<sup>th</sup>.
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**New: Support fp8_hybrid and fp8_e4m3 precision for BERT models.**
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#### Metrics
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| Name | Unit | Description |
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|---------------------------------------------------------------------------------|------------------------|---------------------------------------------------------------------------|
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| model-benchmarks/pytorch-${model_name}/fp32_train_step_time | time (ms) | The average training step time with single precision. |
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| model-benchmarks/pytorch-${model_name}/fp32_train_throughput | throughput (samples/s) | The average training throughput with single precision. |
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| model-benchmarks/pytorch-${model_name}/fp32_inference_step_time | time (ms) | The average inference step time with single precision. |
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| model-benchmarks/pytorch-${model_name}/fp32_inference_throughput | throughput (samples/s) | The average inference throughput with single precision. |
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| model-benchmarks/pytorch-${model_name}/fp32_inference_step_time\_${percentile} | time (ms) | The n<sup>th</sup> percentile inference step time with single precision. |
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| model-benchmarks/pytorch-${model_name}/fp32_inference_throughput\_${percentile} | throughput (samples/s) | The n<sup>th</sup> percentile inference throughput with single precision. |
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| model-benchmarks/pytorch-${model_name}/fp16_train_step_time | time (ms) | The average training step time with half precision. |
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| model-benchmarks/pytorch-${model_name}/fp16_train_throughput | throughput (samples/s) | The average training throughput with half precision. |
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| model-benchmarks/pytorch-${model_name}/fp16_inference_step_time | time (ms) | The average inference step time with half precision. |
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| model-benchmarks/pytorch-${model_name}/fp16_inference_throughput | throughput (samples/s) | The average inference throughput with half precision. |
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| model-benchmarks/pytorch-${model_name}/fp16_inference_step_time\_${percentile} | time (ms) | The n<sup>th</sup> percentile inference step time with half precision. |
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| model-benchmarks/pytorch-${model_name}/fp16_inference_throughput\_${percentile} | throughput (samples/s) | The n<sup>th</sup> percentile inference throughput with half precision. |
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| Name | Unit | Description |
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|-----------------------------------------------------------------------------------------|------------------------|------------------------------------------------------------------------------|
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| model-benchmarks/pytorch-${model_name}/${precision}_train_step_time | time (ms) | The average training step time with fp32/fp16 precision. |
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| model-benchmarks/pytorch-${model_name}/${precision}_train_throughput | throughput (samples/s) | The average training throughput with fp32/fp16 precision. |
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| model-benchmarks/pytorch-${model_name}/${precision}_inference_step_time | time (ms) | The average inference step time with fp32/fp16 precision. |
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| model-benchmarks/pytorch-${model_name}/${precision}_inference_throughput | throughput (samples/s) | The average inference throughput with fp32/fp16 precision. |
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| model-benchmarks/pytorch-${model_name}/${precision}_inference_step_time\_${percentile} | time (ms) | The n<sup>th</sup> percentile inference step time with fp32/fp16 precision. |
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| model-benchmarks/pytorch-${model_name}/${precision}_inference_throughput\_${percentile} | throughput (samples/s) | The n<sup>th</sup> percentile inference throughput with fp32/fp16 precision. |
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@ -29,6 +29,8 @@ available tags are listed below for all stable versions.
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| Tag | Description |
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|-------------------|------------------------------------|
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| v0.7.0-cuda11.8 | SuperBench v0.7.0 with CUDA 11.8 |
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| v0.7.0-cuda11.1.1 | SuperBench v0.7.0 with CUDA 11.1.1 |
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| v0.6.0-cuda11.1.1 | SuperBench v0.6.0 with CUDA 11.1.1 |
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| v0.5.0-cuda11.1.1 | SuperBench v0.5.0 with CUDA 11.1.1 |
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| v0.4.0-cuda11.1.1 | SuperBench v0.4.0 with CUDA 11.1.1 |
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@ -41,6 +43,10 @@ available tags are listed below for all stable versions.
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| Tag | Description |
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|-------------------------------|--------------------------------------------------|
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| v0.7.0-rocm5.1.3 | SuperBench v0.7.0 with ROCm 5.1.3 |
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| v0.7.0-rocm5.1.1 | SuperBench v0.7.0 with ROCm 5.1.1 |
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| v0.7.0-rocm5.0.1 | SuperBench v0.7.0 with ROCm 5.0.1 |
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| v0.7.0-rocm5.0 | SuperBench v0.7.0 with ROCm 5.0 |
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| v0.6.0-rocm5.1.3 | SuperBench v0.6.0 with ROCm 5.1.3 |
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| v0.6.0-rocm5.1.1 | SuperBench v0.6.0 with ROCm 5.1.1 |
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| v0.6.0-rocm5.0.1 | SuperBench v0.6.0 with ROCm 5.0.1 |
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@ -65,7 +65,7 @@ superbench:
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example:
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```yaml
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# SuperBench rules
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version: v0.6
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version: v0.7
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superbench:
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rules:
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failure-rule:
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@ -58,7 +58,7 @@ superbench:
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```yaml title="Example"
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# SuperBench rules
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version: v0.6
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version: v0.7
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superbench:
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rules:
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kernel_launch:
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@ -6,5 +6,5 @@
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Provide hardware and software benchmarks for AI systems.
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"""
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__version__ = '0.6.0'
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__version__ = '0.7.0'
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__author__ = 'Microsoft'
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@ -4,6 +4,7 @@
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#pragma once
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#include <memory>
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#include <stdexcept>
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#include <stdio.h>
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#include <vector>
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@ -61,15 +61,18 @@ class TeBertBenchmarkModel(torch.nn.Module):
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self._embedding = torch.nn.Embedding(config.vocab_size, config.hidden_size)
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# Build BERT using nn.TransformerEncoderLayer or te.TransformerLayer
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# input shape: (seq_len, batch_size, hidden_size)
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encoder_layer = te.TransformerLayer(
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config.hidden_size,
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config.intermediate_size,
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config.num_attention_heads,
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apply_residual_connection_post_layernorm=True,
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output_layernorm=True,
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layer_type='encoder',
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self._encoder_layers = torch.nn.ModuleList(
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[
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te.TransformerLayer(
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config.hidden_size,
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config.intermediate_size,
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config.num_attention_heads,
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apply_residual_connection_post_layernorm=True,
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output_layernorm=True,
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layer_type='encoder',
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) for _ in range(config.num_hidden_layers)
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]
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)
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self._encoder_layers = torch.nn.ModuleList([encoder_layer for _ in range(config.num_hidden_layers)])
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# BertPooler used in huggingface transformers
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# https://github.com/huggingface/transformers/blob/accad48e/src/transformers/models/bert/modeling_bert.py#L893
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self._pooler = torch.nn.Sequential(
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@ -113,7 +116,6 @@ class PytorchBERT(PytorchBase):
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Precision.FLOAT16,
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Precision.FP8_HYBRID,
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Precision.FP8_E4M3,
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Precision.FP8_E5M2,
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]
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self._optimizer_type = Optimizer.ADAMW
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self._loss_fn = torch.nn.CrossEntropyLoss()
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@ -44,6 +44,7 @@ class SuperBenchCommandsLoader(CLICommandsLoader):
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ac.argument('docker_username', type=str, help='Docker registry username if authentication is needed.')
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ac.argument('docker_password', type=str, help='Docker registry password if authentication is needed.')
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ac.argument('no_docker', action='store_true', help='Run on host directly without Docker.')
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ac.argument('no_image_pull', action='store_true', help='Skip pull and use local Docker image.')
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ac.argument(
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'host_file', options_list=('--host-file', '-f'), type=str, help='Path to Ansible inventory host file.'
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)
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@ -99,6 +99,7 @@ def process_runner_arguments(
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docker_username=None,
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docker_password=None,
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no_docker=False,
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no_image_pull=False,
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host_file=None,
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host_list=None,
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host_username=None,
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@ -115,6 +116,7 @@ def process_runner_arguments(
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docker_username (str, optional): Docker registry username if authentication is needed. Defaults to None.
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docker_password (str, optional): Docker registry password if authentication is needed. Defaults to None.
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no_docker (bool, optional): Run on host directly without Docker. Defaults to False.
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no_image_pull (bool, optional): Skip pull and use local Docker image. Defaults to False.
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host_file (str, optional): Path to Ansible inventory host file. Defaults to None.
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host_list (str, optional): Comma separated host list. Defaults to None.
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host_username (str, optional): Host username if needed. Defaults to None.
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@ -149,6 +151,7 @@ def process_runner_arguments(
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'password': docker_password,
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'registry': split_docker_domain(docker_image)[0],
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'skip': no_docker,
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'pull': not no_image_pull,
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}
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)
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# Ansible config
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@ -209,6 +212,7 @@ def deploy_command_handler(
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docker_image='superbench/superbench',
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docker_username=None,
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docker_password=None,
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no_image_pull=False,
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host_file=None,
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host_list=None,
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host_username=None,
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@ -228,6 +232,7 @@ def deploy_command_handler(
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docker_image (str, optional): Docker image URI. Defaults to superbench/superbench:latest.
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docker_username (str, optional): Docker registry username if authentication is needed. Defaults to None.
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docker_password (str, optional): Docker registry password if authentication is needed. Defaults to None.
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no_image_pull (bool, optional): Skip pull and use local Docker image. Defaults to False.
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host_file (str, optional): Path to Ansible inventory host file. Defaults to None.
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host_list (str, optional): Comma separated host list. Defaults to None.
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host_username (str, optional): Host username if needed. Defaults to None.
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@ -243,6 +248,7 @@ def deploy_command_handler(
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docker_username=docker_username,
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docker_password=docker_password,
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no_docker=False,
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no_image_pull=no_image_pull,
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host_file=host_file,
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host_list=host_list,
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host_username=host_username,
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@ -298,6 +304,7 @@ def run_command_handler(
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docker_username=docker_username,
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docker_password=docker_password,
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no_docker=no_docker,
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no_image_pull=False,
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host_file=host_file,
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host_list=host_list,
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host_username=host_username,
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@ -3,7 +3,7 @@
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# Server:
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||||
# - Product: HPE Apollo 6500
|
||||
|
||||
version: v0.6
|
||||
version: v0.7
|
||||
superbench:
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||||
enable: null
|
||||
var:
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||||
|
|
|
|||
|
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@ -4,7 +4,7 @@
|
|||
# - Product: G482-Z53
|
||||
# - Link: https://www.gigabyte.cn/FileUpload/Global/MicroSite/553/G482-Z53.html
|
||||
|
||||
version: v0.6
|
||||
version: v0.7
|
||||
superbench:
|
||||
enable: null
|
||||
var:
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
version: v0.6
|
||||
version: v0.7
|
||||
superbench:
|
||||
enable: null
|
||||
monitor:
|
||||
|
|
|
|||
|
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@ -1,4 +1,4 @@
|
|||
version: v0.6
|
||||
version: v0.7
|
||||
superbench:
|
||||
enable: null
|
||||
monitor:
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
version: v0.6
|
||||
version: v0.7
|
||||
superbench:
|
||||
enable: null
|
||||
monitor:
|
||||
|
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|||
|
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@ -3,7 +3,7 @@
|
|||
# Azure NDm A100 v4
|
||||
# reference: https://docs.microsoft.com/en-us/azure/virtual-machines/ndm-a100-v4-series
|
||||
|
||||
version: v0.6
|
||||
version: v0.7
|
||||
superbench:
|
||||
enable: null
|
||||
monitor:
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
# SuperBench Config
|
||||
version: v0.6
|
||||
version: v0.7
|
||||
superbench:
|
||||
enable: null
|
||||
monitor:
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
# SuperBench Config
|
||||
version: v0.6
|
||||
version: v0.7
|
||||
superbench:
|
||||
enable: null
|
||||
monitor:
|
||||
|
|
|
|||
|
|
@ -92,6 +92,7 @@
|
|||
shell: |
|
||||
docker pull {{ docker_image }}
|
||||
become: yes
|
||||
when: docker_pull | default(true)
|
||||
throttle: 32
|
||||
- name: Starting Container
|
||||
shell: |
|
||||
|
|
|
|||
|
|
@ -183,6 +183,7 @@ class SuperBenchRunner():
|
|||
'ssh_port': random.randint(1 << 14, (1 << 15) - 1),
|
||||
'output_dir': str(self._output_path),
|
||||
'docker_image': self._docker_config.image,
|
||||
'docker_pull': bool(self._docker_config.pull),
|
||||
}
|
||||
if bool(self._docker_config.username) and bool(self._docker_config.password):
|
||||
extravars.update(
|
||||
|
|
|
|||
|
|
@ -60,6 +60,12 @@ class SuperBenchCLIScenarioTest(ScenarioTest):
|
|||
mocked_failure_count.return_value = 0
|
||||
self.cmd('sb deploy --host-list localhost', checks=[NoneCheck()])
|
||||
|
||||
@mock.patch('superbench.runner.SuperBenchRunner.get_failure_count')
|
||||
def test_sb_deploy_skippull(self, mocked_failure_count):
|
||||
"""Test sb deploy without docker pull."""
|
||||
mocked_failure_count.return_value = 0
|
||||
self.cmd('sb deploy --host-list localhost --no-image-pull', checks=[NoneCheck()])
|
||||
|
||||
def test_sb_deploy_no_host(self):
|
||||
"""Test sb deploy, no host_file or host_list provided, should fail."""
|
||||
self.cmd('sb deploy', expect_failure=True)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,44 @@
|
|||
---
|
||||
slug: release-sb-v0.7
|
||||
title: Releasing SuperBench v0.7
|
||||
author: Peng Cheng
|
||||
author_title: SuperBench Team
|
||||
author_url: https://github.com/cp5555
|
||||
author_image_url: https://github.com/cp5555.png
|
||||
tags: [superbench, announcement, release]
|
||||
---
|
||||
|
||||
We are very happy to announce that **SuperBench 0.7.0 version** is officially released today!
|
||||
|
||||
You can install and try superbench by following [Getting Started Tutorial](https://microsoft.github.io/superbenchmark/docs/getting-started/installation).
|
||||
|
||||
## SuperBench 0.7.0 Release Notes
|
||||
|
||||
### SuperBench Improvement
|
||||
|
||||
- Support non-zero return code when "sb deploy" or "sb run" fails in Ansible.
|
||||
- Support log flushing to the result file during runtime.
|
||||
- Update version to include revision hash and date.
|
||||
- Support "pattern" in mpi mode to run tasks in parallel.
|
||||
- Support topo-aware, all-pair, and K-batch pattern in mpi mode.
|
||||
- Fix Transformers version to avoid Tensorrt failure.
|
||||
- Add CUDA11.8 Docker image for NVIDIA arch90 GPUs.
|
||||
- Support "sb deploy" without pulling image.
|
||||
|
||||
### Micro-benchmark Improvements
|
||||
|
||||
- Support list of custom config string in cudnn-functions and cublas-functions.
|
||||
- Support correctness check in cublas-functions.
|
||||
- Support GEMM-FLOPS for NVIDIA arch90 GPUs.
|
||||
- Support cuBLASLt FP16 and FP8 GEMM.
|
||||
- Add wait time option to resolve mem-bw unstable issue.
|
||||
- Fix bug for incorrect datatype judgement in cublas-function source code.
|
||||
|
||||
### Model Benchmark Improvements
|
||||
|
||||
- Support FP8 in BERT model training.
|
||||
|
||||
### Distributed Benchmark Improvements
|
||||
|
||||
- Support pair-wise pattern in IB validation benchmark.
|
||||
- Support topo-aware, pair-wise, and K-batch pattern in nccl-bw benchmark.
|
||||
|
|
@ -101,7 +101,7 @@ module.exports = {
|
|||
announcementBar: {
|
||||
id: 'supportus',
|
||||
content:
|
||||
'📢 <a href="https://microsoft.github.io/superbenchmark/blog/release-sb-v0.6">v0.6.0</a> has been released! ' +
|
||||
'📢 <a href="https://microsoft.github.io/superbenchmark/blog/release-sb-v0.7">v0.7.0</a> has been released! ' +
|
||||
'⭐️ If you like SuperBench, give it a star on <a target="_blank" rel="noopener noreferrer" href="https://github.com/microsoft/superbenchmark">GitHub</a>! ⭐️',
|
||||
},
|
||||
algolia: {
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "superbench-website",
|
||||
"version": "0.6.0",
|
||||
"version": "0.7.0",
|
||||
"lockfileVersion": 1,
|
||||
"requires": true,
|
||||
"dependencies": {
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "superbench-website",
|
||||
"version": "0.6.0",
|
||||
"version": "0.7.0",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"docusaurus": "docusaurus",
|
||||
|
|
|
|||
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