Results from GH action on NVIDIA_RTX4090x2

open/MLCommons/code/bert-99.9/README.md

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+TBD

open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/bert-99.9/offline/README.md

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+This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops).
+
+*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.*
+
+## Host platform
+
+* OS version: Linux-6.2.0-39-generic-x86_64-with-glibc2.29
+* CPU version: x86_64
+* Python version: 3.8.10 (default, Sep 11 2024, 16:02:53) 
+[GCC 9.4.0]
+* MLCommons CM version: 3.3.4
+
+## CM Run Command
+
+See [CM installation guide](https://docs.mlcommons.org/inference/install/).
+
+```bash
+pip install -U cmind
+
+cm rm cache -f
+
+cm pull repo gateoverflow@cm4mlops --checkout=9aecee87a3027de8e20c63f9976584850a09ed9e
+
+cm run script \
+	--tags=app,mlperf,inference,generic,_nvidia,_bert-99.9,_tensorrt,_cuda,_valid,_r4.1-dev_default,_offline \
+	--quiet=true \
+	--env.CM_QUIET=yes \
+	--env.CM_MLPERF_IMPLEMENTATION=nvidia \
+	--env.CM_MLPERF_MODEL=bert-99.9 \
+	--env.CM_MLPERF_RUN_STYLE=valid \
+	--env.CM_MLPERF_SKIP_SUBMISSION_GENERATION=False \
+	--env.CM_MLPERF_BACKEND=tensorrt \
+	--env.CM_MLPERF_SUBMISSION_SYSTEM_TYPE=datacenter,edge \
+	--env.CM_MLPERF_CLEAN_ALL=True \
+	--env.CM_MLPERF_DEVICE=cuda \
+	--env.CM_MLPERF_SUBMISSION_DIVISION=closed \
+	--env.CM_MLPERF_USE_DOCKER=True \
+	--env.CM_NVIDIA_GPU_NAME=rtx_4090 \
+	--env.CM_HW_NAME=RTX4090x2 \
+	--env.CM_RUN_MLPERF_SUBMISSION_PREPROCESSOR=yes \
+	--env.CM_MLPERF_INFERENCE_PULL_CODE_CHANGES=yes \
+	--env.CM_MLPERF_INFERENCE_PULL_SRC_CHANGES=yes \
+	--env.OUTPUT_BASE_DIR=/home/arjun/gh_action_results \
+	--env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/gh_action_submissions \
+	--env.CM_MLPERF_SUBMITTER=MLCommons \
+	--env.CM_USE_DATASET_FROM_HOST=yes \
+	--env.CM_MLPERF_LOADGEN_ALL_SCENARIOS=yes \
+	--env.CM_MLPERF_LOADGEN_COMPLIANCE=yes \
+	--env.CM_MLPERF_SUBMISSION_RUN=yes \
+	--env.CM_RUN_MLPERF_ACCURACY=on \
+	--env.CM_RUN_SUBMISSION_CHECKER=yes \
+	--env.CM_TAR_SUBMISSION_DIR=yes \
+	--env.CM_MLPERF_SUBMISSION_GENERATION_STYLE=full \
+	--env.CM_MLPERF_INFERENCE_VERSION=4.1-dev \
+	--env.CM_RUN_MLPERF_INFERENCE_APP_DEFAULTS=r4.1-dev_default \
+	--env.CM_MLPERF_LOADGEN_ALL_MODES=yes \
+	--env.CM_MLPERF_INFERENCE_SOURCE_VERSION=4.1.23 \
+	--env.CM_MLPERF_LAST_RELEASE=v4.1 \
+	--env.CM_TMP_CURRENT_PATH=/home/arjun/actions-runner/_work/cm4mlops/cm4mlops \
+	--env.CM_TMP_PIP_VERSION_STRING= \
+	--env.CM_MODEL=bert-99.9 \
+	--env.CM_MLPERF_CLEAN_SUBMISSION_DIR=yes \
+	--env.CM_RERUN=yes \
+	--env.CM_MLPERF_LOADGEN_EXTRA_OPTIONS= \
+	--env.CM_MLPERF_LOADGEN_MODE=performance \
+	--env.CM_MLPERF_LOADGEN_SCENARIO=Offline \
+	--env.CM_MLPERF_LOADGEN_SCENARIOS,=Offline,Server \
+	--env.CM_MLPERF_LOADGEN_MODES,=performance,accuracy \
+	--env.CM_OUTPUT_FOLDER_NAME=valid_results \
+	--env.CM_DOCKER_REUSE_EXISTING_CONTAINER=no \
+	--env.CM_DOCKER_DETACHED_MODE=yes \
+	--add_deps_recursive.compiler.tags=gcc \
+	--add_deps_recursive.coco2014-original.tags=_full \
+	--add_deps_recursive.coco2014-preprocessed.tags=_full \
+	--add_deps_recursive.imagenet-original.tags=_full \
+	--add_deps_recursive.imagenet-preprocessed.tags=_full \
+	--add_deps_recursive.openimages-original.tags=_full \
+	--add_deps_recursive.openimages-preprocessed.tags=_full \
+	--add_deps_recursive.openorca-original.tags=_full \
+	--add_deps_recursive.openorca-preprocessed.tags=_full \
+	--add_deps_recursive.get-mlperf-inference-results-dir.tags=_version.r4_1-dev \
+	--add_deps_recursive.get-mlperf-inference-submission-dir.tags=_version.r4_1-dev \
+	--add_deps_recursive.mlperf-inference-nvidia-scratch-space.tags=_version.r4_1-dev \
+	--adr.compiler.tags=gcc \
+	--adr.coco2014-original.tags=_full \
+	--adr.coco2014-preprocessed.tags=_full \
+	--adr.imagenet-original.tags=_full \
+	--adr.imagenet-preprocessed.tags=_full \
+	--adr.openimages-original.tags=_full \
+	--adr.openimages-preprocessed.tags=_full \
+	--adr.openorca-original.tags=_full \
+	--adr.openorca-preprocessed.tags=_full \
+	--adr.get-mlperf-inference-results-dir.tags=_version.r4_1-dev \
+	--adr.get-mlperf-inference-submission-dir.tags=_version.r4_1-dev \
+	--adr.mlperf-inference-nvidia-scratch-space.tags=_version.r4_1-dev \
+	--v=False \
+	--print_env=False \
+	--print_deps=False \
+	--dump_version_info=True \
+	--env.OUTPUT_BASE_DIR=/cm-mount/home/arjun/gh_action_results \
+	--env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/cm-mount/home/arjun/gh_action_submissions \
+	--env.MLPERF_SCRATCH_PATH=/home/cmuser/CM/repos/local/cache/e066920512fd47b7
+```
+*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts),
+ you should simply reload gateoverflow@cm4mlops without checkout and clean CM cache as follows:*
+
+```bash
+cm rm repo gateoverflow@cm4mlops
+cm pull repo gateoverflow@cm4mlops
+cm rm cache -f
+
+```
+
+## Results
+
+Platform: RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config
+
+Model Precision: fp16
+
+### Accuracy Results 
+`F1`: `90.88324`, Required accuracy for closed division `>= 90.78313`
+
+### Performance Results 
+`Samples per second`: `3342.39`

open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/bert-99.9/offline/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config.json

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+{
+  "starting_weights_filename": "https://zenodo.org/record/3750364/files/bert_large_v1_1_fake_quant.onnx",
+  "retraining": "no",
+  "input_data_types": "int32",
+  "weight_data_types": "fp16",
+  "weight_transformations": "quantization, affine fusion"
+}