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use JIT_BATCH_SIZE=4 for GPT2 3090 benchmark (#3870)

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smaller first batch saves about 0.05 ms per token. 1.75ms / tok on local 3090
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chenyu
2024-03-22 00:40:06 -04:00
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parent fe6ceff15f
commit 82ce60e172
1 changed files with 1 additions and 1 deletions
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.github/workflows/benchmark.yml vendored
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@@ -113,7 +113,7 @@ jobs:
- name: Run GPT2 w HALF
run: CUDA=1 JIT=1 HALF=1 python3 examples/gpt2.py --count 10 --temperature 0 --timing | tee gpt2_half.txt
- name: Run GPT2 w HALF/BEAM
run: CUDA=1 JIT=1 HALF=1 BEAM=2 CACHELEVEL=0 CAST_BEFORE_VIEW=0 python3 examples/gpt2.py --count 10 --temperature 0 --timing | tee gpt2_half_beam.txt
run: CUDA=1 JIT=1 HALF=1 BEAM=2 CACHELEVEL=0 CAST_BEFORE_VIEW=0 JIT_BATCH_SIZE=4 python3 examples/gpt2.py --count 10 --temperature 0 --timing | tee gpt2_half_beam.txt
- name: Run full CIFAR training
run: time CUDA=1 HALF=1 LATEWINO=1 STEPS=1000 TARGET_EVAL_ACC_PCT=93.3 python3 examples/hlb_cifar10.py | tee train_cifar_one_gpu.txt
- uses: actions/upload-artifact@v4