mirror of https://github.com/commaai/tinygrad.git
516 lines
27 KiB
YAML
516 lines
27 KiB
YAML
name: Benchmarks
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env:
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# TODO: this rescheduling makes gpt2, mixtral and llama unjitted slower
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COMPARE_SCHEDULE: "0"
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RUN_PROCESS_REPLAY: "1"
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ASSERT_PROCESS_REPLAY: "0"
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PYTHONPATH: .
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GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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on:
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push:
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branches:
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- master
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- update_benchmark
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- update_benchmark_staging
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workflow_dispatch:
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inputs:
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run_process_replay:
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description: "Run process replay tests"
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required: false
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default: false
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type: boolean
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jobs:
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testmacbenchmark:
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name: Mac Benchmark
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runs-on: [self-hosted, macOS]
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defaults:
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run:
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shell: bash -o pipefail {0}
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if: github.repository_owner == 'tinygrad'
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steps:
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- name: Checkout Code
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uses: actions/checkout@v4
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- name: Symlink models and datasets
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run: |
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mkdir -p weights
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ln -s ~/tinygrad/extra/disassemblers/applegpu extra/disassemblers/applegpu
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ln -s ~/tinygrad/weights/sd-v1-4.ckpt weights/sd-v1-4.ckpt
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ln -s ~/tinygrad/weights/bpe_simple_vocab_16e6.txt.gz weights/bpe_simple_vocab_16e6.txt.gz
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ln -s ~/tinygrad/weights/LLaMA weights/LLaMA
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ln -s ~/tinygrad/extra/datasets/cifar-10-python.tar.gz extra/datasets/cifar-10-python.tar.gz
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- name: setup staging db
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if: github.ref == 'refs/heads/update_benchmark_staging'
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run: |
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echo "CACHEDB=/tmp/staging.db" >> $GITHUB_ENV
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rm -f /tmp/staging.db /tmp/staging.db-shm /tmp/staging.db-wal
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- name: reset process replay
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run: test/external/process_replay/reset.py
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- name: Run Stable Diffusion
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run: JIT=2 python3 examples/stable_diffusion.py --seed 0 --noshow --timing | tee sd.txt
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- name: Run Stable Diffusion with fp16
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run: JIT=2 python3 examples/stable_diffusion.py --fp16 --seed 0 --noshow --timing | tee sd_fp16.txt
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- name: Run SDXL
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run: JIT=2 python3 examples/sdxl.py --seed 0 --noshow --timing | tee sdxl.txt
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- name: Run model inference benchmark
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run: METAL=1 python3 test/external/external_model_benchmark.py
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- name: Test speed vs torch
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run: BIG=2 MPS=1 python3 test/test_speed_v_torch.py | tee torch_speed.txt
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- name: Test tensor cores
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run: METAL=1 python3 test/test_linearizer.py TestLinearizer.test_tensor_cores TestLinearizer.test_tensor_cores_padded
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- name: Run Tensor Core GEMM
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run: |
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DEBUG=2 python3 extra/gemm/simple_matmul.py | tee matmul.txt
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DEBUG=2 HALF=1 python3 extra/gemm/simple_matmul.py | tee matmul_half.txt
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- name: Fuzz Padded Tensor Core GEMM
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run: METAL=1 M_START=6 M_STOP=10 M_STEP=1 N_START=6 N_STOP=10 N_STEP=1 K_START=6 K_STOP=24 K_STEP=1 TC_OPT=2 DEBUG=2 python3 ./extra/gemm/fuzz_matmul.py
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- name: Run LLaMA
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run: |
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JIT=0 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_unjitted.txt
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JIT=1 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_jitted.txt
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- name: Run LLaMA with BEAM
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run: JITBEAM=2 IGNORE_BEAM_CACHE=1 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_beam.txt
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- name: Run quantized LLaMA
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run: |
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python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing --quantize int8 | tee llama_int8.txt
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python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing --quantize nf4 | tee llama_nf4.txt
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- name: Run LLaMA 7B on 4 (virtual) GPUs
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run: python3 examples/llama.py --gen 1 --size 7B --shard 4 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_four_gpu.txt
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- name: Run GPT2
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run: |
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JIT=0 python3 examples/gpt2.py --prompt "Hello." --count 10 --temperature 0 --timing | tee gpt2_unjitted.txt
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JIT=1 python3 examples/gpt2.py --prompt "Hello." --count 10 --temperature 0 --timing | tee gpt2_jitted.txt
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- name: Run GPT2 w HALF
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run: HALF=1 python3 examples/gpt2.py --count 10 --temperature 0 --timing | tee gpt2_half.txt
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- name: Run GPT2 w HALF/BEAM
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run: HALF=1 JITBEAM=2 IGNORE_BEAM_CACHE=1 CAST_BEFORE_VIEW=0 python3 examples/gpt2.py --count 10 --temperature 0 --timing | tee gpt2_half_beam.txt
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- name: Train MNIST
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run: time PYTHONPATH=. TARGET_EVAL_ACC_PCT=97.3 python3 examples/beautiful_mnist.py | tee beautiful_mnist.txt
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- name: Run 10 CIFAR training steps
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run: JIT=2 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar.txt
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- name: Run 10 CIFAR training steps w HALF
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run: JIT=2 STEPS=10 DEFAULT_FLOAT=HALF python3 examples/hlb_cifar10.py | tee train_cifar_half.txt
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#- name: Run 10 CIFAR training steps w BF16
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# run: STEPS=10 DEFAULT_FLOAT=BFLOAT16 python3 examples/hlb_cifar10.py | tee train_cifar_bf16.txt
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- name: Run 10 CIFAR training steps w winograd
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run: JIT=2 WINO=1 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar_wino.txt
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- uses: actions/upload-artifact@v4
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with:
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name: Speed (Mac)
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path: |
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onnx_inference_speed.csv
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torch_speed.txt
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llama_unjitted.txt
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llama_jitted.txt
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llama_beam.txt
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llama_int8.txt
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llama_nf4.txt
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llama_four_gpu.txt
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gpt2_unjitted.txt
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gpt2_jitted.txt
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gpt2_half.txt
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gpt2_half_beam.txt
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matmul.txt
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matmul_half.txt
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sd.txt
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sd_fp16.txt
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sdxl.txt
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beautiful_mnist.txt
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train_cifar.txt
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train_cifar_half.txt
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train_cifar_bf16.txt
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train_cifar_wino.txt
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- name: Run process replay tests
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run: cp test/external/process_replay/process_replay.py ./process_replay.py && git fetch origin master && git -c advice.detachedHead=false checkout origin/master && PYTHONPATH=. python3 process_replay.py
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testnvidiabenchmark:
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name: tinybox green Benchmark
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runs-on: [self-hosted, Linux, tinyboxgreen]
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defaults:
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run:
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shell: bash -o pipefail {0}
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if: github.repository_owner == 'tinygrad'
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steps:
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- name: Checkout Code
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uses: actions/checkout@v4
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- name: Print nvidia-smi
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run: nvidia-smi
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- name: Symlink models and datasets
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run: |
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mkdir -p weights
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ln -s ~/tinygrad/weights/LLaMA weights/LLaMA
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ln -s /raid/weights/mixtral-8x7b-32kseqlen weights/mixtral-8x7b-32kseqlen
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ln -s /raid/weights/LLaMA-2 weights/LLaMA-2
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ln -s /raid/weights/LLaMA-3 weights/LLaMA-3
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mkdir -p extra/datasets
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ln -s /raid/datasets/imagenet extra/datasets/imagenet
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- name: setup staging db
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if: github.ref == 'refs/heads/update_benchmark_staging'
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run: |
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echo "CACHEDB=/tmp/staging.db" >> $GITHUB_ENV
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rm -f /tmp/staging.db /tmp/staging.db-shm /tmp/staging.db-wal
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- name: reset process replay
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run: test/external/process_replay/reset.py
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- name: Run model inference benchmark
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run: NV=1 NOCLANG=1 python3 test/external/external_model_benchmark.py
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- name: Test speed vs torch
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run: NV=1 BIG=2 TORCHCUDA=1 python3 test/test_speed_v_torch.py | tee torch_speed.txt
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- name: Test tensor cores
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run: |
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NV=1 python3 test/test_linearizer.py TestLinearizer.test_tensor_cores TestLinearizer.test_tensor_cores_padded
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PTX=1 NV=1 python3 test/test_linearizer.py TestLinearizer.test_tensor_cores TestLinearizer.test_tensor_cores_padded
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- name: Run Tensor Core GEMM (CUDA)
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run: |
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CUDA=1 HALF=1 DEBUG=2 python3 extra/gemm/simple_matmul.py | tee matmul.txt
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CUDA=1 BFLOAT16=1 DEBUG=2 python3 extra/gemm/simple_matmul.py | tee matmul_bfloat16.txt
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- name: Run Tensor Core GEMM (PTX)
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run: NV=1 PTX=1 HALF=1 DEBUG=2 python3 extra/gemm/simple_matmul.py | tee matmul_ptx.txt
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- name: Run Tensor Core GEMM (NV)
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run: NV=1 HALF=1 DEBUG=2 python3 extra/gemm/simple_matmul.py | tee matmul_nv.txt
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- name: Run Tensor Core GEMM (NV) with BEAM
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run: BEAM=4 NV=1 HALF=1 IGNORE_BEAM_CACHE=1 DEBUG=2 python3 extra/gemm/simple_matmul.py
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- name: Run Stable Diffusion
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run: NV=1 python3 examples/stable_diffusion.py --seed 0 --noshow --timing | tee sd.txt
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- name: Run SDXL
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run: NV=1 python3 examples/sdxl.py --seed 0 --noshow --timing | tee sdxl.txt
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- name: Run LLaMA
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run: |
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NV=1 JIT=0 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_unjitted.txt
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NV=1 JIT=1 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_jitted.txt
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- name: Run LLaMA with BEAM
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run: NV=1 JITBEAM=2 IGNORE_BEAM_CACHE=1 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_beam.txt
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- name: Run LLaMA 7B on 4 GPUs
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run: NV=1 python3 examples/llama.py --gen 1 --size 7B --shard 4 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_four_gpu.txt
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- name: Run LLaMA 7B on 6 GPUs
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run: NV=1 python3 examples/llama.py --gen 1 --size 7B --shard 6 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_six_gpu.txt
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- name: Run LLaMA-3 8B BEAM
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run: NV=1 JITBEAM=2 IGNORE_BEAM_CACHE=1 python3 examples/llama3.py --model weights/LLaMA-3/8B-SF-DPO/ --benchmark --temperature 0 | tee llama3_beam.txt
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- name: Run LLaMA-3 8B on 4 GPUs
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run: NV=1 python3 examples/llama3.py --shard 4 --model weights/LLaMA-3/8B-SF-DPO/ --benchmark --temperature 0 | tee llama3_four_gpu.txt
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- name: Run LLaMA-3 8B on 6 GPUs
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run: NV=1 python3 examples/llama3.py --shard 6 --model weights/LLaMA-3/8B-SF-DPO/ --benchmark --temperature 0 | tee llama3_six_gpu.txt
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- name: Run LLaMA-2 70B
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run: NV=1 MAX_CONTEXT=256 python3 examples/llama.py --gen 2 --size 70B --shard 6 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_2_70B.txt
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- name: Run Mixtral 8x7B
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run: time NV=1 python3 examples/mixtral.py --temperature 0 --count 10 --timing | tee mixtral.txt
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- name: Run GPT2
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run: |
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NV=1 JIT=0 python3 examples/gpt2.py --prompt "Hello." --count 10 --temperature 0 --timing | tee gpt2_unjitted.txt
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NV=1 JIT=1 python3 examples/gpt2.py --prompt "Hello." --count 10 --temperature 0 --timing | tee gpt2_jitted.txt
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- name: Run GPT2 w HALF
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run: NV=1 HALF=1 python3 examples/gpt2.py --count 10 --temperature 0 --timing | tee gpt2_half.txt
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- name: Run GPT2 w HALF/BEAM
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run: NV=1 HALF=1 JITBEAM=2 IGNORE_BEAM_CACHE=1 CAST_BEFORE_VIEW=0 python3 examples/gpt2.py --count 10 --temperature 0 --timing | tee gpt2_half_beam.txt
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- uses: actions/upload-artifact@v4
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with:
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name: Speed (NVIDIA)
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path: |
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onnx_inference_speed.csv
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torch_speed.txt
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matmul.txt
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matmul_bfloat16.txt
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matmul_ptx.txt
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matmul_nv.txt
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sd.txt
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sdxl.txt
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llama_unjitted.txt
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llama_jitted.txt
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llama_beam.txt
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llama_four_gpu.txt
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llama_six_gpu.txt
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llama3_beam.txt
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llama3_four_gpu.txt
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llama3_six_gpu.txt
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llama_2_70B.txt
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mixtral.txt
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gpt2_unjitted.txt
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gpt2_jitted.txt
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gpt2_half.txt
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gpt2_half_beam.txt
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- name: Run process replay tests
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run: cp test/external/process_replay/process_replay.py ./process_replay.py && git fetch origin master && git -c advice.detachedHead=false checkout origin/master && PYTHONPATH=. python3 process_replay.py
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testmorenvidiabenchmark:
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name: tinybox green Training Benchmark
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runs-on: [self-hosted, Linux, tinyboxgreen]
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defaults:
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run:
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shell: bash -o pipefail {0}
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if: github.repository_owner == 'tinygrad'
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steps:
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- name: Checkout Code
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uses: actions/checkout@v4
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- name: Symlink models and datasets
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run: |
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mkdir -p weights
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ln -s ~/tinygrad/weights/bpe_simple_vocab_16e6.txt.gz weights/bpe_simple_vocab_16e6.txt.gz
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ln -s ~/tinygrad/weights/LLaMA weights/LLaMA
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ln -s ~/tinygrad/extra/datasets/cifar-10-python.tar.gz extra/datasets/cifar-10-python.tar.gz
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ln -s /raid/weights/mixtral-8x7b-32kseqlen weights/mixtral-8x7b-32kseqlen
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ln -s /raid/weights/LLaMA-2 weights/LLaMA-2
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mkdir -p extra/datasets
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ln -s /raid/datasets/imagenet extra/datasets/imagenet
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- name: setup staging db
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if: github.ref == 'refs/heads/update_benchmark_staging'
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run: |
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echo "CACHEDB=/tmp/staging.db" >> $GITHUB_ENV
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rm -f /tmp/staging.db /tmp/staging.db-shm /tmp/staging.db-wal
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- name: reset process replay
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run: test/external/process_replay/reset.py
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- name: Fuzz Padded Tensor Core GEMM (NV)
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run: NV=1 M_START=12 M_STOP=20 M_STEP=1 N_START=6 N_STOP=10 N_STEP=1 K_START=28 K_STOP=36 K_STEP=1 HALF=1 TC_OPT=2 python3 ./extra/gemm/fuzz_matmul.py
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- name: Fuzz Padded Tensor Core GEMM (PTX)
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run: NV=1 PTX=1 M_START=12 M_STOP=20 M_STEP=1 N_START=6 N_STOP=10 N_STEP=1 K_START=28 K_STOP=36 K_STEP=1 HALF=1 TC_OPT=2 python3 ./extra/gemm/fuzz_matmul.py
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- name: Train MNIST
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run: time PYTHONPATH=. NV=1 TARGET_EVAL_ACC_PCT=97.3 python3 examples/beautiful_mnist.py | tee beautiful_mnist.txt
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- name: Run 10 CIFAR training steps
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run: NV=1 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar.txt
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- name: Run 10 CIFAR training steps w HALF
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run: NV=1 STEPS=10 DEFAULT_FLOAT=HALF python3 examples/hlb_cifar10.py | tee train_cifar_half.txt
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- name: Run 10 CIFAR training steps w BF16
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run: NV=1 STEPS=10 DEFAULT_FLOAT=BFLOAT16 python3 examples/hlb_cifar10.py | tee train_cifar_bf16.txt
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- name: Run 10 CIFAR training steps w winograd
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run: NV=1 WINO=1 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar_wino.txt
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- name: Run full CIFAR training w 1 GPU
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run: time NV=1 DEFAULT_FLOAT=HALF LATEWINO=1 STEPS=1000 TARGET_EVAL_ACC_PCT=93.2 python3 examples/hlb_cifar10.py | tee train_cifar_one_gpu.txt
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- name: Run full CIFAR training steps w 6 GPUS
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run: time NV=1 DEFAULT_FLOAT=HALF STEPS=350 BS=1536 GPUS=6 TARGET_EVAL_ACC_PCT=93.2 python3 examples/hlb_cifar10.py | tee train_cifar_six_gpu.txt
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- name: Run MLPerf resnet eval on training data
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run: time NV=1 MODEL=resnet python3 examples/mlperf/model_eval.py
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- name: Run 10 MLPerf ResNet50 training steps (1 gpu)
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run: NV=1 DEFAULT_FLOAT=HALF BENCHMARK=10 BS=256 GPUS=1 MODEL=resnet python3 examples/mlperf/model_train.py | tee train_resnet_one_gpu.txt
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- name: Run 10 MLPerf ResNet50 training steps (6 gpu)
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run: NV=1 DEFAULT_FLOAT=HALF BENCHMARK=10 BS=1536 GPUS=6 MODEL=resnet python3 examples/mlperf/model_train.py | tee train_resnet.txt
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- uses: actions/upload-artifact@v4
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with:
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name: Speed (NVIDIA Training)
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path: |
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beautiful_mnist.txt
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train_cifar.txt
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train_cifar_half.txt
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train_cifar_bf16.txt
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train_cifar_wino.txt
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train_cifar_one_gpu.txt
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train_resnet.txt
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train_resnet_one_gpu.txt
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train_cifar_six_gpu.txt
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- name: Run process replay tests
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run: cp test/external/process_replay/process_replay.py ./process_replay.py && git fetch origin master && git -c advice.detachedHead=false checkout origin/master && PYTHONPATH=. python3 process_replay.py
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testamdbenchmark:
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name: tinybox red Benchmark
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runs-on: [self-hosted, Linux, tinybox]
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defaults:
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run:
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shell: bash -o pipefail {0}
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if: github.repository_owner == 'tinygrad'
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steps:
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- name: Checkout Code
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uses: actions/checkout@v4
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- name: Symlink models and datasets
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run: |
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mkdir -p weights
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ln -s ~/tinygrad/weights/bpe_simple_vocab_16e6.txt.gz weights/bpe_simple_vocab_16e6.txt.gz
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ln -s ~/tinygrad/weights/LLaMA weights/LLaMA
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ln -s ~/tinygrad/extra/datasets/cifar-10-python.tar.gz extra/datasets/cifar-10-python.tar.gz
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ln -s /raid/weights/mixtral-8x7b-32kseqlen weights/mixtral-8x7b-32kseqlen
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ln -s /raid/weights/LLaMA-2 weights/LLaMA-2
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ln -s /raid/weights/LLaMA-3 weights/LLaMA-3
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mkdir -p extra/datasets
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ln -s /raid/datasets/imagenet extra/datasets/imagenet
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- name: setup staging db
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if: github.ref == 'refs/heads/update_benchmark_staging'
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run: |
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echo "CACHEDB=/tmp/staging.db" >> $GITHUB_ENV
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rm -f /tmp/staging.db /tmp/staging.db-shm /tmp/staging.db-wal
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- name: reset process replay
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run: test/external/process_replay/reset.py
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- name: Show off tinybox
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run: /opt/rocm/bin/rocm-bandwidth-test
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# TODO: unstable on AMD
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#- name: Run model inference benchmark
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# run: LD_PRELOAD="/opt/rocm/lib/libhsa-runtime64.so" HSA=1 NOCLANG=1 python3 test/external/external_model_benchmark.py
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# TODO: unstable on AMD
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#- name: Test speed vs torch
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# run: |
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# python3 -c "import torch; print(torch.__version__)"
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# LD_PRELOAD="/opt/rocm/lib/libhsa-runtime64.so" HSA=1 BIG=2 TORCHCUDA=1 python3 test/test_speed_v_torch.py | tee torch_speed.txt
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- name: Test tensor cores
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run: |
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AMD=1 python3 test/test_linearizer.py TestLinearizer.test_tensor_cores TestLinearizer.test_tensor_cores_padded
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- name: Run Tensor Core GEMM (AMD)
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run: AMD=1 HALF=1 DEBUG=2 python3 extra/gemm/simple_matmul.py | tee matmul_amd.txt
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|
# TODO: AMD compiler bug causes this to fail
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#- name: Fuzz Padded Tensor Core GEMM
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# run: HSA=1 M_START=12 M_STOP=20 M_STEP=1 N_START=12 N_STOP=20 N_STEP=1 K_START=28 K_STOP=36 K_STEP=1 HALF=1 TC_OPT=2 DEBUG=2 python3 ./extra/gemm/fuzz_matmul.py
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- name: Run Stable Diffusion
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run: AMD=1 python3 examples/stable_diffusion.py --seed 0 --noshow --timing | tee sd.txt
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|
- name: Run SDXL
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run: AMD=1 python3 examples/sdxl.py --seed 0 --noshow --timing | tee sdxl.txt
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|
- name: Run LLaMA 7B
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run: |
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AMD=1 JIT=0 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_unjitted.txt
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AMD=1 JIT=1 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_jitted.txt
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|
- name: Run LLaMA 7B with BEAM
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|
run: AMD=1 JITBEAM=2 IGNORE_BEAM_CACHE=1 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_beam.txt
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|
- name: Run LLaMA 7B on 4 GPUs
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|
run: AMD=1 python3 examples/llama.py --gen 1 --size 7B --shard 4 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_four_gpu.txt
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- name: Run LLaMA 7B on 6 GPUs
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|
run: AMD=1 python3 examples/llama.py --gen 1 --size 7B --shard 6 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_six_gpu.txt
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|
- name: Run LLaMA-3 8B BEAM
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|
run: AMD=1 JITBEAM=2 IGNORE_BEAM_CACHE=1 python3 examples/llama3.py --model weights/LLaMA-3/8B-SF-DPO/ --benchmark --temperature 0 | tee llama3_beam.txt
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|
- name: Run LLaMA-3 8B on 4 GPUs
|
|
run: AMD=1 python3 examples/llama3.py --shard 4 --model weights/LLaMA-3/8B-SF-DPO/ --benchmark --temperature 0 | tee llama3_four_gpu.txt
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|
- name: Run LLaMA-3 8B on 6 GPUs
|
|
run: AMD=1 python3 examples/llama3.py --shard 6 --model weights/LLaMA-3/8B-SF-DPO/ --benchmark --temperature 0 | tee llama3_six_gpu.txt
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|
- name: Run LLaMA-2 70B
|
|
run: AMD=1 python3 examples/llama.py --gen 2 --size 70B --shard 6 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_2_70B.txt
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|
- name: Run Mixtral 8x7B
|
|
run: time AMD=1 python3 examples/mixtral.py --temperature 0 --count 10 --timing | tee mixtral.txt
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|
- name: Run GPT2
|
|
run: |
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|
AMD=1 JIT=0 python3 examples/gpt2.py --prompt "Hello." --count 10 --temperature 0 --timing | tee gpt2_unjitted.txt
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|
AMD=1 JIT=1 python3 examples/gpt2.py --prompt "Hello." --count 10 --temperature 0 --timing | tee gpt2_jitted.txt
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|
- name: Run GPT2 w HALF
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|
run: AMD=1 HALF=1 python3 examples/gpt2.py --count 10 --temperature 0 --timing | tee gpt2_half.txt
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|
- name: Run GPT2 w HALF/BEAM
|
|
run: AMD=1 HALF=1 JITBEAM=2 IGNORE_BEAM_CACHE=1 CAST_BEFORE_VIEW=0 python3 examples/gpt2.py --count 10 --temperature 0 --timing | tee gpt2_half_beam.txt
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|
- uses: actions/upload-artifact@v4
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|
with:
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name: Speed (AMD)
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|
path: |
|
|
onnx_inference_speed.csv
|
|
torch_speed.txt
|
|
llama_unjitted.txt
|
|
llama_jitted.txt
|
|
llama_beam.txt
|
|
llama_four_gpu.txt
|
|
llama_six_gpu.txt
|
|
llama3_beam.txt
|
|
llama3_four_gpu.txt
|
|
llama3_six_gpu.txt
|
|
llama_2_70B.txt
|
|
gpt2_unjitted.txt
|
|
gpt2_jitted.txt
|
|
gpt2_half.txt
|
|
gpt2_half_beam.txt
|
|
matmul.txt
|
|
matmul_amd.txt
|
|
sd.txt
|
|
sdxl.txt
|
|
mixtral.txt
|
|
- name: Run process replay tests
|
|
run: cp test/external/process_replay/process_replay.py ./process_replay.py && git fetch origin master && git -c advice.detachedHead=false checkout origin/master && PYTHONPATH=. python3 process_replay.py
|
|
|
|
testmoreamdbenchmark:
|
|
name: tinybox red Training Benchmark
|
|
runs-on: [self-hosted, Linux, tinybox]
|
|
defaults:
|
|
run:
|
|
shell: bash -o pipefail {0}
|
|
if: github.repository_owner == 'tinygrad'
|
|
steps:
|
|
- name: Checkout Code
|
|
uses: actions/checkout@v4
|
|
- name: Symlink models and datasets
|
|
run: |
|
|
mkdir -p weights
|
|
ln -s ~/tinygrad/weights/bpe_simple_vocab_16e6.txt.gz weights/bpe_simple_vocab_16e6.txt.gz
|
|
ln -s ~/tinygrad/weights/LLaMA weights/LLaMA
|
|
ln -s ~/tinygrad/extra/datasets/cifar-10-python.tar.gz extra/datasets/cifar-10-python.tar.gz
|
|
ln -s /raid/weights/mixtral-8x7b-32kseqlen weights/mixtral-8x7b-32kseqlen
|
|
ln -s /raid/weights/LLaMA-2 weights/LLaMA-2
|
|
mkdir -p extra/datasets
|
|
ln -s /raid/datasets/imagenet extra/datasets/imagenet
|
|
- name: setup staging db
|
|
if: github.ref == 'refs/heads/update_benchmark_staging'
|
|
run: |
|
|
echo "CACHEDB=/tmp/staging.db" >> $GITHUB_ENV
|
|
rm -f /tmp/staging.db /tmp/staging.db-shm /tmp/staging.db-wal
|
|
- name: reset process replay
|
|
run: test/external/process_replay/reset.py
|
|
- name: Train MNIST
|
|
run: time PYTHONPATH=. AMD=1 TARGET_EVAL_ACC_PCT=97.3 python3 examples/beautiful_mnist.py | tee beautiful_mnist.txt
|
|
- name: Run 10 CIFAR training steps
|
|
run: AMD=1 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar.txt
|
|
- name: Run 10 CIFAR training steps w HALF
|
|
run: AMD=1 STEPS=10 DEFAULT_FLOAT=HALF python3 examples/hlb_cifar10.py | tee train_cifar_half.txt
|
|
- name: Run 10 CIFAR training steps w BF16
|
|
run: AMD=1 STEPS=10 DEFAULT_FLOAT=BFLOAT16 python3 examples/hlb_cifar10.py | tee train_cifar_bf16.txt
|
|
- name: Run 10 CIFAR training steps w winograd
|
|
run: AMD=1 WINO=1 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar_wino.txt
|
|
- name: Run full CIFAR training w 1 GPU
|
|
run: time AMD=1 DEFAULT_FLOAT=HALF LATEWINO=1 STEPS=1000 TARGET_EVAL_ACC_PCT=93.2 python3 examples/hlb_cifar10.py | tee train_cifar_one_gpu.txt
|
|
- name: Run full CIFAR training steps w 6 GPUS
|
|
run: time AMD=1 DEFAULT_FLOAT=HALF STEPS=350 BS=1536 GPUS=6 TARGET_EVAL_ACC_PCT=93.2 python3 examples/hlb_cifar10.py | tee train_cifar_six_gpu.txt
|
|
- name: Run MLPerf resnet eval
|
|
run: time AMD=1 MODEL=resnet python3 examples/mlperf/model_eval.py
|
|
- name: Run 10 MLPerf ResNet50 training steps (1 gpu)
|
|
run: AMD=1 DEFAULT_FLOAT=HALF BENCHMARK=10 BS=256 GPUS=1 MODEL=resnet python3 examples/mlperf/model_train.py | tee train_resnet_one_gpu.txt
|
|
- name: Run 10 MLPerf ResNet50 training steps (6 gpu)
|
|
run: AMD=1 DEFAULT_FLOAT=HALF BENCHMARK=10 BS=1536 GPUS=6 MODEL=resnet python3 examples/mlperf/model_train.py | tee train_resnet.txt
|
|
- uses: actions/upload-artifact@v4
|
|
with:
|
|
name: Speed (AMD Training)
|
|
path: |
|
|
beautiful_mnist.txt
|
|
train_cifar.txt
|
|
train_cifar_half.txt
|
|
train_cifar_bf16.txt
|
|
train_cifar_wino.txt
|
|
train_cifar_one_gpu.txt
|
|
train_resnet.txt
|
|
train_resnet_one_gpu.txt
|
|
train_cifar_six_gpu.txt
|
|
- name: Run process replay tests
|
|
run: cp test/external/process_replay/process_replay.py ./process_replay.py && git fetch origin master && git -c advice.detachedHead=false checkout origin/master && PYTHONPATH=. python3 process_replay.py
|
|
|
|
testqualcommbenchmark:
|
|
name: comma Benchmark
|
|
runs-on: [self-hosted, Linux, comma]
|
|
defaults:
|
|
run:
|
|
shell: bash -o pipefail {0}
|
|
if: github.repository_owner == 'tinygrad'
|
|
steps:
|
|
- name: Checkout Code
|
|
uses: actions/checkout@v4
|
|
- name: setup staging db
|
|
if: github.ref == 'refs/heads/update_benchmark_staging'
|
|
run: |
|
|
echo "CACHEDB=/tmp/staging.db" >> $GITHUB_ENV
|
|
rm -f /tmp/staging.db /tmp/staging.db-shm /tmp/staging.db-wal
|
|
- name: reset process replay
|
|
run: test/external/process_replay/reset.py
|
|
- name: openpilot compile 0.9.4
|
|
run: PYTHONPATH=. NOLOCALS=1 FLOAT16=1 IMAGE=2 QCOM=1 python examples/openpilot/compile2.py | tee openpilot_compile_0_9_4.txt
|
|
- name: openpilot compile 0.9.7
|
|
run: PYTHONPATH=. NOLOCALS=1 FLOAT16=1 IMAGE=2 QCOM=1 python examples/openpilot/compile2.py https://github.com/commaai/openpilot/raw/v0.9.7/selfdrive/modeld/models/supercombo.onnx | tee openpilot_compile_0_9_7.txt
|
|
- name: validate openpilot 0.9.7
|
|
run: PYTHONPATH=. FLOAT16=0 IMAGE=2 QCOM=1 python3 test/external/external_benchmark_openpilot.py https://github.com/commaai/openpilot/raw/v0.9.7/selfdrive/modeld/models/supercombo.onnx | tee openpilot_image_0_9_7.txt
|
|
- name: benchmark openpilot 0.9.4
|
|
run: PYTHONPATH=. QCOM=1 python3 test/external/external_benchmark_openpilot.py https://github.com/commaai/openpilot/raw/v0.9.4/selfdrive/modeld/models/supercombo.onnx | tee openpilot_0_9_4.txt
|
|
- name: benchmark openpilot 0.9.7
|
|
run: PYTHONPATH=. QCOM=1 python3 test/external/external_benchmark_openpilot.py https://github.com/commaai/openpilot/raw/v0.9.7/selfdrive/modeld/models/supercombo.onnx | tee openpilot_0_9_7.txt
|
|
- name: benchmark openpilot w IMAGE=2 0.9.4
|
|
run: PYTHONPATH=. NOLOCALS=1 FLOAT16=1 IMAGE=2 QCOM=1 python3 test/external/external_benchmark_openpilot.py https://github.com/commaai/openpilot/raw/v0.9.4/selfdrive/modeld/models/supercombo.onnx | tee openpilot_image_0_9_4.txt
|
|
- name: benchmark openpilot w IMAGE=2 0.9.7
|
|
run: PYTHONPATH=. NOLOCALS=1 FLOAT16=1 IMAGE=2 QCOM=1 python3 test/external/external_benchmark_openpilot.py https://github.com/commaai/openpilot/raw/v0.9.7/selfdrive/modeld/models/supercombo.onnx | tee openpilot_image_0_9_7.txt
|
|
- name: openpilot compile3 0.9.7
|
|
run: PYTHONPATH="." QCOM=1 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/v0.9.7/selfdrive/modeld/models/supercombo.onnx
|
|
- name: openpilot compile3 0.9.7+ tomb raider
|
|
run: PYTHONPATH="." QCOM=1 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/e8bea2c78ffa92685ece511e9b554122aaf1a79d/selfdrive/modeld/models/supercombo.onnx
|
|
- name: Run process replay tests
|
|
run: cp test/external/process_replay/process_replay.py ./process_replay.py && git fetch origin master && git -c advice.detachedHead=false checkout origin/master && PYTHONPATH=. python3 process_replay.py
|
|
- uses: actions/upload-artifact@v4
|
|
with:
|
|
name: Speed (comma)
|
|
path: |
|
|
openpilot_compile_0_9_4.txt
|
|
openpilot_compile_0_9_7.txt
|
|
openpilot_0_9_4.txt
|
|
openpilot_0_9_7.txt
|
|
openpilot_image_0_9_4.txt
|
|
openpilot_image_0_9_7.txt
|