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feat: tinyboxgreen (#4366)
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* feat: tinyboxgreen

* feat: tinyboxgreenv2

* fix symlink weights

* fix: remove llama 2 70b for now

* feat: naming

* fix: remove extra cifar steps

* feat: disable mixtral on nvidia
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@wozeparrot
wozeparrot committed May 21, 2024
1 parent de733d7 commit 0043249
Showing 1 changed file with 71 additions and 13 deletions.
84 changes: 71 additions & 13 deletions .github/workflows/benchmark.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -91,7 +91,7 @@ jobs:
train_cifar_wino.txt
testnvidiabenchmark:
name: NVIDIA Benchmark
name: tinybox green Benchmark
runs-on: [self-hosted, Linux, tinyboxgreen]
defaults:
run:
Expand All @@ -108,6 +108,10 @@ jobs:
run: |
mkdir -p weights
ln -s ~/tinygrad/weights/LLaMA weights/LLaMA
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: Run model inference benchmark
run: CUDA=1 NOCLANG=1 python3 test/external/external_model_benchmark.py
- name: Test speed vs torch
Expand All @@ -130,12 +134,22 @@ jobs:
run: CUDA=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
- name: Fuzz Padded Tensor Core GEMM(PTX)
run: CUDA=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
- name: Run Stable Diffusion
run: CUDA=1 python3 examples/stable_diffusion.py --seed 0 --noshow --timing | tee sd.txt
- name: Run LLaMA
run: |
CUDA=1 JIT=0 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_unjitted.txt
CUDA=1 JIT=1 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_jitted.txt
- name: Run LLaMA with BEAM
run: CUDA=1 JIT=1 BEAM=2 CACHELEVEL=0 python3 examples/llama.py --gen 1 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_beam.txt
- name: Run LLaMA 7B on 4 GPUs
run: CUDA=1 python3 examples/llama.py --gen 1 --size 7B --shard 4 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_four_gpu.txt
- name: Run LLaMA 7B on 6 GPUs
run: CUDA=1 python3 examples/llama.py --gen 1 --size 7B --shard 6 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_six_gpu.txt
# - name: Run LLaMA-2 70B
# run: CUDA=1 python3 examples/llama.py --gen 2 --size 70B --shard 6 --prompt "Hello." --count 10 --temperature 0 --timing | tee llama_2_70B.txt
# - name: Run Mixtral 8x7B
# run: time CUDA=1 python3 examples/mixtral.py --temperature 0 --count 10 --timing | tee mixtral.txt
- name: Run GPT2
run: |
CUDA=1 JIT=0 python3 examples/gpt2.py --prompt "Hello." --count 10 --temperature 0 --timing | tee gpt2_unjitted.txt
Expand All @@ -144,16 +158,6 @@ jobs:
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 JIT_BATCH_SIZE=4 python3 examples/gpt2.py --count 10 --temperature 0 --timing | tee gpt2_half_beam.txt
- name: Train MNIST
run: time PYTHONPATH=. CUDA=1 TARGET_EVAL_ACC_PCT=97.3 python3 examples/beautiful_mnist.py | tee beautiful_mnist.txt
- name: Run 10 CIFAR training steps
run: CUDA=1 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar.txt
- name: Run 10 CIFAR training steps w HALF
run: CUDA=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: CUDA=1 STEPS=10 DEFAULT_FLOAT=BFLOAT16 python3 examples/hlb_cifar10.py | tee train_cifar_bf16.txt
- name: Run full CIFAR training
run: time CUDA=1 DEFAULT_FLOAT=HALF 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
with:
name: Speed (NVIDIA)
Expand All @@ -164,21 +168,75 @@ jobs:
matmul_bfloat16.txt
matmul_ptx.txt
matmul_nv.txt
sd.txt
llama_unjitted.txt
llama_jitted.txt
llama_beam.txt
llama_four_gpu.txt
llama_six_gpu.txt
# llama_2_70B.txt
# mixtral.txt
gpt2_unjitted.txt
gpt2_jitted.txt
gpt2_half.txt
gpt2_half_beam.txt
testmorenvidiabenchmark:
name: tinybox green Training Benchmark
runs-on: [self-hosted, Linux, tinyboxgreen]
defaults:
run:
shell: bash -o pipefail {0}
if: github.repository_owner == 'tinygrad'
env:
PYTHONPATH: .
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: Train MNIST
run: time PYTHONPATH=. CUDA=1 TARGET_EVAL_ACC_PCT=97.3 python3 examples/beautiful_mnist.py | tee beautiful_mnist.txt
- name: Run 10 CIFAR training steps
run: CUDA=1 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar.txt
- name: Run 10 CIFAR training steps w HALF
run: CUDA=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: CUDA=1 STEPS=10 DEFAULT_FLOAT=BFLOAT16 python3 examples/hlb_cifar10.py | tee train_cifar_bf16.txt
- name: Run full CIFAR training w 1 GPU
run: time CUDA=1 DEFAULT_FLOAT=HALF LATEWINO=1 STEPS=1000 TARGET_EVAL_ACC_PCT=93.3 python3 examples/hlb_cifar10.py | tee train_cifar_one_gpu.txt
- name: Run full CIFAR training steps w 6 GPUS
run: time CUDA=1 DEFAULT_FLOAT=HALF STEPS=350 BS=1536 GPUS=6 TARGET_EVAL_ACC_PCT=93.3 python3 examples/hlb_cifar10.py | tee train_cifar_six_gpu.txt
- name: Run MLPerf resnet eval on training data
run: time CUDA=1 MODEL=resnet python3 examples/mlperf/model_eval.py
- name: Run 10 MLPerf ResNet50 training steps (1 gpu)
run: CUDA=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: CUDA=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 (NVIDIA 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
testamdbenchmark:
name: tinybox Benchmark
name: tinybox red Benchmark
runs-on: [self-hosted, Linux, tinybox]
defaults:
run:
Expand Down Expand Up @@ -260,7 +318,7 @@ jobs:
mixtral.txt
testmoreamdbenchmark:
name: tinybox Training
name: tinybox red Training Benchmark
runs-on: [self-hosted, Linux, tinybox]
defaults:
run:
Expand Down

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