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Update benchmarks.yml
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.github/workflows/benchmarks.yml

Lines changed: 43 additions & 49 deletions
Original file line numberDiff line numberDiff line change
@@ -33,17 +33,11 @@ jobs:
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with:
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repository: juliagmt-google/xla
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path: xla
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- name: Create results directory
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working-directory: xla
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run: mkdir -p results
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- name: Install Kaggle API client
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run: pip install kaggle
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# - name: Get GPU spec
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# working-directory: xla
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# continue-on-error: true
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# run: nvidia-smi
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- name: Get GPU spec
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working-directory: xla
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continue-on-error: true
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run: nvidia-smi
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- name: Configure XLA
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working-directory: xla
@@ -65,63 +59,63 @@ jobs:
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with:
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halt-dispatch-input: ${{ inputs.halt-for-connection }}
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- name: Build hlo_runner_main
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working-directory: xla
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run: bazel build -c opt --config=cuda --dynamic_mode=off //xla/tools/multihost_hlo_runner:hlo_runner_main
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# - name: Build hlo_runner_main
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# working-directory: xla
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# run: bazel build -c opt --config=cuda --dynamic_mode=off //xla/tools/multihost_hlo_runner:hlo_runner_main
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# - name: Wait For Connection
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# uses: google-ml-infra/actions/ci_connection@main
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# with:
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# halt-dispatch-input: ${{ inputs.halt-for-connection }}
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- name: Create gpu_hlo_backend.hlo
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working-directory: xla
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run: |
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cat << EOF > gpu_hlo_backend.hlo
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HloModule module
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// CHECK: is_scheduled=true
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# - name: Create gpu_hlo_backend.hlo
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# working-directory: xla
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# run: |
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# cat << EOF > gpu_hlo_backend.hlo
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# HloModule module
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# // CHECK: is_scheduled=true
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ENTRY computation {
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p = f32[5000,6000]{1,0} parameter(0)
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e = f32[5000,6000]{1,0} sqrt(p)
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c = f32[6000,5000] transpose(p), dimensions={1,0}
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r = f32[300,20,5000] reshape(c)
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ROOT out = (f32[5000,6000], f32[300,20,5000]) tuple(e,r)
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}
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EOF
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# ENTRY computation {
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# p = f32[5000,6000]{1,0} parameter(0)
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# e = f32[5000,6000]{1,0} sqrt(p)
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# c = f32[6000,5000] transpose(p), dimensions={1,0}
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# r = f32[300,20,5000] reshape(c)
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# ROOT out = (f32[5000,6000], f32[300,20,5000]) tuple(e,r)
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# }
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# EOF
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# - name: Wait For Connection
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# uses: google-ml-infra/actions/ci_connection@main
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# with:
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# halt-dispatch-input: ${{ inputs.halt-for-connection }}
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- name: Run an HLO file
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working-directory: xla
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run: |
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nvidia-smi --query-gpu=utilization.gpu --format=csv -l 1 > results/gpu_utilization_gpu_backend.log & ./bazel-bin/xla/tools/multihost_hlo_runner/hlo_runner_main --device_type=gpu --log_output=True --use_spmd_partitioning gpu_hlo_backend.hlo
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# - name: Run an HLO file
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# working-directory: xla
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# run: |
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# nvidia-smi --query-gpu=utilization.gpu --format=csv -l 1 > results/gpu_utilization_gpu_backend.log & ./bazel-bin/xla/tools/multihost_hlo_runner/hlo_runner_main --device_type=gpu --log_output=True --use_spmd_partitioning gpu_hlo_backend.hlo
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cd results
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ls
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cat gpu_hlo_backend.hlo.log
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# cd results
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# ls
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# cat gpu_hlo_backend.hlo.log
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- name: Wait For Connection
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uses: google-ml-infra/actions/ci_connection@main
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with:
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halt-dispatch-input: ${{ inputs.halt-for-connection }}
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# - name: Wait For Connection
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# uses: google-ml-infra/actions/ci_connection@main
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# with:
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# halt-dispatch-input: ${{ inputs.halt-for-connection }}
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- name: Download parse_xla_logs.py
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working-directory: xla
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run: wget https://raw.githubusercontent.com/juliagmt-google/xla/main/.github/workflows/parse_xla_logs.py
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# - name: Download parse_xla_logs.py
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# working-directory: xla
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# run: wget https://raw.githubusercontent.com/juliagmt-google/xla/main/.github/workflows/parse_xla_logs.py
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- name: Parse XLA logs
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working-directory: xla
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run: python parse_xla_logs.py results/gpu_hlo_backend.hlo.log
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# - name: Parse XLA logs
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# working-directory: xla
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# run: python parse_xla_logs.py results/gpu_hlo_backend.hlo.log
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- name: Upload Results
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uses: actions/upload-artifact@v4
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with:
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name: gpu-xla-benchmarks
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path: xla/results
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# - name: Upload Results
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# uses: actions/upload-artifact@v4
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# with:
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# name: gpu-xla-benchmarks
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# path: xla/results
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# # jax-build-and-test:
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# # runs-on: linux-x86-g2-48-l4-4gpu # Use a GPU-enabled runner
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# # container:

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