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Use cuda.Stream.from_handle to create core.Stream from nvbench.CudaStream

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Oleksandr Pavlyk
2025-07-02 15:09:12 -05:00
parent b357af0092
commit 883e5819b6
4 changed files with 34 additions and 49 deletions
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12
python/examples/auto_throughput.py
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@@ -63,13 +63,9 @@ def throughput_bench(state: nvbench.State):
state.exec(launcher)
(
nvbench.register(throughput_bench)
.addInt64Axis("Stride", [1, 4])
.addInt64Axis("ItemsPerThread", [1, 2, 3, 4])
)
if __name__ == "__main__":
print(nvbench.__version__)
b = nvbench.register(throughput_bench)
b.addInt64Axis("Stride", [1, 2, 4])
b.addInt64Axis("ItemsPerThread", [1, 2, 3, 4])
nvbench.run_all_benchmarks(sys.argv)