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46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
import sys
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import cuda.nvbench as nvbench
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import cupy as cp
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def as_cp_ExternalStream(
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cs: nvbench.CudaStream, dev_id: int = -1
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) -> cp.cuda.ExternalStream:
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h = cs.addressof()
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return cp.cuda.ExternalStream(h, dev_id)
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def cupy_extract_by_mask(state: nvbench.State):
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n_cols = state.getInt64("numCols")
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n_rows = state.getInt64("numRows")
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dev_id = state.getDevice()
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cp_s = as_cp_ExternalStream(state.getStream(), dev_id)
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state.collectCUPTIMetrics()
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state.addElementCount(n_rows * n_cols, "# Elements")
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state.addGlobalMemoryReads(
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n_rows * n_cols * (cp.dtype(cp.int32).itemsize + cp.dtype("?").itemsize)
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)
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state.addGlobalMemoryWrites(n_rows * n_cols * (cp.dtype(cp.int32).itemsize))
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with cp_s:
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X = cp.full((n_cols, n_rows), fill_value=3, dtype=cp.int32)
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mask = cp.ones((n_cols, n_rows), dtype="?")
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_ = X[mask]
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def launcher(launch: nvbench.Launch):
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with as_cp_ExternalStream(launch.getStream(), dev_id):
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_ = X[mask]
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state.exec(launcher, sync=True)
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if __name__ == "__main__":
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b = nvbench.register(cupy_extract_by_mask)
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b.addInt64Axis("numCols", [1024, 2048, 4096, 2 * 4096])
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b.addInt64Axis("numRows", [1024, 2048, 4096, 2 * 4096])
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nvbench.run_all_benchmarks(sys.argv)
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