Add example for benchmarking CuPy function

python/examples/cupy_extract.py

@@ -0,0 +1,45 @@
+import sys
+
+import cuda.nvbench as nvbench
+import cupy as cp
+
+
+def as_cp_ExternalStream(
+    cs: nvbench.CudaStream, dev_id: int = -1
+) -> cp.cuda.ExternalStream:
+    h = cs.addressof()
+    return cp.cuda.ExternalStream(h, dev_id)
+
+
+def cupy_extract_by_mask(state: nvbench.State):
+    n_cols = state.getInt64("numCols")
+    n_rows = state.getInt64("numRows")
+
+    dev_id = state.getDevice()
+    cp_s = as_cp_ExternalStream(state.getStream(), dev_id)
+
+    state.collectCUPTIMetrics()
+    state.addElementCount(n_rows * n_cols, "# Elements")
+    state.addGlobalMemoryReads(
+        n_rows * n_cols * (cp.dtype(cp.int32).itemsize + cp.dtype("?").itemsize)
+    )
+    state.addGlobalMemoryWrites(n_rows * n_cols * (cp.dtype(cp.int32).itemsize))
+
+    with cp_s:
+        X = cp.full((n_cols, n_rows), fill_value=3, dtype=cp.int32)
+        mask = cp.ones((n_cols, n_rows), dtype="?")
+        _ = X[mask]
+
+    def launcher(launch: nvbench.Launch):
+        with as_cp_ExternalStream(launch.getStream(), dev_id):
+            _ = X[mask]
+
+    state.exec(launcher, sync=True)
+
+
+if __name__ == "__main__":
+    b = nvbench.register(cupy_extract_by_mask)
+    b.addInt64Axis("numCols", [1024, 2048, 4096, 2 * 4096])
+    b.addInt64Axis("numRows", [1024, 2048, 4096, 2 * 4096])
+
+    nvbench.run_all_benchmarks(sys.argv)