/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of NVIDIA CORPORATION nor the names of its * contributors may be used to endorse or promote products derived * from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ /* * This example shows how to use the clock function to measure the performance * of block of threads of a kernel accurately. Blocks are executed in parallel * and out of order. Since there's no synchronization mechanism between blocks, * we measure the clock once for each block. The clock samples are written to * device memory. */ // This kernel computes a standard parallel reduction and evaluates the // time it takes to do that for each block. The timing results are stored // in device memory. extern "C" __global__ void timedReduction(const float *input, float *output, clock_t *timer) { // __shared__ float shared[2 * blockDim.x]; extern __shared__ float shared[]; const int tid = threadIdx.x; const int bid = blockIdx.x; if (tid == 0) timer[bid] = clock(); // Copy input. shared[tid] = input[tid]; shared[tid + blockDim.x] = input[tid + blockDim.x]; // Perform reduction to find minimum. for (int d = blockDim.x; d > 0; d /= 2) { __syncthreads(); if (tid < d) { float f0 = shared[tid]; float f1 = shared[tid + d]; if (f1 < f0) { shared[tid] = f1; } } } // Write result. if (tid == 0) output[bid] = shared[0]; __syncthreads(); if (tid == 0) timer[bid + gridDim.x] = clock(); }