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https://github.com/NVIDIA/cuda-samples.git
synced 2026-10-25 22:28:17 +08:00
Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks.
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@@ -38,8 +38,8 @@
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*
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*/
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#include <stdio.h>
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#include <cooperative_groups.h>
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#include <stdio.h>
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using namespace cooperative_groups;
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@@ -49,35 +49,36 @@ using namespace cooperative_groups;
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* calculates the sum of val across the group g. The workspace array, x,
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* must be large enough to contain g.size() integers.
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*/
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__device__ int sumReduction(thread_group g, int *x, int val) {
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// rank of this thread in the group
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int lane = g.thread_rank();
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__device__ int sumReduction(thread_group g, int *x, int val)
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{
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// rank of this thread in the group
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int lane = g.thread_rank();
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// for each iteration of this loop, the number of threads active in the
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// reduction, i, is halved, and each active thread (with index [lane])
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// performs a single summation of it's own value with that
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// of a "partner" (with index [lane+i]).
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for (int i = g.size() / 2; i > 0; i /= 2) {
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// store value for this thread in temporary array
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x[lane] = val;
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// for each iteration of this loop, the number of threads active in the
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// reduction, i, is halved, and each active thread (with index [lane])
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// performs a single summation of it's own value with that
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// of a "partner" (with index [lane+i]).
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for (int i = g.size() / 2; i > 0; i /= 2) {
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// store value for this thread in temporary array
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x[lane] = val;
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// synchronize all threads in group
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g.sync();
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// synchronize all threads in group
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g.sync();
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if (lane < i)
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// active threads perform summation of their value with
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// their partner's value
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val += x[lane + i];
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if (lane < i)
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// active threads perform summation of their value with
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// their partner's value
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val += x[lane + i];
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// synchronize all threads in group
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g.sync();
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}
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// synchronize all threads in group
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g.sync();
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}
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// master thread in group returns result, and others return -1.
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if (g.thread_rank() == 0)
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return val;
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else
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return -1;
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// master thread in group returns result, and others return -1.
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if (g.thread_rank() == 0)
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return val;
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else
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return -1;
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}
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/**
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@@ -85,93 +86,92 @@ __device__ int sumReduction(thread_group g, int *x, int val) {
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*
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* Creates cooperative groups and performs reductions
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*/
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__global__ void cgkernel() {
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// threadBlockGroup includes all threads in the block
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thread_block threadBlockGroup = this_thread_block();
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int threadBlockGroupSize = threadBlockGroup.size();
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__global__ void cgkernel()
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{
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// threadBlockGroup includes all threads in the block
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thread_block threadBlockGroup = this_thread_block();
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int threadBlockGroupSize = threadBlockGroup.size();
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// workspace array in shared memory required for reduction
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extern __shared__ int workspace[];
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// workspace array in shared memory required for reduction
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extern __shared__ int workspace[];
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int input, output, expectedOutput;
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int input, output, expectedOutput;
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// input to reduction, for each thread, is its' rank in the group
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input = threadBlockGroup.thread_rank();
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// input to reduction, for each thread, is its' rank in the group
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input = threadBlockGroup.thread_rank();
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// expected output from analytical formula (n-1)(n)/2
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// (noting that indexing starts at 0 rather than 1)
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expectedOutput = (threadBlockGroupSize - 1) * threadBlockGroupSize / 2;
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// expected output from analytical formula (n-1)(n)/2
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// (noting that indexing starts at 0 rather than 1)
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expectedOutput = (threadBlockGroupSize - 1) * threadBlockGroupSize / 2;
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// perform reduction
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output = sumReduction(threadBlockGroup, workspace, input);
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// perform reduction
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output = sumReduction(threadBlockGroup, workspace, input);
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// master thread in group prints out result
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if (threadBlockGroup.thread_rank() == 0) {
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printf(
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" Sum of all ranks 0..%d in threadBlockGroup is %d (expected %d)\n\n",
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(int)threadBlockGroup.size() - 1, output, expectedOutput);
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// master thread in group prints out result
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if (threadBlockGroup.thread_rank() == 0) {
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printf(" Sum of all ranks 0..%d in threadBlockGroup is %d (expected %d)\n\n",
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(int)threadBlockGroup.size() - 1,
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output,
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expectedOutput);
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printf(" Now creating %d groups, each of size 16 threads:\n\n",
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(int)threadBlockGroup.size() / 16);
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}
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printf(" Now creating %d groups, each of size 16 threads:\n\n", (int)threadBlockGroup.size() / 16);
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}
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threadBlockGroup.sync();
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threadBlockGroup.sync();
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// each tiledPartition16 group includes 16 threads
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thread_block_tile<16> tiledPartition16 =
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tiled_partition<16>(threadBlockGroup);
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// each tiledPartition16 group includes 16 threads
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thread_block_tile<16> tiledPartition16 = tiled_partition<16>(threadBlockGroup);
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// This offset allows each group to have its own unique area in the workspace
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// array
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int workspaceOffset =
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threadBlockGroup.thread_rank() - tiledPartition16.thread_rank();
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// This offset allows each group to have its own unique area in the workspace
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// array
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int workspaceOffset = threadBlockGroup.thread_rank() - tiledPartition16.thread_rank();
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// input to reduction, for each thread, is its' rank in the group
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input = tiledPartition16.thread_rank();
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// input to reduction, for each thread, is its' rank in the group
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input = tiledPartition16.thread_rank();
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// expected output from analytical formula (n-1)(n)/2
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// (noting that indexing starts at 0 rather than 1)
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expectedOutput = 15 * 16 / 2;
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// expected output from analytical formula (n-1)(n)/2
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// (noting that indexing starts at 0 rather than 1)
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expectedOutput = 15 * 16 / 2;
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// Perform reduction
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output = sumReduction(tiledPartition16, workspace + workspaceOffset, input);
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// Perform reduction
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output = sumReduction(tiledPartition16, workspace + workspaceOffset, input);
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// each master thread prints out result
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if (tiledPartition16.thread_rank() == 0)
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printf(
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" Sum of all ranks 0..15 in this tiledPartition16 group is %d "
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"(expected %d)\n",
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output, expectedOutput);
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// each master thread prints out result
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if (tiledPartition16.thread_rank() == 0)
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printf(" Sum of all ranks 0..15 in this tiledPartition16 group is %d "
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"(expected %d)\n",
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output,
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expectedOutput);
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return;
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return;
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}
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/**
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* Host main routine
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*/
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int main() {
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// Error code to check return values for CUDA calls
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cudaError_t err;
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int main()
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{
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// Error code to check return values for CUDA calls
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cudaError_t err;
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// Launch the kernel
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// Launch the kernel
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int blocksPerGrid = 1;
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int threadsPerBlock = 64;
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int blocksPerGrid = 1;
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int threadsPerBlock = 64;
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printf("\nLaunching a single block with %d threads...\n\n", threadsPerBlock);
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printf("\nLaunching a single block with %d threads...\n\n", threadsPerBlock);
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// we use the optional third argument to specify the size
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// of shared memory required in the kernel
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cgkernel<<<blocksPerGrid, threadsPerBlock, threadsPerBlock * sizeof(int)>>>();
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err = cudaDeviceSynchronize();
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// we use the optional third argument to specify the size
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// of shared memory required in the kernel
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cgkernel<<<blocksPerGrid, threadsPerBlock, threadsPerBlock * sizeof(int)>>>();
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err = cudaDeviceSynchronize();
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if (err != cudaSuccess) {
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fprintf(stderr, "Failed to launch kernel (error code %s)!\n",
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cudaGetErrorString(err));
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exit(EXIT_FAILURE);
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}
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if (err != cudaSuccess) {
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fprintf(stderr, "Failed to launch kernel (error code %s)!\n", cudaGetErrorString(err));
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exit(EXIT_FAILURE);
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}
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printf("\n...Done.\n\n");
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printf("\n...Done.\n\n");
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return 0;
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return 0;
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}
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