chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,63 @@
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#include <limits>
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#include <vector>
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#include "path/sssp_dijkstra.cuh"
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#include "common.h"
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namespace gpu_easygraph {
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using std::vector;
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static int decide_warp_size(
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_IN_ int len_V,
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_IN_ int len_E
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)
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{
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vector<int> warp_size_cand{1, 2, 4, 8, 16, 32};
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if (len_E / len_V < warp_size_cand.front()) {
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return warp_size_cand.front();
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}
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for (int i = 0; i + 1 < warp_size_cand.size(); ++i) {
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if (warp_size_cand[i] <= len_E / len_V
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&& len_E / len_V < warp_size_cand[i + 1]) {
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return warp_size_cand[i + 1];
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}
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}
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return warp_size_cand.back();
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}
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int sssp_dijkstra(
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_IN_ const vector<int>& V,
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_IN_ const vector<int>& E,
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_IN_ const vector<double>& W,
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_IN_ const vector<int>& sources,
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_IN_ int target,
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_OUT_ vector<double>& res
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)
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{
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int len_V = V.size() - 1;
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int len_E = E.size();
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int warp_size = decide_warp_size(len_V, len_E);
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res = vector<double>(sources.size() * V.size());
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int r = cuda_sssp_dijkstra(V.data(), E.data(), W.data(),
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sources.data(), len_V, len_E, sources.size(),
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target, warp_size, res.data());
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double double_inf = std::numeric_limits<double>::infinity();
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for (int i = 0; i < res.size(); ++i) {
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if (res[i] >= EG_DOUBLE_INF) {
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res[i] = double_inf;
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}
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}
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return r;
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}
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} // namespace gpu_easygraph
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@@ -0,0 +1,233 @@
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#include <cuda.h>
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#include <cuda_runtime.h>
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#include <stdlib.h>
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#include "common.h"
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namespace gpu_easygraph {
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static __device__ double atomicMinDouble (
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_OUT_ double *address,
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_IN_ double val
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)
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{
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unsigned long long ret = __double_as_longlong(*address);
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while (val < __longlong_as_double(ret))
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{
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unsigned long long old = ret;
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if ((ret = atomicCAS((unsigned long long *)address, old, __double_as_longlong(val))) == old)
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break;
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}
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return __longlong_as_double(ret);
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}
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static __global__ void d_calc_min_edge (
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_IN_ int* d_V,
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_IN_ int* d_E,
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_IN_ double* d_W,
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_IN_ int len_V,
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_IN_ int len_E,
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_OUT_ double* d_min_edge
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)
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{
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int tid = blockIdx.x * blockDim.x + threadIdx.x;
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int tnum = blockDim.x * gridDim.x;
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for (int u = tid; u < len_V; u += tnum) {
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double curr_min = EG_DOUBLE_INF;
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int edge_start = d_V[u];
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int edge_end = d_V[u + 1];
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for(int v = edge_start; v < edge_end; ++v) {
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curr_min = min(curr_min, d_W[v]);
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}
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d_min_edge[u] = curr_min;
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}
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}
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static __global__ void d_sssp_dijkstra (
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_IN_ int* d_curr_node,
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_IN_ int* d_V,
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_IN_ int* d_E,
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_IN_ double* d_W,
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_IN_ double* d_min_edge,
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_IN_ int* d_sources,
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_OUT_ double* d_dist_2D,
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_BUFFER_ int* d_U_2D,
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_BUFFER_ int* d_F_2D,
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_IN_ int len_V,
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_IN_ int len_E,
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_IN_ int len_sources,
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_IN_ int target,
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_IN_ int warp_size
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)
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{
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while (1) {
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__shared__ int curr_node;
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if (threadIdx.x == 0) {
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curr_node = atomicAdd(d_curr_node, 1);
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}
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__syncthreads();
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if (curr_node >= len_sources) {
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break;
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}
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int s = d_sources[curr_node];
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double* d_dist = d_dist_2D + curr_node * len_V;
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int* d_U = d_U_2D + blockIdx.x * len_V;
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int* d_F = d_F_2D + blockIdx.x * len_V;
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__shared__ int len_F;
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__shared__ double delta;
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__shared__ int target_cnt;
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for (int i = threadIdx.x; i < len_V; i += blockDim.x) {
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d_U[i] = 1;
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d_dist[i] = EG_DOUBLE_INF;
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}
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__syncthreads();
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if (threadIdx.x == 0) {
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d_dist[s] = 0.0;
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d_F[0] = s;
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len_F = 1;
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delta = 0.0;
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target_cnt = 0;
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}
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__syncthreads();
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while (delta < EG_DOUBLE_INF && target_cnt == 0) {
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for (int j = threadIdx.x; j < len_F * warp_size; j += blockDim.x) {
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int f = d_F[j / warp_size];
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int edge_start = d_V[f];
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int edge_end = d_V[f + 1];
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double dist = d_dist[f];
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for (int e = j % warp_size; e < edge_end - edge_start; e += warp_size) {
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int adj = d_E[e + edge_start];
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double relax_w = dist + d_W[e + edge_start];
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atomicMinDouble(d_dist + adj, relax_w);
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}
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__threadfence_block();
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}
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__syncthreads();
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if (threadIdx.x == 0) {
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delta = EG_DOUBLE_INF;
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}
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__syncthreads();
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for (int i = threadIdx.x; i < len_V; i += blockDim.x) {
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double dist_i = d_dist[i];
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if (d_U[i] == 1 && dist_i < EG_DOUBLE_INF) {
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atomicMinDouble(&delta, dist_i + d_min_edge[i]);
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}
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}
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__syncthreads();
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if (threadIdx.x == 0) {
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len_F = 0;
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}
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__syncthreads();
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for (int i = threadIdx.x; i < len_V; i += blockDim.x) {
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double dist_i = d_dist[i];
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if (d_U[i] && dist_i <= delta && dist_i < EG_DOUBLE_INF) {
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d_U[i] = 0;
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int f_idx = atomicAdd(&len_F, 1);
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d_F[f_idx] = i;
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target_cnt += i == target;
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}
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}
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__syncthreads();
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}
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__syncthreads();
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}
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}
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// we here use CSR to represent a graph
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int cuda_sssp_dijkstra(
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_IN_ const int* V,
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_IN_ const int* E,
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_IN_ const double* W,
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_IN_ const int* sources,
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_IN_ int len_V,
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_IN_ int len_E,
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_IN_ int len_sources,
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_IN_ int target,
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_IN_ int warp_size,
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_OUT_ double* res
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)
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{
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int cuda_ret = cudaSuccess;
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int EG_ret = EG_GPU_SUCC;
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int min_edge_block_size;
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int min_edge_grid_size;
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int dijkstra_block_size;
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int dijkstra_grid_size;
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cudaOccupancyMaxPotentialBlockSize(&min_edge_grid_size, &min_edge_block_size, d_calc_min_edge, 0, 0);
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cudaOccupancyMaxPotentialBlockSize(&dijkstra_grid_size, &dijkstra_block_size, d_sssp_dijkstra, 0, 0);
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int *d_curr_node = NULL;
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int *d_V = NULL, *d_E = NULL, *d_sources= NULL;
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int *d_U_2D = NULL, *d_F_2D = NULL;
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double *d_W = NULL, *d_min_edge = NULL, *d_dist_2D = NULL;
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EXIT_IF_CUDA_FAILED(cudaMalloc((void**)&d_curr_node, sizeof(int)));
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EXIT_IF_CUDA_FAILED(cudaMalloc((void**)&d_V, sizeof(int) * (len_V + 1)));
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EXIT_IF_CUDA_FAILED(cudaMalloc((void**)&d_E, sizeof(int) * len_E));
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EXIT_IF_CUDA_FAILED(cudaMalloc((void**)&d_sources, sizeof(int) * len_sources));
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EXIT_IF_CUDA_FAILED(cudaMalloc((void**)&d_U_2D, sizeof(int) * dijkstra_grid_size * len_V));
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EXIT_IF_CUDA_FAILED(cudaMalloc((void**)&d_F_2D, sizeof(int) * dijkstra_grid_size * len_V));
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EXIT_IF_CUDA_FAILED(cudaMalloc((void**)&d_W, sizeof(double) * len_E));
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EXIT_IF_CUDA_FAILED(cudaMalloc((void**)&d_min_edge, sizeof(double) * len_V));
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EXIT_IF_CUDA_FAILED(cudaMalloc((void**)&d_dist_2D, sizeof(double) * len_sources * len_V));
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EXIT_IF_CUDA_FAILED(cudaMemset(d_curr_node, 0, sizeof(int)));
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EXIT_IF_CUDA_FAILED(cudaMemcpy(d_V, V, sizeof(int) * (len_V + 1), cudaMemcpyHostToDevice));
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EXIT_IF_CUDA_FAILED(cudaMemcpy(d_E, E, sizeof(int) * len_E, cudaMemcpyHostToDevice));
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EXIT_IF_CUDA_FAILED(cudaMemcpy(d_sources, sources, sizeof(int) * len_sources, cudaMemcpyHostToDevice));
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EXIT_IF_CUDA_FAILED(cudaMemcpy(d_W, W, sizeof(double) * len_E, cudaMemcpyHostToDevice));
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d_calc_min_edge<<<dijkstra_grid_size, dijkstra_block_size>>>(d_V, d_E, d_W, len_V, len_E, d_min_edge);
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d_sssp_dijkstra<<<min_edge_grid_size, min_edge_block_size>>>(d_curr_node ,d_V, d_E, d_W, d_min_edge, d_sources,
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d_dist_2D, d_U_2D, d_F_2D, len_V, len_E, len_sources, target, warp_size);
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EXIT_IF_CUDA_FAILED(cudaMemcpy(res, d_dist_2D, sizeof(double) * len_sources * len_V, cudaMemcpyDeviceToHost));
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exit:
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cudaFree(d_curr_node);
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cudaFree(d_V);
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cudaFree(d_E);
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cudaFree(d_sources);
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cudaFree(d_U_2D);
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cudaFree(d_F_2D);
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cudaFree(d_W);
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cudaFree(d_min_edge);
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cudaFree(d_dist_2D);
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if (cuda_ret != cudaSuccess) {
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switch (cuda_ret) {
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case cudaErrorMemoryAllocation:
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EG_ret = EG_GPU_FAILED_TO_ALLOCATE_DEVICE_MEM;
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break;
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default:
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EG_ret = EG_GPU_DEVICE_ERR;
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break;
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}
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}
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return EG_ret;
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}
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} // namespace gpu_easygraph
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@@ -0,0 +1,20 @@
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#pragma once
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#include "common.h"
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namespace gpu_easygraph {
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int cuda_sssp_dijkstra(
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_IN_ const int* V,
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_IN_ const int* E,
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_IN_ const double* W,
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_IN_ const int* sources,
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_IN_ int len_V,
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_IN_ int len_E,
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_IN_ int len_sources,
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_IN_ int target,
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_IN_ int warp_size,
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_OUT_ double* res
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);
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} // namespace gpu_easygraph
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