Use a CUDA Thread Index as a number - c++

Question

I am new to CUDA and GPGPUs. I am trying to check properties of a large set of numbers (bigger than 32 bit) and I would like to try to do this using my Windows 7 64bit machine equipped with a nVidia GTX 1080:
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 1080"
CUDA Driver Version / Runtime Version 8.0 / 8.0
CUDA Capability Major/Minor version number: 6.1
Total amount of global memory: 8192 MBytes (8589934592 bytes)
(20) Multiprocessors, (128) CUDA Cores/MP: 2560 CUDA Cores
GPU Max Clock rate: 1734 MHz (1.73 GHz)
Memory Clock rate: 5005 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 2097152 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 2 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
CUDA Device Driver Mode (TCC or WDDM): WDDM (Windows Display Driver Model)
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 1 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
When I run the following code the value for "sum" is nonsensical (28, 20, etc.) even though I can see the threadId goes from 0 to 4095 :
#include <cuda.h>
#include <cuda_runtime.h>
#include "device_launch_parameters.h"
#include "stdio.h"
__global__ void Simple(unsigned long long int *sum)
{
unsigned long long int blockId = blockIdx.x + blockIdx.y * gridDim.x + gridDim.x * gridDim.y * blockIdx.z;
unsigned long long int threadId = blockId * (blockDim.x * blockDim.y * blockDim.z)
+ (threadIdx.z * (blockDim.x * blockDim.y))
+ (threadIdx.y * blockDim.x)
+ threadIdx.x;
printf("threadId = %llu.\n", threadId);
// Check threadId for property. Possibly introduce a grid stride for loop to give each thread a range to check.
sum[0]++;
}
int main(int argc, char **argv)
{
unsigned long long int sum[] = { 0 };
unsigned long long int *dev_sum;
cudaMalloc((void**)&dev_sum, sizeof(unsigned long long int));
cudaMemcpy(dev_sum, sum, sizeof(unsigned long long int), cudaMemcpyHostToDevice);
dim3 grid(2, 1, 1);
dim3 block(1024, 1, 1);
printf("--------- Start kernel ---------\n\n");
Simple <<< grid, block >>> (dev_sum);
cudaDeviceSynchronize();
cudaMemcpy(sum, dev_sum, sizeof(unsigned long long int), cudaMemcpyDeviceToHost);
printf("sum = %llu.\n", sum[0]);
cudaFree(dev_sum);
getchar();
return 0;
}
How would I modify this kernel call to get the maximum threads to operate (with my setup ) over a range of numbers say 0 to 10^12 by adding a grid stride loop?
dim3 grid(2, 1, 1);
dim3 block(1024, 1, 1);
Simple <<< grid, block >>> (dev_sum);

Answer 1

All threads are doing increment on the same place in memory, which results in race condition. That is why the outcome is incorrect. You should use atomic addition to have it right (there is a function for that in CUDA).