In measuring the runtime of two kernels I fail to understand why the kernel I expect to be slower (because of block-level synchronization and two extra conditional checks) is actually faster. I’ve only observed this behaviour when using NVIDIA Tesla k20m, the runtime behaves as expected when using a Titan XP. Nevertheless, I’m curious as to why this is so.
Compile and run with an argument that specifies the number of iterations the kernel should perform. In my case, I noticed the difference with 100,000 iterations. Version 1 completes in approximately 453 Seconds while Version 2 completes in approximately 422 Seconds.
I’m using cuda 9.0 and compiling with nvcc filename.cu, no additional flags.
Version 1:
#include <stdio.h>
#include <stdlib.h>
__global__
void kernel(unsigned long *res, unsigned long n)
{
int x = 0;
for(int i = 0; i < n; i++)
{
x++;
}
*res = x;
}
int main(int argc, char *argv[])
{
if(argc != 2)
{
fprintf(stderr, "Invalid arguments.\nUsage: %s <iterations>\n", argv[0]);
exit(EXIT_FAILURE);
}
unsigned long n = strtol(argv[1], NULL, 10);
unsigned long h_res;
unsigned long *d_res;
cudaMalloc((void **)&d_res, sizeof(unsigned long));
kernel<<<2097152, 1024>>>(d_res, n);
cudaMemcpy(&h_res, d_res, sizeof(unsigned long), cudaMemcpyDeviceToHost);
fprintf(stdout, "Result(%lu) = %lu\n", n, h_res);
cudaFree(d_res);
return EXIT_SUCCESS;
}
Version 2
#include <stdio.h>
#include <stdlib.h>
__global__
void kernel(volatile unsigned int *t, unsigned long *res, unsigned long n)
{
__shared__ unsigned int test;
if(threadIdx.x == 0 && threadIdx.y == 0 && threadIdx.z == 0)
{
test = *t;
}
__syncthreads();
if(test == 1)
{
return;
}
int x = 0;
for(int i = 0; i < n; i++)
{
x++;
}
*res = x;
}
int main(int argc, char *argv[])
{
if(argc != 2)
{
fprintf(stderr, "Invalid arguments.\nUsage: %s <iterations>\n", argv[0]);
exit(EXIT_FAILURE);
}
unsigned long n = strtol(argv[1], NULL, 10);
unsigned long h_res;
unsigned long *d_res;
volatile unsigned int *t;
cudaMalloc((void **)&d_res, sizeof(unsigned long));
cudaHostAlloc((void **)&t, sizeof(volatile unsigned int), cudaHostAllocMapped);
*t = 0;
kernel<<<2097152, 1024>>>(t, d_res, n);
cudaMemcpy(&h_res, d_res, sizeof(unsigned long), cudaMemcpyDeviceToHost);
fprintf(stdout, "Result(%lu) = %lu\n", n, h_res);
cudaFree((void *)d_res);
cudaFreeHost((void *)t);
return EXIT_SUCCESS;
}
Output of Device Query:
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "Tesla K20m"
CUDA Driver Version / Runtime Version 9.0 / 9.0
CUDA Capability Major/Minor version number: 3.5
Total amount of global memory: 4743 MBytes (4972937216 bytes)
(13) Multiprocessors, (192) CUDA Cores/MP: 2496 CUDA Cores
GPU Max Clock rate: 706 MHz (0.71 GHz)
Memory Clock rate: 2600 Mhz
Memory Bus Width: 320-bit
L2 Cache Size: 1310720 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 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: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 4 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 9.0, CUDA Runtime Version = 9.0, NumDevs = 1, Device0 = Tesla K20m
Result = PASS