CUDA atomicAdd()与long long int

Question

CUDA atomicAdd()与long long int

4

每当我尝试使用atomicAdd与除(*int, int)之外的任何内容一起使用时，都会出现以下错误：

error: no instance of overloaded function "atomicAdd" matches the argument list

但是我需要使用比int更大的数据类型。这里有什么解决办法吗？

设备查询：

/usr/local/cuda/samples/1_Utilities/deviceQuery/deviceQuery Starting...

 CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "GeForce GTX 680"
  CUDA Driver Version / Runtime Version          5.0 / 5.0
  CUDA Capability Major/Minor version number:    3.0
  Total amount of global memory:                 4095 MBytes (4294246400 bytes)
  ( 8) Multiprocessors x (192) CUDA Cores/MP:    1536 CUDA Cores
  GPU Clock rate:                                1084 MHz (1.08 GHz)
  Memory Clock rate:                             3004 Mhz
  Memory Bus Width:                              256-bit
  L2 Cache Size:                                 524288 bytes
  Max Texture Dimension Size (x,y,z)             1D=(65536), 2D=(65536,65536), 3D=(4096,4096,4096)
  Max Layered Texture Size (dim) x layers        1D=(16384) x 2048, 2D=(16384,16384) x 2048
  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
  Maximum sizes of each dimension of a block:    1024 x 1024 x 64
  Maximum sizes of each dimension of a grid:     2147483647 x 65535 x 65535
  Maximum memory pitch:                          2147483647 bytes
  Texture alignment:                             512 bytes
  Concurrent copy and kernel execution:          Yes with 1 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
  Device supports Unified Addressing (UVA):      Yes
  Device PCI Bus ID / PCI location ID:           1 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 5.0, CUDA Runtime Version = 5.0, NumDevs = 1, Device0 = GeForce GTX 680

- user1743798

3

你能够使用unsigned long long int吗？或者必须使用long long int？如果你可以使用无符号版本，它应该能够正常工作。如果你必须使用有符号的64位版本，你可以创建一个变种，参考文档中提供的示例，使用atomicCAS进行任意原子访问。如果需要帮助，请回复并说明，我可以给你一个例子。 - Robert Crovella

1个回答

网页内容由stack overflow 提供, 点击上面的

可以查看英文原文，
原文链接

- Clark Kent · Accepted Answer

我的猜测是编译标志有误。如果您正在寻找除int之外的任何内容，则应使用sm_12或更高版本。

正如Robert Crovella所述，支持unsigned long long int变量，但不支持long long int。

使用以下代码：初学者CUDA-简单的var增量不起作用

#include <iostream>

using namespace std;

__global__ void inc(unsigned long long int *foo) {
  atomicAdd(foo, 1);
}

int main() {
  unsigned long long int count = 0, *cuda_count;
  cudaMalloc((void**)&cuda_count, sizeof(unsigned long long int));
  cudaMemcpy(cuda_count, &count, sizeof(unsigned long long int), cudaMemcpyHostToDevice);
  cout << "count: " << count << '\n';
  inc <<< 100, 25 >>> (cuda_count);
  cudaMemcpy(&count, cuda_count, sizeof(unsigned long long int), cudaMemcpyDeviceToHost);
  cudaFree(cuda_count);
  cout << "count: " << count << '\n';
  return 0;
}

从Linux编译：nvcc -gencode arch=compute_12,code=sm_12 -o add add.cu

结果：

count: 0
count: 2500