【发布时间】:2017-02-08 10:25:17
【问题描述】:
所以我在 GeForce GT 610 上运行我的 OpenCL 程序。我知道 CUDA 会是一个更好的选择,我以后可能会编写我的代码的 CUDA 版本,但是要知道我在 OpenCL 中编写也是为了能够在 AMD 显卡上运行。
在初始化期间,我选择了一个要运行的设备。这是我的程序在此阶段打印的内容:
OpenCL Platform 0: NVIDIA CUDA
----- OpenCL Device # 0: GeForce GT 610-----
Gflops: 1.620000
Max Compute Units: 1
Max Clock Frequency: 1620
Total Memory of Device (bytes): 1072889856
Max Size of Memory Object Allocation (bytes): 268222464
Max Work Group Size: 1024
我的问题是为什么它说最大计算单元只有 1?根据 GeForce 网站上的规格详细信息,it has 48 CUDA cores。我知道 CUDA 在 Nvidia 卡上运行得更好,但它真的限制了这么多吗? Nvidia 将 OpenCL 限制为 1/48 的功率?
这是我的代码打印如下:
if (clGetPlatformInfo(platforms[platform], CL_PLATFORM_NAME, sizeof(name), name, NULL)) Fatal("Cannot get OpenCL platform name\n");
if (verbose) printf("OpenCL Platform %d: %s\n", platform, name);
...在forloop里面...
cl_uint compUnits, freq;
cl_ulong memSize, maxAlloc;
size_t maxWorkGrps;
if (clGetDeviceInfo(id[devId], CL_DEVICE_MAX_COMPUTE_UNITS, sizeof(compUnits), &compUnits, NULL)) Fatal("Cannot get OpenCL device units\n");
if (clGetDeviceInfo(id[devId], CL_DEVICE_MAX_CLOCK_FREQUENCY, sizeof(freq), &freq, NULL)) Fatal("Cannot get OpenCL device frequency\n");
if (clGetDeviceInfo(id[devId], CL_DEVICE_NAME, sizeof(name), name, NULL)) Fatal("Cannot get OpenCL device name\n");
if (clGetDeviceInfo(id[devId], CL_DEVICE_GLOBAL_MEM_SIZE, sizeof(memSize), &memSize, NULL)) Fatal("Cannot get OpenCL memory size.\n");
if (clGetDeviceInfo(id[devId], CL_DEVICE_MAX_MEM_ALLOC_SIZE, sizeof(memSize), &maxAlloc, NULL)) Fatal("Cannot get OpenCL memory size.\n");
if (clGetDeviceInfo(id[devId], CL_DEVICE_MAX_WORK_GROUP_SIZE, sizeof(maxWorkGrps), &maxWorkGrps, NULL)) Fatal("Cannot get OpenCL max work group size\n");
int Gflops = compUnits * freq;
if (verbose) printf(" ----- OpenCL Device # %d: %s-----\n"
"Gflops: %f\n"
"Max Compute Units: %d\n"
"Max Clock Frequency: %d\n"
"Total Memory of Device (bytes): %lu\n"
"Max Size of Memory Object Allocation (bytes): %lu\n"
"Max Work Group Size: %d\n",
devId,
name,
1e-3*Gflops,
compUnits,
freq,
memSize,
maxAlloc,
maxWorkGrps);
【问题讨论】: