我的OpenCL内核出现问题:
#pragma OPENCL EXTENSION cl_khr_fp64 : enable
struct complex {
double im;
double re;
double r;
double phi;
};
struct complex createComplexFromPolar(double _r, double _phi){
struct complex t;
t.r = _r;
t.phi = _phi;
t.re = cos(t.phi);
t.im = sin(t.phi);
return t;
}
struct complex createComplexFromKarthes(double real, double imag){
struct complex t;
t.re = real;
t.im = imag;
t.phi = atan(imag / real);
t.r = sqrt(pow(real, 2) + pow(imag, 2));
return t;
}
struct complex recreateComplexFromKarthes(struct complex t){
return t = createComplexFromKarthes(t.re, t.im);
}
struct complex recreateComplexFromPolar(struct complex t){
return t = createComplexFromPolar(t.r, t.phi);
}
struct complex addComplex(const struct complex z, const struct complex c){
struct complex t;
t.re = c.re + z.re;
t.im = c.im + z.re;
return recreateComplexFromKarthes(t);
}
struct complex subComplex(const struct complex z, const struct complex c){
struct complex t;
t.re = z.re - c.re;
t.im = z.im - c.im;
return recreateComplexFromKarthes(t);
}
struct complex addComplexScalar(const struct complex z, const double n){
struct complex t;
t.re = z.re + n;
return recreateComplexFromKarthes(t);
}
struct complex subComplexScalar(const struct complex z, const double n){
struct complex t;
t.re = z.re - n;
return recreateComplexFromKarthes(t);
}
struct complex multComplexScalar(const struct complex z, const double n) {
struct complex t;
t.re = z.re * n;
t.im = z.im * n;
return recreateComplexFromKarthes(t);
}
struct complex multComplex(const struct complex z, const struct complex c) {
struct complex t;
t.re = z.re*c.re - z.im*c.re;
t.im = z.re*c.im + z.im*c.re;
return recreateComplexFromKarthes(t);
}
struct complex divComplex(const struct complex z, const struct complex c) {
return createComplexFromPolar(z.r / c.r, z.phi - c.phi);
}
__kernel void newtonFraktal(__global const int* res, __global const double* param, __global int* result){
const int x = get_global_id(0);
const int y = get_global_id(1);
const int xRes = res[0];
const int yRes = res[1];
struct complex z = createComplexFromKarthes(x - (xRes / 2), y - (yRes / 2));
struct complex c = createComplexFromKarthes(param[0], param[1]);
int i = 0;
while (z.r < 500){
if (i >= 10000)
break;
z = subComplex(z, divComplex(addComplex(addComplex(multComplex(multComplex(z,z),c),multComplex(z,c)),c),addComplex(multComplexScalar(multComplex(z,c),2),c)));
//z-(c*z*z + c*z + c) / ((c*z) * 2 + c);
i++;
}
result[x + res[0]*y] = i;
}
该内核的目的是为牛顿分形创建图像数据。
问题是当param[0]
和param[1]
相差超过3(这会导致clFinish(-36)
)或者它们变得太大时会导致崩溃(这会导致clEnqueueReadBuffer(-36)
)。
当我将此代码作为C ++代码运行时,每个参数都完全没问题 - 我知道运行时环境之间存在很大差异。
我在nVidia GeForce GTX 770
上运行内核,主机在AMD FX-8350
上运行。
我希望你们有一个提示,告诉我如何解决这个问题。我想有没有一步一步的OpenV Debugger for nVidia?
提前感谢您的帮助,
- fodinabor
param[0] = 3;
和param[1] = 1;
多次表现很好 - 但是atm。我无法运行它..
所以我想这与我的主人有关..我在下面发布了它。这个问题可能来自一个太大的全球工作规模吗?我的显卡应该可以使用1024*1024*64
来保留640*480
..所以通常它应该有用吗?我尝试用一半尺寸运行它 - &gt; 2轮,它总是在第二轮崩溃 - 如果这有帮助..
NewtonFraktalCLGeneration::NewtonFraktalCLGeneration(cl_double* param){
FILE* f;
if (fopen_s(&f, "newton.cl", "r") != 0){
return;
}
char* buf = (char*)malloc(100 * sizeof(char));
char* temp = buf;
int recv_size = 0, total_recv = 0;
int i = 1;
while ((recv_size = fread_s(temp, sizeof(char) * 100, sizeof(char), 100, f)) > 0){
total_recv += recv_size;
buf = (char*)realloc(buf, total_recv + 100 * sizeof(char));
temp = buf + total_recv;
}
buf[total_recv] = '\0';
err = CL_SUCCESS;
try {
cl::vector<cl::Platform> platforms;
cl::Platform::get(&platforms);
cl_context_properties properties[] =
{ CL_CONTEXT_PLATFORM, (cl_context_properties)(platforms[0])(), 0 };
cl::Context context(CL_DEVICE_TYPE_GPU, properties);
cl::vector<cl::Device> devices = context.getInfo<CL_CONTEXT_DEVICES>();
cl::Program::Sources source(1, std::make_pair(buf,strlen(buf)));
cl::Program program_ = cl::Program(context, source);
program_.build(devices);
cl::Kernel kernel(program_, "newtonFraktal", &err);
int *res = new int[2];
res[0] = Services()->getCore()->getXRes(), res[1] = Services()->getCore()->getYRes();
cl::Buffer resBuf(context, CL_MEM_READ_ONLY, 2 * sizeof(int));
cl::Buffer paramBuf(context, CL_MEM_READ_ONLY, 2 * sizeof(cl_double));
result = (cl_int*)calloc(res[0] * res[1], sizeof(cl_int) + 1);
cl::Buffer outBuf(context, CL_MEM_WRITE_ONLY | CL_MEM_USE_HOST_PTR, res[0] * res[1] * sizeof(cl_int) + 1, result);
cl::CommandQueue queue(context, devices[0], 0, &err);
cl::Event event;
queue.enqueueWriteBuffer(resBuf, CL_TRUE, 0, 2 * sizeof(int), res);
queue.enqueueWriteBuffer(paramBuf, CL_TRUE, 0, 2 * sizeof(double), param);
kernel.setArg(0, resBuf);
kernel.setArg(1, paramBuf);
kernel.setArg(2, outBuf);
queue.enqueueNDRangeKernel(
kernel,
cl::NullRange,
cl::NDRange(res[0], res[1]),
cl::NullRange,
NULL,
&event);
queue.finish();
queue.enqueueReadBuffer(outBuf, CL_TRUE, 0, res[0] * res[1] * sizeof(cl_int) + 1, result);
}
catch (cl::Error& err) {
std::cerr
<< "ERROR: "
<< err.what()
<< "("
<< err.err()
<< ")"
<< std::endl;
this->err = err.err();
}
}
答案 0 :(得分:0)
好的 - 所以现在我真的遇到了问题(我希望:D):
我的内核在显卡上执行,显示器连接到它...并且执行时间超过5秒。 - &GT; TDR(具有Windows驱动程序安全性的东西)重置驱动程序 - &gt;内核执行被杀了所以现在我将注册表中的TDRDelay设置为更高的值,并且将来可能会使用另一个图形卡:D
这对我来说有点烦人..但最后我解决了..所以感谢所有这些帮助我解决其他问题的人。
如果有人在此处再次提出此问题,请说明如何增加TDRDelay(不应该用于生产系统;-)):
打开注册表编辑器(例如,通过Win Key
+ R
并在窗口中编写regedit
并执行)浏览到HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\GraphicsDrivers
并创建一个名为TdrDelay
的新条目您可以选择的值(它间接地是内核的最大执行时间),以秒为单位(我将其设置为10秒)。现在重新启动系统并享受未阻止的OpenCL / CUDA内核:D