Question

我有一块内核源代码可以在我的PC上运行在G970上但是在我2015年初的MacBook pro上使用Iris 6100 1536MB图形进行编译。

platform = cl.get_platforms()[0]
device   = platform.get_devices()[1] # Get the GPU ID
ctx      = cl.Context([device])      # Tell CL to use GPU
queue    = cl.CommandQueue(ctx)      # Create a command queue for the target device.
# program  = cl.Program(ctx, kernelsource).build()
print platform.get_devices()

这个get_devices（）显示我有＆＃39;英特尔（R）Core（TM）i5-5287U CPU @ 2.90GHz＆＃39;在＆＃39; Apple＆＃39;在0xffffffff＆gt;，＆＃39;英特尔（R）Iris（TM）图形6100＆＃39;在＆＃39; Apple＆＃39;在0x1024500。

内核将在CPU上正常运行。但是当我在GPU上构建程序时。它返回：

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-44-e2b6e1b931de> in <module>()
      3 ctx      = cl.Context([device])      # Tell CL to use GPU
      4 queue    = cl.CommandQueue(ctx)      # Create a command queue for the target device.
----> 5 program  = cl.Program(ctx, kernelsource).build()
      6 
      7 

/usr/local/lib/python2.7/site-packages/pyopencl-2015.2.4-py2.7-macosx-10.11-x86_64.egg/pyopencl/__init__.pyc in build(self, options, devices, cache_dir)
    393                         self._context, self._source, options, devices,
    394                         cache_dir=cache_dir),
--> 395                     options=options, source=self._source)
    396 
    397             del self._context

/usr/local/lib/python2.7/site-packages/pyopencl-2015.2.4-py2.7-macosx-10.11-x86_64.egg/pyopencl/__init__.pyc in _build_and_catch_errors(self, build_func, options, source)
    428         # Python 3.2 outputs the whole list of currently active exceptions
    429         # This serves to remove one (redundant) level from that nesting.
--> 430         raise err
    431 
    432     # }}}

RuntimeError: clbuildprogram failed: BUILD_PROGRAM_FAILURE - 

Build on <pyopencl.Device 'Intel(R) Iris(TM) Graphics 6100' on 'Apple' at 0x1024500>:

Cannot select: 0x7f94b30a5110: i64,ch = dynamic_stackalloc 0x7f94b152a290, 0x7f94b30a4f10, 0x7f94b3092c10 [ORD=7] [ID=54]
  0x7f94b30a4f10: i64 = and 0x7f94b30a4c10, 0x7f94b3092b10 [ORD=7] [ID=52]
    0x7f94b30a4c10: i64 = add 0x7f94b30a6610, 0x7f94b3092a10 [ORD=7] [ID=49]
      0x7f94b30a6610: i64 = shl 0x7f94b3092d10, 0x7f94b3092e10 [ID=46]
        0x7f94b3092d10: i64 = bitcast 0x7f94b30a4810 [ID=41]
          0x7f94b30a4810: v2i32 = IGILISD::MOVSWZ 0x7f94b3092710, 0x7f94b30a2810, 0x7f94b30a2810, 0x7f94b30a2810 [ID=32]
            0x7f94b3092710: i32,ch = CopyFromReg 0x7f94b152a290, 0x7f94b3092610 [ORD=5] [ID=22]
              0x7f94b3092610: i32 = Register %vreg60 [ORD=5] [ID=1]
            0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
            0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
            0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
        0x7f94b3092e10: i64 = bitcast 0x7f94b30a3f10 [ID=38]
          0x7f94b30a3f10: v2i32 = IGILISD::MOVSWZ 0x7f94b30a4510, 0x7f94b30a2810, 0x7f94b30a2810, 0x7f94b30a2810 [ID=29]
            0x7f94b30a4510: i32 = Constant<2> [ID=19]
            0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
            0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
            0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
      0x7f94b3092a10: i64 = bitcast 0x7f94b30a4b10 [ID=40]
        0x7f94b30a4b10: v2i32 = IGILISD::MOVSWZ 0x7f94b30a4e10, 0x7f94b30a2810, 0x7f94b30a2810, 0x7f94b30a2810 [ID=31]
          0x7f94b30a4e10: i32 = Constant<7> [ID=21]
          0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
          0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
          0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
    0x7f94b3092b10: i64 = bitcast 0x7f94b3092910 [ID=39]
      0x7f94b3092910: v2i32 = IGILISD::MOVSWZ 0x7f94b30a5010, 0x7f94b30a4210, 0x7f94b30a2810, 0x7f94b30a2810 [ID=30]
        0x7f94b30a5010: i32 = Constant<-8> [ID=20]
        0x7f94b30a4210: i32 = Constant<-1> [ORD=3] [ID=10]
        0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
        0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
  0x7f94b3092c10: i64 = bitcast 0x7f94b3092810 [ID=35]
    0x7f94b3092810: v2i32 = IGILISD::MOVSWZ 0x7f94b30a2810, 0x7f94b30a2810, 0x7f94b30a2810, 0x7f94b30a2810 [ID=27]
      0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
      0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
      0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
      0x7f94b30a2810: i32 = Constant<0> [ORD=1] [ID=7]
In function: trajectories
(options: -I /usr/local/lib/python2.7/site-packages/pyopencl-2015.2.4-py2.7-macosx-10.11-x86_64.egg/pyopencl/cl)
(source saved as /var/folders/p2/jd7m10gs5k1_q6hx5kvktkcc0000gn/T/tmpWQmCKr.cl)

有什么建议为什么这不会运行？我正在运行2015年初的MacBook Pro，Sierra 10.12.5。 print cl.version.VERSION返回2015.2.4

这是内核代码：

kernelsource = """
__kernel void trajectories(
    // TODO: adjust argtypes above if this is changed
    const int N,
    const int dim,
    __constant float* data,
    const int nrParticles,
    __global float* pos,
    __global float* vel,
    const int nrSteps,
    __global float* trj, 
    __global float* sigarr, 
    const float sigma, 
    const float mass, 
    const float alpha,  // alpha is resistance in reverse. 
    const float dt
){
    int i,k,step;
    float h, sigsum, hexp; 
    int pidx = get_global_id(0); // global ID used as particle index
    int ofs = pidx * nrSteps * dim;
    int accofs = ofs + (nrSteps-1) * dim; // use last trj point to tmp store acc vector
    float v[dim];
    float sigma2 = sigma*sigma;
    float m = mass / sigma2;
    float dt_over_m = dt /m;
    for(step=0; step<nrSteps; step++){
        for(k=0; k<dim; k++)
        {
            trj[accofs+k]=0;
        }  
        for(i=0; i<N; i++)
        {

            h=0;  // to store ||data[i]-x||**2
            for(k=0; k<dim; k++)
            { 
                v[k] = pos[pidx*dim+k] - data[i*dim + k];
                h += v[k]*v[k];     //h == force1p_sum
            };
            hexp = exp(-h/sigma2)/sigma2;

            for(k=0; k<dim; k++)
            { 
                trj[accofs+k] += -(hexp) * v[k]; 
            };         
        };
        sigsum = 0;
        for(k=0; k<dim; k++)
        { 
            vel[pidx*dim+k]     = alpha * vel[pidx*dim+k] + dt_over_m * trj[accofs+k];      // vel = alpha*vel + acc*dt 
            pos[pidx*dim+k]    += dt * vel[pidx*dim+k];                        // pos = pos + vel*dt
            sigsum             += vel[pidx*dim+k] * vel[pidx*dim+k]; // v^2 for kinetic energy
            trj[ofs+step*dim+k] = pos[pidx*dim+k];             // write to result vector

        };
        sigarr[pidx*nrSteps+step] = sigsum;                    // sig = | vel | 
    }
    for(step=0; step<nrSteps-2; step++)
    {
        sigarr[pidx*nrSteps+step] = sigarr[pidx*nrSteps+step+2] - sigarr[pidx*nrSteps+step+1];
    };
    sigarr[pidx*nrSteps+nrSteps-1] = sigarr[pidx*nrSteps+nrSteps-2] = 0;  

}
"""

由于

嘉俊

Answer 1

在这种情况下，您应该尝试查询构建的错误。您可以在类似的内核代码错误中做的另一件事是您可以使用脱机编译器。每个OpenCL实现者都有离线编译器。

您可以在此处找到英特尔的OpenCL离线编译器：https://software.intel.com/en-us/articles/programming-with-the-intel-sdk-for-opencl-applications-development-tools

AMD有一个名为CodeXL的工具，您可以在其中进行离线编译，以查看您的内核代码是否已编译。

以下是ARM OpenCL脱机编译器：https://developer.arm.com/products/software-development-tools/graphics-development-tools/mali-offline-compiler/downloads

英特尔的支持取决于OpenCL 2.1，而ARM则支持1.1。因此，您可以选择其中任何一个来编译内核代码，以便轻松找出错误或错误。

内核中的问题如下：

float v[dim];

OpenCL C规范不允许使用可变长度数组，脱机编译器会出现以下错误：

ERROR: <source>:22:12: error: variable length arrays are not supported in OpenCL

您可以修复该行以克服错误，从现在开始，您可以检查您的内核是否可以使用脱机编译器进行编译。

编辑：在规范中，有一个脚注解释了不支持可变长度数组。你可以在这里看到它：

https://www.khronos.org/registry/OpenCL/specs/opencl-2.0-openclc.pdf#page=31

pyopenCL，openCL，无法在GPU

1 个答案: