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Hi,

I have a new 'strange' behavior of a OpenCL kernel using the Xeon Phi.

In this case, I have a small example written in HPL that executes perfectly in CPU, GPU but not in XEON PHI.

I've attached the example in a .cpp file. You can download HPL library to test it or you can reproduce it with OpenCL (If you need the OpenCL code, please ask me). The problem is in the following loop:

inline Double ipow(Double aa, Int a, Int b) { Double q, qaux; Int n, n2; Int two_pow = 0; q = aa; n = a; while_(two_pow < 100) { n2 = n / 2; if_(n2 * 2 == n) { qaux = 1.5*q; q = qaux; n = n2; } else_ { n = n * b; two_pow = 200; } //////// UNCOMMENT THIS LINE AND THE PROBLEM WILL BE SOLVED :( // two_pow++; } return(q); }

As I wrote above, if you uncomment the line (superfluous line) the code executes perfectly in the three (Intel CPU, NVIDIA GPU, and XEON PHI) platforms but the line is commented, the code fails in the XEON PHI case. The global and local work spaces are {1,1,1}.

Why it fails for PHI case? Thank you so much

Moisés Viñas

http://gac.udc.es/~moises/index_en.html

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Hi Yuri,

Yes, the public version is outdated :-/ But the problem will be solved if you change the following files in /src subfolder for these ones: CLbinding.cpp, Device.h and Device.cpp

The results for a* = 1.5^7 x 3 for i!=0. For i = 0 is an aleatory number. However, for XEON PHI, the value is 1.5 x 3 Why?*

Thanks in advance,

Moisés Viñas

http://gac.udc.es/~moises/index_en.html

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Yuri, my Xeon Phi acts strange with a simple convolution kernel. I believe the results it shows are incorrect. Is there a known problem with opencl support for phi?

For kernel enqueue:

global size set to 1024x1024

local size set to NULL.

Thanks

//KERNEL_SIMPLE

__kernel void Convolve(const __global float * pInput,

__constant float * pFilter,

__global float * pOutput,

const int nInWidth,

const int nFilterWidth)

{

const int nWidth = get_global_size(0);

const int xOut = get_global_id(0);

const int yOut = get_global_id(1);

const int xInTopLeft = xOut;

const int yInTopLeft = yOut;

float sum = 0;

for (int r = 0; r < nFilterWidth; r++)

{

const int idxFtmp = r * nFilterWidth;

const int yIn = yInTopLeft + r;

const int idxIntmp = yIn * nInWidth + xInTopLeft;

for (int c = 0; c < nFilterWidth; c++)

{

const int idxF = idxFtmp + c;

const int idxIn = idxIntmp + c;

sum += pFilter[idxF]*pInput[idxIn];

}

}

const int idxOut = yOut * nWidth + xOut;

pOutput[idxOut] = sum;

}

//KERNEL_SIMPLE

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