PyCUDA October 2019

pycuda@tiker.net

3 participants
2 discussions

GPUArray class gives negative "s" with large size gpuarray

by takayanagi.tetsuya＠jp.panasonic.com

Hi, All. I have developed Lattice Boltzmann Method Code with PyCUDA in our company for simulating Air flow. Then, I need to handle large gpuarray such like arr[velocity][Z][Y][X] for 3-dimensional fluid flow. My code run correctly relatively small size gpuarray such as (27, 300, 300, 300). But Changing gpuarray size from (27, 300, 300, 300) to (27, 450, 450, 450) gives following error. Error message OverflowError : can't convert negative int to unsigned For debugging it, I'm testing following simple code, which also arise error if I designate large size numpy array such like (27, 450, 450, 450). // // sample code start // import math import numpy as np import pycuda.gpuarray as gpuarray from pycuda.compiler import SourceModule import pycuda.autoinit module = SourceModule(""" __global__ void plus_one_3d(int nx, int ny, int nz, int nv, float *arr){ const int x = threadIdx.x + blockDim.x * blockIdx.x; const int y = threadIdx.y + blockDim.y * blockIdx.y; const int z = threadIdx.z + blockDim.z * blockIdx.z; const int nxyz = nx * ny * z + nx * y + x; int ijk = nx * ny * z + nx * y + x; if (x < nx && y < ny && z < nz){ for (int c = 0; c < nv; c++){ arr[nxyz * c + ijk] += 1.0; } } } """) plus_one = module.get_function("plus_one_3d") num_x, num_y, num_z = np.int32(450), np.int32(450), np.int32(450) nv = np.int32(27) arr_gpu = gpuarray.zeros([nv, num_z, num_y, num_x], dtype=np.float32) threads_per_block = (6, 6, 6) block_x = math.ceil(num_x / threads_per_block[0]) block_y = math.ceil(num_y / threads_per_block[1]) block_z = math.ceil(num_z / threads_per_block[2]) blocks_per_grid = (block_x, block_y, block_z) plus_one(num_x, num_y, num_z, nv, arr_gpu, block=threads_per_block, grid=blocks_per_grid) arr = arr_gpu.get() print("result :", arr) // // sample code end // Debugging with pycharm leads variables "s" become negative of GPUArray class when I designate shape (27, 450, 450, 450) as a gpuarray. But s is calculated correctly when I designate shape (27, 300, 300, 300). I think data type of s is something wrong. Any advise ? Besh wishes, t-tetsuya

1 year, 7 months

How to free page-locked memory?

by Rengan Xu

Hi All, In PyCUDA, what is the API to free the allocated page-locked memory? In CUDA, we have cudaFreeHost(void* ptr) to free the page-locked memory, but I didn't find the corresponding API in PyCUDA. Any help would be appreciated. Regards, Rengan

1 year, 7 months

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PyCUDA October 2019