CUDACast #10a - Your First CUDA Python Program
Why Stack Overflow recommends it
Stack Overflow users link it as a starting point for GPU programming in plain Python with Numba, and as the source of example code they are adapting or debugging.
Recommended by 1 people across 1 different months, 2018 to 2019.
What it is
A short NVIDIA Developer tutorial from the CUDACast series showing how to write and run a first CUDA Python program using the Numba compiler from Continuum Analytics. It walks through a simple vector addition example offloaded to the GPU.
What people said
Recommends Sooraj · 2018-06 · Stack Overflow · on “implementing python code on GPU from spyder”
For parallel processing in python some intermideate libraries or packages needed to be there that sit between the code and the gpu/cpu for parallel executions. Some popular packages are pycuda, numba etc. If you want to do gpu programming using simple python syntax without using other frameworks like tensorflow, then take a look at this [this video] .
Cites FraserOfSmeg · 2018-04 · Stack Overflow · on “CudaAPIError 716 when trying to copy data from gpu”
I'm learning Numba and CUDA Python. I've been following a set of [this video] and have (I believe) understood the principals. My issue is with copying computed values back from my GPU. I use the following line to do this: aVals = retVal.copy_to_host() I've also tried using this line: retVal.copy_to_host( aVals[:] ) Neither work and both give the same error: numba.cuda.cudadrv.driver.CudaAPIError: [716] Call to cuMemcpyDtoH results in UNKNOWN_CUDA_ERROR I'm reasonably confident the above lines are the issue as if I comment out the line the code runs without errors. Is there some underlying issue I'm overlooking with copying an array from GPU to CPU? Have I screwed up my arrays somewhere? There's a
Cites Redhwan · 2019-10 · Stack Overflow · on “Exception: Version mismatch: this is the 'cffi' package version 1.13.1,”
I tried to run the code using CUDA, I got this error, it seems something wrong in the system the full code: I got it CUDACast #10a - Your First CUDA Python Program [this video] and no module named numbapro [LINK] import numpy as np from timeit import default_timer as timer from numba import vectorize @vectorize(["float32(float32, float32)"], target='cuda') def VectorAdd(a, b): return a + b def main(): N = 32000000 A = np.ones(N, dtype=np.float32) B = np.ones(N, dtype=np.float32) C = np.zeros(N, dtype=np.float32) start = timer() C = VectorAdd(A, B) vectoradd_timer = timer() - start print("C[:5] = " + str(C[:5])) print("C[-5:] = " + str(C[-5:])) print("VectorAdd took %f seconds" % vectoradd_timer)