CODEWITHSUNDEEP
juliagpubenchmarkingjulia-gpu
user888379
user888379

Reputation: 1467

Julia benchmarking DSP.jl, CUDANative and CuArrays

I'm experimenting with DSP.jl - the conv() method, in particular. I'm using CUDANative and CuArrays to create arrays to be arguments to conv(), so that the cuda versions of fft(), etc. will be used. I'm using BenchmarkTools to get performance data. I find that the Julia runtime complains about running out of CPU or GPU memory under odd circumstances. Here's my test setup:

using CUDAdrv, CUDAnative, CuArrays
using DSP
using FFTW
using BenchmarkTools

N = 120
A = rand(Float32, N, N, N);
B = rand(Float32, N, N, N);
A_d = cu(A);
B_d = cu(B);

function doConv(A, B)
    C = conv(A, B)
    finalize(C)
    C = []
end

t = @benchmark doConv($A_d, $B_d)
display(t)

Here's an example of the odd behavior I mentioned. If I set N to 120, my script runs to completion. If I set N to 64, I get the "out of memory" error:ERROR: LoadError: CUFFTError(code 2, cuFFT failed to allocate GPU or CPU memory). I can run the smaller case first, get the error, then bump N to the larger value and have the script complete successfully.

Is there something I should be doing differently to prevent this from happening?

Upvotes: 3

Views: 287

Answers (0)

Related Questions