使用GPU计算稀疏数据 [英] Computation on sparse data using GPU

问题描述

我正在Matlab中计算函数 f ( x )= exp(- x )，其中 x 是标量的向量.该函数是在GPU上计算得出的，例如

I'm computing a function f(x) = exp(-x) in Matlab, where x is a vector of scalars. The function is computed on GPU, e.g.

x_cpu = [4 5 11 1];
x = gpuArray(x_cpu);
f = exp(-x);

那么结果将是:

f = exp(-[4，5，11，1])= [0.183，0.0067，1.6702e-005，0.3679].

f = exp(-[4, 5, 11, 1]) = [0.183, 0.0067, 1.6702e-005, 0.3679].

请注意， f ( x (3))= f (11)= exp(-11)= 1.6702e-005 = 0.000016702，这是一个很小的值.因此，我想避免通过简单地设置 f ( x (i))=来计算所有 x (i)> 10的函数0.

Note that f(x(3)) = f(11) = exp(-11) = 1.6702e-005 = 0.000016702, which is a pretty small value. So, I would like to avoid computing the function for all x(i) > 10 by simply setting f(x(i)) = 0.

我可能可以将稀疏矩阵表示用于 x .但是，并行计算工具箱不支持对GPU上的稀疏矩阵进行操作.

I can probably use the sparse matrix representation for x. However, the Parallel Computing Toolbox does not support operations on sparse matrices on GPU.

您将如何处理?

推荐答案

尽管并行计算工具箱不支持GPU上的稀疏矩阵运算，但Jacket却支持.因此，一种可能的方法是简单地使用其他工具.

While the Parallel Computing Toolbox does not support sparse matrix operations on the GPU, Jacket does. So one possible approach is to simply use the different tool.

免责声明是我从事Jacket的工作，但我确实认为这对您有好处，因为它支持您想做的事情而PCT不做，并且支持

Disclaimer is that I work on Jacket, but I really do think it would be beneficial to you on this since it supports the things you want to do and that PCT does not do, and for reasons here.

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