MATLAB 中的并行矩阵乘法
有没有一种相对容易实现或透明的方法来在Matlab中并行乘以两个大矩阵？
理想情况下，我想最多用几行代码来执行这种并行乘法，也许是这样的：
C_1 = A*B % normal
C_2 = pmult(A,B) % parallel
% C_1 and C_2 have the same entries
如果有一种方法可以轻松地执行这种并行乘法，有人可以指出我的代码吗？如果没有，有谁知道在 Matlab 中实现并行矩阵乘法算法的最佳方法是什么？
预先感谢很棒的 Stackoverflow 社区。
编辑 - 我相信我遇到的部分问题是稀疏矩阵的矩阵乘法不会自动并行化；它会自动并行化密集矩阵。新问题：Matlab 可以并行进行稀疏矩阵乘法吗？ （CPU 并行化，因为我没有启用 CUDA 的显卡）
Is there a relatively easy to implement or transparent way to multiply two large matrices in Matlab in parallel?
Ideally, I would like to perform this parallel multiplication with at most a few lines of code, perhaps something like:
C_1 = A*B % normal
C_2 = pmult(A,B) % parallel
% C_1 and C_2 have the same entries
If there is a way to easily do this paralell multiplication, can someone please point me to the code? If not, does anyone have any ideas on what they feel is the best way to implement a parallel matrix multiplication algorithm in Matlab?
Thanks in advance, awesome Stackoverflow community.
EDIT --
I believe that part of the issue I was running into is that matrix multiplication for sparse matrices is not automatically parallelized; it is automatically parallelized for dense matrices. New question: can Matlab do sparse matrix multiplication in parallel? (CPU parallelization as I don't have CUDA enabled graphics cards)
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Matlab 可能已经通过其隐式多线程支持做到了这一点。请参阅 http://www.mathworks.com /support/solutions/en/data/1-4PG4AN/?solution=1-4PG4AN; “*”运算符。 Matlab 已经为您完成了简单的可并行操作；只需在多核机器上运行它即可。
Matlab probably already does this via its implicit multithreading support. See http://www.mathworks.com/support/solutions/en/data/1-4PG4AN/?solution=1-4PG4AN; the "*" operator. The trivially parallelizable operations are already done for you by Matlab; just run it on a multicore machine.
你说的并行是什么意思？这两种方法都使用显式并行性，并且都需要并行计算工具箱（第二种也需要功能强大的 GPU）。
选项 1：MPI 并行
选项 2：GPU 并行
What do you mean by parallel? These two approaches use explicit parallelism, and both require Parallel Computing Toolbox (the second also requires a capable GPU).
Option 1: MPI parallelism
Option 2: GPU parallelism