EigenSparseProduct

Made it multi-threading: C = A * B, where A is an Eigen::ColMajor sparsematrix and B is an Eigen::RowMajor sparsematrix.
实现了Eigen::ColMajor稀疏矩阵乘Eigen::RowMajor稀疏矩阵的多线程乘法。

Benckmark

Here we made 2 test cases:

• A is 471538*941014, B is 941014*471538, with 0.00127% nonzero values.
• A is 235771*235771, B is 235771*235771, with 0.00296% nonzero values.

The machine has an Intel Core-i7 6700K CPU @ 4.38GHz, with 16GiB 2400MHz DDR4 memory (single channel) on Windows 10.0.17134.407. We made the product of each case continuously for 4 times, and logged the total time consumed as following.

Method	Case	1st	2nd	3rd	4th
Eigen's	1	1141ms	1176ms	1162ms	1162ms
Ours	1	345ms	298ms	313ms	298ms
Eigen's	2	471ms	479ms	476ms	475ms
Ours	2	140ms	115ms	121ms	120ms

This method turns out to perform a little worse for the 1st product due to memory allocation, but it becomes faster for the following. The overall speed-up ratio is 3.30 ~ 4.16 on this 4 cored machine, according to the table.