Fastest way to multiply a constant sparse matrix to a vector

General Usage Performance
1

One answer to this question about multiplying a constant sparse matrix to a static vector made me wonder:

Is there a more performant way of multiplying a constant sparse matrix A to a non-static vector x than doing A * x?

(e.g., for a matrix and vector of large sizes, which do not work well with StaticArrays)

2

mul!(y,A,x)

3

But this is just a memory thing, right? Is it different (in speed) to doing y .= A * x?

4

Yes, A*x allocates y and then does mul!. So it’s faster than using *, but only by the amount it takes to allocate y.

5

Then there is the copying from the result of A * x to y, as opposed to filling y directly which mul! does.

6

OK I see thanks!

7

MKL has some new interesting stuff with the Inspector-executor API (Intel | Data Center Solutions, IoT, and PC Innovation). You give an estimate on how many times you will do an operation and it optimizes the operation for the given matrix.

8

Out of curiosity, is there any reason that the compiler doesn’t just read y .= A * x to mean mul!(y,A,x)? Is there some case in which the user doesn’t want the same thing to happen? (For the elements of y to reflect A*x.)