Ah, that seems likely. I tried pre-allocating a vector for the current slice outside the loop, which I'm filling using an explicit element-by-element copy. Doing this AND using A_mul_B!() brings the performance up to when I was doing the matrix multiply myself.
I guess when the ArrayView stuff is implemented then I wouldn't need to pre-allocate the temporary holding place for the slice. Is there anything in the works so that C[:] = A * B would be equivalent to A_mul_B!(C, A, B)? I'm trying to figure out whether there's something about my use-case here that makes it unusual, as it seems like doing any linear algebra inside of a tight-loop requires you to use the A_mul_B functions. Thanks for the help, John! -s On Sat, Mar 8, 2014 at 4:13 PM, John Myles White <[email protected]>wrote: > That seems right. Is most of the memory allocation happening in y[:, i]? > > -- John > > On Mar 8, 2014, at 4:11 PM, Spencer Russell <[email protected]> wrote: > > Hmm, replacing slope = A * y[:, i] with A_mul_B!(slope, A, y[:, i:i])gave a > very slightly reduced memory allocation and about the same speed. Am > I using it correctly? > > -s > > > On Sat, Mar 8, 2014 at 3:39 PM, John Myles White <[email protected] > > wrote: > >> Looks like A_mul_B! should work for you to avoid memory allocation. >> -- John >> >> >> On Mar 8, 2014, at 3:38 PM, Spencer Russell <[email protected]> wrote: >> >> I'm learning a little numerical ODE stuff, so I whipped up an >> implementation of the Euler algorithm. >> >> It accepts systems of 1st-order equations, and the code was clean and I >> was happy, and all was right in the world. Then I noticed that for small >> step sizes it was allocating a very large amount of memory. It seems that >> the allocation is happening in the matrix math, because when I wrote out >> the matrix multiplication explicitly I got about a 30x speedup and huge >> reduction in memory allocation (50MB instead of 2GB). >> >> This feels like a bit of a nuclear option, and makes what was really nice >> general code into something much uglier. Is there a better solution? >> >> https://gist.github.com/ssfrr/4f5ecfaf462bb5b487db >> >> -s >> >> >> > >
