On Tuesday, 10 January 2012 at 14:14:41 UTC, Manu wrote:
Just thought I might share a real-life case study today. Been a
lot of talk
of SIMD stuff, some people might be interested.
Working on an android product today, I noticed the matrix
library was
burning a ridiculous amount of our frame time.
The disassembly looked like pretty normal ARM float code, so
rewriting a
couple of the key routines to use the VFPU (carefully), our key
device
moved from 19fps -> 34fps (limited at 30, we can now ship).
GalaxyS 2 is now running at 170fps, and devices we previously
considered
un-viable can now actually get a release! .. Most devices saw
around 25-45%
speed improvement.
Imagine if all vector code throughout was using the vector
hardware nicely,
and not just one or 2 key functions...
Getting the API right (intuitively encouraging proper usage and
disallowing
inefficient operations), it'll make a big difference!
Wow, impressive difference.
In the future, how will [your idea of] D's SIMD vector libraries
effect my math libraries? Will I simply replace:
struct Vector4(T) {
T x, y, z, w;
}
with something like:
struct Vector4(T) {
__vector(T[4]) values;
}
or will std.simd automatically provide a full range of vector
operations (normalize, dot, cross, etc) like mono.simd? I can't
help but hope for the latter, even if it does make my current
efforts redundant, it would defiantly be a benefit to future D
pioneers.
