4 ms·
They are optimized for that because a lot of algorithms can make use of them, from quicksort/mergesort through image rendering and encryption. It is an easy opt
by daveguy 10y ago
They are optimized for that because a lot of algorithms can make use of them, from quicksort/mergesort through image rendering and encryption. It is an easy optimization from a hardware perspective -- simple repetitive hardware structure. This is why GPUs are so powerful and games are not the only thing that benefits from this type of optimization. Matrix multiplication is also used in signal processing. The CEO asked, how can we optimize the use of our hardware for the most benefit? And SIMD with wide pipes is at the top of the list. Most of the post is about all the new algorithms that can take advantage of the hardware push. The hardware push is there because it is an easy use of hardware resources.
This is also an optimization that compilers can readily take advantage of on a small scale (similar to pipelining) so the combination of benefit + ability to use + simplicity/low resource use makes it an inevitability.
- mcguire 10y agoA sort that uses vectorized floating point multiplication?
- sbierwagen 10y agoFrom 2008: http://www.vldb.org/pvldb/1/1454171.pdf http://www.vldb.org/pvldb/1/1454171.pdf Also: http://researcher.watson.ibm.com/researcher/files/jp-INOUEHRS/PACT2007-SIMDsort.pdf http://researcher.watson.ibm.com/researcher/files/jp-INOUEHR... and https://github.com/NumScale/boost.simd https://github.com/NumScale/boost.simd