Machine learning techniques are applicable to computer system optimization. We show that shared memory multiprocessors can successfully utilize machine learning algorithms for mem...
M. F. Sakr, Steven P. Levitan, Donald M. Chiarulli...
Improving memory performance at software level is more effective in reducing the rapidly expanding gap between processor and memory performance. Loop transformations (e.g. loop un...
Surendra Byna, Xian-He Sun, William Gropp, Rajeev ...
Abstract—Sharing patterns in shared-memory multiprocessors are the key to performance: uniprocessor latencytolerating techniques such as out-of-order execution and non-blocking c...
Prior research indicates that there is much spatial variation in applications' memory access patterns. Modern memory systems, however, use small fixed-size cache blocks and a...
Stephen Somogyi, Thomas F. Wenisch, Anastassia Ail...
Chip Multiprocessor (CMP) memory systems suffer from the effects of destructive thread interference. This interference reduces performance predictability because it depends heavil...