Optimal footprint symbiosis in shared cache
Department of Computer Science; Center for Scalable Architectures and Systems
On multicore processors, applications are run sharing the cache. This paper presents online optimization to collocate applications to minimize cache interference to maximize performance. The paper formulates the optimization problem and solution, presents a new sampling technique for locality analysis and evaluates it in an exhaustive test of 12,870 cases. For locality analysis, previous sampling was two orders of magnitude faster than full-trace analysis. The new sampling reduces the cost by another two orders of magnitude. The best prior work improves co-run performance by 56% on average. The new optimization improves it by another 29%. When sampling and optimization are combined, the paper shows that it takes less than 0.1 second analysis per program to obtain a co-run that is within 1.5% of the best possible performance.
2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
Optimal footprint symbiosis in shared cache.
2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/1160