Optimal Symbiosis and Fair Scheduling in Shared Cache.

On multi-core processors, applications are run sharing the cache. This paper presents optimization theory to co-locate applications to minimize cache interference and maximize performance. The theory precisely specifies MRC-based composition, optimization, and correctness conditions. The paper also presents a new technique called footprint symbiosis to obtain the best shared cache performance under fair CPU allocation as well as a new sampling technique which reduces the cost of locality analysis. 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 percent of the best possible performance. In an exhaustive evaluation with 12,870 tests, the best prior work improves co-run performance by 56 percent on average. The new optimization improves it by another 29 percent. Without single co-run test, footprint symbiosis is able to choose co-run choices that are just 8 percent slower than the best co-run solutions found with exhaustive testing.