Selective Data Migration Between Locality Groups in NUMA Systems

Abstract

Non-uniform memory access (NUMA) architectures exhibit variable memory access latencies that depend on the issuing core and the accessed memory location. To minimize an application’s memory access time, the accessed data should be kept as close to the computation as possible. An promising strategy is to deploy groups of threads that access the same data on neighboring cores and close to the accessed data. This not only minimizes remote memory accesses latency but also reduces the amount of accessed cache lines and the traffic incurred by the cache coherence protocol; however, finding and maintaining a good thread group allocation is difficult. This paper presents a novel at-runtime technique that improves application performance through better data locality without prior profiling runs. The presented technique accurately detects accessed memory sections through low-overhead sampling. Sections that are frequently accessed on a remote node are migrated to the local memory node. Migration of unused data such as data streams is avoided by only copying sections that are expected to yield a positive net gain.