PsmArena: Partitioned shared memory for NUMA-awareness in multithreaded scientific applications

Abstract

The Distributed Shared Memory (DSM) architecture is widely used in today's computer design to mitigate the ever-widening processing-memory gap, and it inevitably exhibits Non-Uniform Memory Access (NUMA) to shared-memory parallel applications. Failure to adapt to the NUMA effect can significantly downgrade application performance, especially on today's manycore platforms with tens to hundreds of cores. However, traditional approaches such as first-touch and memory policy fall short in false page-sharing, fragmentation, or ease of use. In this paper, we propose a partitioned shared-memory approach that allows multithreaded applications to achieve full NUMA-awareness with only minor code changes and develop an accompanying NUMA-aware heap manager which eliminates false page-sharing and minimizes fragmentation. Experiments on a 256-core cc-NUMA computing node show that the proposed approach helps applications to adapt to NUMA with only minor code changes and improves the performance of typical multithreaded scientific applications by up to 4.3 folds with the increased use of cores.

Optimizing Data Parallelism for FM-Based Short-Read Alignment on the Heterogeneous Non-Uniform Memory Access Architectures

“…Sequencing alignment is a collaborative research type in which heterogeneous architectures have been widely used. NUMA has emerged as one of the most widely utilized computing infrastructures [18]. Research focusing on sequence alignments as a trade-off between data locality and data dispersion in the systems based on NUMA highlights an interesting research topic on NUMA-based heterogeneous architecture [16].…”