Skip to Main content Skip to Navigation
Conference papers

NumaMMA: NUMA MeMory Analyzer

Abstract : Non Uniform Memory Access (NUMA) architectures are nowadays common for running High-Performance Computing (HPC) applications. In such architectures, several distinct physical memories are assembled to create a single shared memory. Nevertheless, because there are several physical memories, access times to these memories are not uniform depending on the location of the core performing the memory request and on the location of the target memory. Hence, threads and data placement are crucial to efficiently exploit such architectures. To help in taking decision about this placement, profiling tools are needed. In this work, we propose NUMA MeMory Ana-lyzer (NumaMMA), a new profiling tool for understanding the memory access patterns of HPC applications. NumaMMA combines efficient collection of memory traces using hardware mechanisms with original visualization means allowing to see how memory access patterns evolve over time. The information reported by NumaMMA allows to understand the nature of these access patterns inside each object allocated by the application. We show how NumaMMA can help understanding the memory patterns of several HPC applications in order to optimize them and get speedups up to 28% over the standard non optimized version.
Complete list of metadata

Cited literature [31 references]  Display  Hide  Download
Contributor : Lionel Morel Connect in order to contact the contributor
Submitted on : Friday, December 14, 2018 - 4:14:43 PM
Last modification on : Saturday, June 26, 2021 - 3:41:04 AM
Long-term archiving on: : Friday, March 15, 2019 - 5:18:38 PM


Files produced by the author(s)



François Trahay, Manuel Selva, Lionel Morel, Kevin Marquet. NumaMMA: NUMA MeMory Analyzer. ICPP 2018 - 47th International Conference on Parallel Processing, Aug 2018, Eugene, United States. pp.1-10, ⟨10.1145/3225058.3225094⟩. ⟨cea-01854072v2⟩



Record views


Files downloads