NUMA-CIC: Issues and Challenges for Scaling Scientific Applications on a Large Scale ccNuma Prototype

This whitepaper studies the various aspects and challenges of performance scaling on large scale shared memory systems.
Our experiments are performed on a large ccNUMA machine that consists of 72 IBM 3755 nodes connected with
NumaConnect and provides shared memory over a total of 1728 cores, a number that is far beyond conventional server
platforms. As benchmarks, three data-intensive and memory-bound applications with different communication patterns
are selected, namely Jacobi, CSR SpMV and Floyd-Warshall. Our results illustrate the need for numa-aware design and
implementation of shared-memory parallel algorithms in order to achieve scaling to high core counts. At the same time, we
observed that, depending on its communication pattern, an application could bene t more from explicit communication
using message passing.