Equipping Sparse Solvers for Exascale

Abstract

The ESSEX project is funded by the German DFG priority programme 1648 Software for Exascale Computing (SPPEXA). In 2016 it has entered its second funding phase, ESSEX-II. ESSEX investigated programming concepts and numerical algorithms for scalable, efficient and robust iterative sparse matrix applications on exascale systems. Starting with successful blueprints and prototype solutions identified in ESSEX-I, the second phase project ESSEX-II developed a collection of broadly usable and scalable sparse eigenvalue solvers with high hardware efficiency for the computer architectures to come. Project activities were organized along the traditional software layers of low-level parallel building blocks (kernels), algorithm implementations, and applications. The classic abstraction boundaries separating these layers were broken in ESSEX by strongly integrating objectives: scalability, numerical reliability, fault tolerance, and holistic performance and power engineering. The basic building block library supports an elaborate MPI+X approach that is able to fully exploit hardware heterogeneity while exposing functional parallelism and data parallelism to all other software layers in a flexible way. In addition, facilities for fully asynchronous checkpointing, silent data corruption detection and correction, performance assessment, performance model validation, and energy measurements are provided transparently.