D12.2: Exploration of Scalable Numerical Algorithms

Work Package 12 (WP12) “Novel Programming Techniques” performs research and development in four key areas for future multi-petascale and exascale systems. The work in WP12 focuses on auto tuned and automatic techniques to be applied in parallel programming model runtimes (Task 12.1: “Auto-tuned runtime Environments”), performance tools (Task 12.3: “Development environments and tools”) and file systems (Task 12.4: “File system optimization”). Furthermore, as it is widely accepted that the key to exploiting future high-end systems will be based on research on new numerical algorithms as well as advancing the parallel processing technology used for higher scalability in numerical applications; consequently WP12 also focuses on research studies exposing more scalability for numerical algorithms (Task 12.2: “Scalable numerical algorithms”). The key research topics investigated in Task 12.2 are: Reducing Synchronization Overhead in Iterative Solvers Enhancing Parallel Hybrid Sparse Solvers for Scalability Topology-Awareness Enabling Hybridization in Heterogeneous Architectures Application Scalability Task 12.2 evaluated different algorithms, methods, and approaches and demonstrated the scalability of the algorithms using simple ad-hoc programs. In total 17 complementary areas organized as individual projects were covered. This document is a summary of the projects’ results. It contains high-level summaries of all projects as well as brief description of covered topics. In most of the summaries, links to PRACE white papers or scientific publications are given for those readers that are interested in more detailed information