Reservoir Labs, Inc. — Department of Energy STTR Phase II: The Polyhedral User Mapping Assistant and Visualizer (PUMA-V) project is addressing the ch

Description

The Polyhedral User Mapping Assistant and Visualizer (PUMA-V) project is addressing the challenges of developing optimized computer software for heterogeneous supercomputing systems in support of physics simulations needed for bringing theoretical calculations to the level of the newest precision experiments. Current Lattice Quantum Chromodynamics (LQCD) and Lattice Beyond Standard Model (LBSM) simulations require four orders of magnitude greater computational rates to reach this level. Heterogeneous hardware can provide orders of magnitude improvements in computational rates but presents significantly more complex code development and porting challenges. The project will develop the capability for optimizing LQCD software bases in particular the heavily templated QDP++ data parallel libraries through an interactive control and visualization interface for advanced software optimization technologies. The approach will leverage the polyhedral model for precision of dependence analysis and increased range of optimized mappings. Phase I research and development (1) demonstrated capabilities for recovering high-level array semantics from the templated software base by overloading templates in the QDP++ library (2) developed a visualization and control interface within the Eclipse Interactive Development Environment (IDE) for polyhedral parallelization and optimization. (1) Implementation of translation tools interfacing heavily templated LQCD libraries to polyhedral mapping (2) application of the tools to current theoretical physics simulations related to testing Standard Model (SM) theories (3) development of new optimized solver algorithms for LQCD (4) development and quality improvements. Commercial Applications and Other Benefits: Acceleration of theoretical science in support of Standard Model and Beyond Standard Model theories. Energy and cost savings in high performance computing systems generally. Reduced cost and defects for high performance computing software development through advanced development tools and productivity methodologies. Increased rate of scientific research and innovation.