Assessing Saiph, a task-based DSL for high-performance computational fluid dynamics

Abstract

Scientific applications face the challenge of efficiently exploiting increasingly complex parallel and distributed systems. Developing hand-tuned codes is a time-consuming, tedious and hardly reusable task. Reaching high performance appears detrimental to productivity and portability and unreasonable to expect from scientists. Domain-Specific Languages (DSLs) are collaborative environments aiming to overcome such difficulties by decoupling the problem description from the algorithmic implementation. However, developing a competitive tool in High-Performance Computing (HPC) is challenging: DSLs for HPC environments have two additional critical requirements, performance and scalability. Moreover, documented and successful cases are few, making it difficult to popularise DSLs as problem-solving environments for scientific HPC code development. In this context, Saiph is a task-based DSL easing the simulation of physical phenomena from Computational Fluid Dynamics (CFD), developed to meet HPC productivity and performance requirements. This work reports the tuning and evaluation of Saiph using the Taylor–Green Vortex (TGV) problem as a case study. We assess Saiph’s productivity, numerical methods, and high-performance strategies to illustrate its use and demonstrate its competitiveness, viability and benefits for CFD software developments in HPC environments. Hence, we contribute to the popularisation of HPC DSLs as suitable problem-solving environments able to unify modern computational and scientific knowledge.