Software Autotuning for Sustainable Performance Portability

TL;DR

This paper presents an autotuning approach for scientific software that enhances performance and portability across diverse hardware platforms without sacrificing code modularity or correctness.

Contribution

It introduces an automated autotuning method that optimizes performance on various hardware while maintaining software modularity and correctness.

Findings

Achieves significant performance improvements on heterogeneous hardware.

Enables performance portability without modifying core software modules.

Maintains software correctness and modularity during autotuning.

Abstract

Scientific software applications are increasingly developed by large interdiscplinary teams operating on functional modules organized around a common software framework, which is capable of integrating new functional capabilities without modifying the core of the framework. In such environment, software correctness and modularity take precedence at the expense of code performance, which is an important concern during execution on supercomputing facilities, where the allocation of core-hours is a valuable resource. To alleviate the performance problems, we propose automated performance tuning (autotuning) of software to extract the maximum performance on a given hardware platform and to enable performance portability across heterogeneous hardware platforms. The resulting code remains generic without committing to a particular software stack and yet is compile-time specializable for maximal sustained performance.