Language Support for Reliable Memory Regions

TL;DR

This paper introduces language support for reliable memory regions, called havens, enabling explicit resilience management in HPC systems to address increasing errors and heterogeneity at exascale.

Contribution

It extends previous haven-based memory management with language annotations, making resilient memory regions more explicit and easier for HPC programmers to use.

Findings

Annotations improve resilience of HPC applications

Implementation demonstrates effective haven management

Enhanced reliability in conjugate gradient solver

Abstract

The path to exascale computational capabilities in high-performance computing (HPC) systems is challenged by the inadequacy of present software technologies to adapt to the rapid evolution of architectures of supercomputing systems. The constraints of power have driven system designs to include increasingly heterogeneous architectures and diverse memory technologies and interfaces. Future systems are also expected to experience an increased rate of errors, such that the applications will no longer be able to assume correct behavior of the underlying machine. To enable the scientific community to succeed in scaling their applications, and to harness the capabilities of exascale systems, we need software strategies that provide mechanisms for explicit management of resilience to errors in the system, in addition to locality of reference in the complex memory hierarchies of future HPC systems. In prior work, we introduced the concept of explicitly reliable memory regions, called havens. Memory management using havens supports reliability management through a region-based approach to memory allocations. Havens enable the creation of robust memory regions, whose resilient behavior is guaranteed by software-based protection schemes. In this paper, we propose language support for havens through type annotations that make the structure of a program's havens more explicit and convenient for HPC programmers to use. We describe how the extended haven-based memory management model is implemented, and demonstrate the use of the language-based annotations to affect the resiliency of a conjugate gradient solver application.