The RECIPE Approach to Challenges in Deeply Heterogeneous High Performance Systems

TL;DR

RECIPE introduces a hierarchical resource management framework for heterogeneous HPC systems to optimize energy use, ensure reliability, and meet application time constraints, with predictive models for thermal and reliability management.

Contribution

The paper presents a novel hierarchical management approach that integrates predictive reliability and thermal models to improve performance and hardware longevity in exascale heterogeneous systems.

Findings

Prediction accuracy significantly affects checkpointing overheads.

Hierarchical management improves energy efficiency and reliability.

Application to weather forecasting demonstrates practical benefits.

Abstract

RECIPE (REliable power and time-ConstraInts-aware Predictive management of heterogeneous Exascale systems) is a recently started project funded within the H2020 FETHPC programme, which is expressly targeted at exploring new High-Performance Computing (HPC) technologies. RECIPE aims at introducing a hierarchical runtime resource management infrastructure to optimize energy efficiency and minimize the occurrence of thermal hotspots, while enforcing the time constraints imposed by the applications and ensuring reliability for both time-critical and throughput-oriented computation that run on deeply heterogeneous accelerator-based systems. This paper presents a detailed overview of RECIPE, identifying the fundamental challenges as well as the key innovations addressed by the project. In particular, the need for predictive reliability approaches to maximize hardware lifetime and guarantee application performance is identified as the key concern for RECIPE, and is addressed via hierarchical resource management of the heterogeneous architectural components of the system, driven by estimates of the application latency and hardware reliability obtained respectively through timing analysis and modelling thermal properties, mean-time-to-failure of subsystems. We show the impact of prediction accuracy on the overheads imposed by the checkpointing policy, as well as a possible application to a weather forecasting use case.