Hybrid Application Mapping for Composable Many-Core Systems: Overview and Future Perspective

Behnaz Pourmohseni,Tobias Schwarzer,Stefan Wildermann,Valentina Richthammer,Jan Spieck,Michael Glaß,Martin Rapp,Heba Khdr,Fedor Smirnov,Jürgen Teich,Jörg Henkel,Andreas Weichslgartner

doi:10.3390/jlpea10040038

Abstract

Many-core platforms are rapidly expanding in various embedded areas as they provide the scalable computational power required to meet the ever-growing performance demands of embedded applications and systems. However, the huge design space of possible task mappings, the unpredictable workload dynamism, and the numerous non-functional requirements of applications in terms of timing, reliability, safety, and so forth. impose significant challenges when designing many-core systems. Hybrid Application Mapping (HAM) is an emerging class of design methodologies for many-core systems which address these challenges via an incremental (per-application) mapping scheme: The mapping process is divided into (i) a design-time Design Space Exploration (DSE) step per application to obtain a set of high-quality mapping options and (ii) a run-time system management step in which applications are launched dynamically (on demand) using the precomputed mappings. This paper provides an overview of HAM and the design methodologies developed in line with it. We introduce the basics of HAM and elaborate on the way it addresses the major challenges of application mapping in many-core systems. We provide an overview of the main challenges encountered when employing HAM and survey a collection of state-of-the-art techniques and methodologies proposed to address these challenges. We finally present an overview of open topics and challenges in HAM, provide a summary of emerging trends for addressing them particularly using machine learning, and outline possible future directions. While there exists a large body of HAM methodologies, the techniques studied in this paper are developed, to a large extent, within the scope of invasive computing. Invasive computing introduces resource awareness into applications and employs explicit resource reservation to enable incremental application mapping and dynamic system management.

Highlights

The ever-increasing computational power requirements of embedded applications have substantially changed the design process of embedded systems over the past decade
We introduce the fundamentals of Hybrid Application Mapping (HAM) and elaborate on the way HAM addresses the major design challenges in mapping applications to many-core systems
Embedded applications often have a set of non-functional requirements in terms of timing, safety, security, reliability, and so forth

Summary

Introduction

The ever-increasing computational power requirements of embedded applications have substantially changed the design process of embedded systems over the past decade. Many-core platforms such as Tilera TILE-Gx [1], Kalray MPPA-256 [2], Intel SCC (Single-chip Cloud Computer) [3], the KiloCore [4], or the upcoming SiPearl Rhea processor family [5] integrate tens, hundreds, or even thousands of processing cores on a single chip with a highly scalable communication scheme. This enables them to deliver a scalable computational power which is required to meet the progressively growing performance demands of emerging embedded applications and systems. An overview of the major challenges of many-core application mapping is provided

Methods

Results

Conclusion