Heterogeneous computing with accelerators: an overview with examples

Abstract

Accelerator-based platforms are heterogeneous in nature, yet most applications avoid heterogeneity, and focus on acceleration alone. Platform-level heterogeneity can bring significant performance improvement, as it essentially means using additional resources for the same computation. But is the performance gained using these additional resources worth the effort to program and deploy heterogeneous applications? In this work, we present a taxonomy of the existing programming models and tools available for heterogeneous computing with accelerators, and give examples of systems fitting different classes. We further provide guidelines for efficiently navigating this landscape in the search for a suitable tool for designing and deploying a new application.