Mitigating Application Diversity for Allocating a Unified ACC-Rich Platform

Abstract

Heterogeneous accelerator-rich (ACC-rich) platforms combining general-purpose cores and specialized HW accelerators (ACCs) promise high-performance and low-power streaming application (app) deployments, e.g. for video analytics, software-defined radio, and radar. In order to recover NRE, a unified platform for a set of applications (apps) is desirable. When apps have functional and structural similarities, they can benefit from common ACCs. Identifying the most beneficial set of common ACCs is challenging. However, current allocation strategies mostly focus on one app in isolation. Automatically allocating a unified platform requires simultaneously considering many apps, an efficient design space traversal and a fair evaluation across diverse apps. This paper introduces a Unified ACC-rich Platform Allocation (UPA) methodology for sets of data flow apps. Key contributions are: (1) a genetic algorithm (GA) guided by a fair and efficient evaluation to allocate one unified platform for many apps, (2) defining relative efficiency for fair comparison across diverse apps, and (3) defining metrics to quantify many app platform efficiency. This paper demonstrates UPA's benefits using OpenVX apps. A 12-ACCs-UPA improves average efficiency 4.59x over app-dedicated platforms. The UPA platform enables more apps (55% of OpenVX apps) to be efficiently deployed (≥ 60% of optimal app-dedicated platform). The benefits increase even further with increasing ACC budget.