Allocating One Common ACC-Rich Platform for Many Streaming Applications

Abstract

Many demanding streaming applications share functional and structural similarities with other apps in their respective domain, e.g., video analytics, software-defined radio, and radar. This opens the opportunity for specialization (e.g., heterogeneous computing) to achieve the needed efficiency and/or performance. However, current design space exploration (DSE) focuses on an individual application in isolation (e.g., one particular vision flow), but not a set of similar applications. Hence, optimizations that occur due to considering multiple applications simultaneously are missed. New DSE methodologies and tools are needed with a broader scope of application sets instead of individual applications. This article introduces a novel domain-specific DSE (DS-DSE) approach focusing on streaming applications. Key contributions are: 1) a formalized method to extract the functional and structural similarities of domain applications; 2) a rapid platform performance estimation and comparison at two abstraction levels: domain score (DS) and analytic performance estimation (APE) model; 3) two novel algorithms, dynamic score selection (DSS), and GenetIc domain exploration (GIDE), for hardware/software partitioning of a domain-specific platform to maximize the throughput across domain applications (under certain constraints); and 4) a methodology to evaluate a platform’s benefit for a set of applications. We demonstrate DSS’s and GIDE’s benefits using OpenVX applications and synthetic domains. The DSS and GIDE generated domain-specific platforms improve performance over application-specific platforms by 58% and 75% for OpenVX, as well as by 23% and 48% for synthetic applications. GIDE’s platforms reach 99.8% (OpenVX) and 97.6% (synthetic) throughput of the domain optimal platform obtained through exhaustive search.