Paper Info
Title
ADRENALINE: An OpenVX Environment to Optimize Embedded Vision Applications on Many-core Accelerators
Abstract
The acceleration of Computer Vision algorithms is an important enabler to support the more and more pervasive applications of the embedded vision domain. Heterogeneous systems featuring a clustered many-core accelerator are a very promising target for embedded vision workloads, but the code optimization for these platforms is a challenging task. In this work we introduce ADRENALINE 1, a novel framework for fast prototyping and optimization of OpenVX applications for heterogeneous SoCs with many-core accelerators. ADRENALINE consists of an optimized OpenVX run-time system and a virtual platform, and it is intended to provide support to a wide range of end users. We highlight the benefits of this approach in different optimization contexts.
Year
DOI
Venue
2015
10.1109/MCSoC.2015.45
MCSoC
Keywords
Field
DocType
embedded vision, OpenVX, virtual platform, accelerator
Program optimization,End user,Virtual platform,Computer science,Computer vision algorithms,Acceleration,Embedded system
Conference
Citations 
PageRank 
References 
5
0.45
13
Authors
4
Name
Order
Citations
PageRank
Giuseppe Tagliavini1213.91
Germain Haugou217010.71
Andrea Marongiu333739.19
Luca Benini4131161188.49