Paper Info
Title
Supporting localized OpenVX kernel execution for efficient computer vision application development on STHORM many-core platform
Abstract
Nowadays Embedded Computer Vision (ECV) is considered a technology enabler for next generation killer apps, and scientific and industrial communities are showing a growing interest in developing applications on high-end embedded systems. Modern many-core accelerators are a promising target for running common ECV algorithms, since their architectural features are particularly suitable in terms of data access patterns and program control flow. In this work we propose a set of software optimization techniques, mainly based on data tiling and local buffering policies, which are specifically targeted to accelerate the execution of OpenVX-based ECV applications by exploiting the memory hierarchy of STHORM many-core accelerator.
Year
DOI
Venue
2014
10.1145/2597917.2597947
Conf. Computing Frontiers
Keywords
Field
DocType
many-core systems,general,parallel algorithms,openvx,embedded computer vision,mobile processors
Program optimization,Kernel (linear algebra),Memory hierarchy,Program control,Computer science,Parallel algorithm,Parallel computing,Real-time computing,Embedded computer vision,Data access,Embedded system
Conference
Citations 
PageRank 
References 
0
0.34
2
Authors
3
Name
Order
Citations
PageRank
Giuseppe Tagliavini1213.91
Germain Haugou217010.71
Luca Benini3131161188.49