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FPGA implementation of a dense optical flow algorithm using altera openCL SDK

Title	FPGA implementation of a dense optical flow algorithm using altera openCL SDK
Author	Ulutaş, Umut, Tosun, Mustafa, Levent, Vecdi Emre, Büyükaydın, D., Akgün, T., Uğurdağ, Hasan Fatih
Publication Date:	2017
Publication Place	- Springer International Publishing
Subject	Altera SDK for OpenCL, Dense optical flow, FPGA, High-Level Synthesis
Type	Document
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	978-3-319-67596-1
Record ID	d0e77f5e-d4be-4e17-b68a-0059ec35ec65
Library Location	Electrical & Electronics Engineering
Date	2017
Notes	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text	FPGA acceleration of compute-intensive algorithms is usually not regarded feasible because of the long Verilog or VHDL RTL design efforts they require. Data-parallel algorithms have an alternative platform for acceleration, namely, GPU. Two languages are widely used for GPU programming, CUDA and OpenCL. OpenCL is the choice of many coders due to its portability to most multi-core CPUs and most GPUs. OpenCL SDK for FPGAs and High-Level Synthesis (HLS) in general make FPGA acceleration truly feasible. In data-parallel applications, OpenCL based synthesis is preferred over traditional HLS as it can be seamlessly targeted to both GPUs and FPGAs. This paper shares our experiences in targeting a demanding optical flow algorithm to a high-end FPGA as well as a high-end GPU using OpenCL. We offer throughput and power consumption results on both platforms.
DOI	10.1007/978-3-319-67597-8_9
Cilt	778

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Özyeğin University

FPGA implementation of a dense optical flow algorithm using altera openCL SDK

Author Ulutaş, Umut, Tosun, Mustafa, Levent, Vecdi Emre, Büyükaydın, D., Akgün, T., Uğurdağ, Hasan Fatih

Publication Date 2017

Publication Place - Springer International Publishing

Subject Altera SDK for OpenCL, Dense optical flow, FPGA, High-Level Synthesis

Type Document

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 978-3-319-67596-1

Record ID d0e77f5e-d4be-4e17-b68a-0059ec35ec65

Library Location Electrical & Electronics Engineering

Date 2017

Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Sample Text FPGA acceleration of compute-intensive algorithms is usually not regarded feasible because of the long Verilog or VHDL RTL design efforts they require. Data-parallel algorithms have an alternative platform for acceleration, namely, GPU. Two languages are widely used for GPU programming, CUDA and OpenCL. OpenCL is the choice of many coders due to its portability to most multi-core CPUs and most GPUs. OpenCL SDK for FPGAs and High-Level Synthesis (HLS) in general make FPGA acceleration truly feasible. In data-parallel applications, OpenCL based synthesis is preferred over traditional HLS as it can be seamlessly targeted to both GPUs and FPGAs. This paper shares our experiences in targeting a demanding optical flow algorithm to a high-end FPGA as well as a high-end GPU using OpenCL. We offer throughput and power consumption results on both platforms.

DOI 10.1007/978-3-319-67597-8_9

Cilt 778