Heterogeneous Computing Utilizing FPGAs

Heterogeneous Computing Utilizing FPGAs Heterogeneous computing plays an ever-increasing role in power-efficient, high-performance embedded systems for various data processing tasks, such as computer vision. One possibility to accelerate this kind of application is the usage of FPGAs as a co-processor for standard CPUs. Although hardware design is becoming easier by utilizing High-Level-Synthesis tools, the question of interfacing FPGAs and CPUs has yet to be completely solved. The Heterogeneous System Architecture (HSA) Foundation defines and publishes architecture neutral standards for heterogeneous systems and programming models. While compatible CPU, GPU and DSP designs exist, FPGA models have not been defined yet. This paper describes the IP library LibHSA, which greatly simplifies integration of domain specific FPGA acceleration into existing HSA compliant systems. It allows FPGA based accelerators to take immediate advantage of high-level language tool chains. Including user space memory access, low-latency task dispatch and other benefits of the HSA programming model. We will demonstrate LibHSA with a programmable image processor implementation on a Xilinx FPGA. The image processor supports low-level algorithms, e.g. Sobel, Median, Laplace, or Gaussian. Our results show that the LibHSA infrastructure greatly simplifies the effort integrating FPGAs and customized hardware into existing accelerator systems, runtimes and application software. Keywords Heterogeneous system http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Signal Processing Systems Springer Journals

Loading next page...
 
/lp/springer_journal/heterogeneous-computing-utilizing-fpgas-itXHYXDlkG
Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Engineering; Signal,Image and Speech Processing; Circuits and Systems; Electrical Engineering; Image Processing and Computer Vision; Pattern Recognition; Computer Imaging, Vision, Pattern Recognition and Graphics
ISSN
1939-8018
eISSN
1939-8115
D.O.I.
10.1007/s11265-018-1382-7
Publisher site
See Article on Publisher Site

Abstract

Heterogeneous computing plays an ever-increasing role in power-efficient, high-performance embedded systems for various data processing tasks, such as computer vision. One possibility to accelerate this kind of application is the usage of FPGAs as a co-processor for standard CPUs. Although hardware design is becoming easier by utilizing High-Level-Synthesis tools, the question of interfacing FPGAs and CPUs has yet to be completely solved. The Heterogeneous System Architecture (HSA) Foundation defines and publishes architecture neutral standards for heterogeneous systems and programming models. While compatible CPU, GPU and DSP designs exist, FPGA models have not been defined yet. This paper describes the IP library LibHSA, which greatly simplifies integration of domain specific FPGA acceleration into existing HSA compliant systems. It allows FPGA based accelerators to take immediate advantage of high-level language tool chains. Including user space memory access, low-latency task dispatch and other benefits of the HSA programming model. We will demonstrate LibHSA with a programmable image processor implementation on a Xilinx FPGA. The image processor supports low-level algorithms, e.g. Sobel, Median, Laplace, or Gaussian. Our results show that the LibHSA infrastructure greatly simplifies the effort integrating FPGAs and customized hardware into existing accelerator systems, runtimes and application software. Keywords Heterogeneous system

Journal

Journal of Signal Processing SystemsSpringer Journals

Published: May 31, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off