Please use this identifier to cite or link to this item: https://doi.org/10.1109/VLSI.Design.2009.35
Title: Accelerating system-level design Tasks using Commodity graphics hardware: A case study
Authors: Bordoloi, U.D.
Chakraborty, S. 
Issue Date: 2009
Source: Bordoloi, U.D., Chakraborty, S. (2009). Accelerating system-level design Tasks using Commodity graphics hardware: A case study. Proceedings: 22nd International Conference on VLSI Design - Held Jointly with 7th International Conference on Embedded Systems : 465-470. ScholarBank@NUS Repository. https://doi.org/10.1109/VLSI.Design.2009.35
Abstract: Many system-level design tasks (e.g. timing analysis, hardware/software partitioning and design space exploration) involve computational kernels that are intractable (usually NP-hard). As a result, they involve high running times even for mid-sized problems. In this paper we explore the possibility of using commodity graphics processing units (GPUs) to accelerate such tasks that commonly arise in the electronic design automation (EDA) domain. We demonstrate this idea via a detailed case study on a general hardware/software design space exploration problem and propose a GPU-based engine for it. Not only does this problem commonly arise in the embedded systems domain, its computational kernel turns out to be a general combinatorial optimization problem (viz. the knapsack problem) which lies at the heart of several EDA applications. Our experimental results show that our GPU-based implementation offers very attractive speedups for this computational kernel (up to 100×), and speedups of up to 17× for the full problem. In contrast to ASIC/FPGA-based accelerators - since even low-end desktop and notebook computers are today equipped with GPUs - our solution involves no extra hardware cost. Although recent research has shown the benefits of using GPUs for a variety of non-graphics applications (e.g. in databases and bioinformatics), hardly any work has been done on harnessing the parallelism of GPUs to accelerate problems from the EDA domain. We hope that our results and the generality of the problem we address will motivate researchers from this community to explore the possibility of using GPUs for a wider variety of problems from the EDA domain. © 2009 IEEE.
Source Title: Proceedings: 22nd International Conference on VLSI Design - Held Jointly with 7th International Conference on Embedded Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/40509
ISBN: 9780769535067
DOI: 10.1109/VLSI.Design.2009.35
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

4
checked on Dec 14, 2017

WEB OF SCIENCETM
Citations

1
checked on Nov 20, 2017

Page view(s)

42
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.