Page 1 |
Save page Remove page | Previous | 1 of 172 | Next |
|
small (250x250 max)
medium (500x500 max)
large ( > 500x500)
Full Resolution
All (PDF)
|
This page
All
Subset |
HIGH-PERFORMANCE LINEAR ALGEBRA ON
RECONFIGURABLE COMPUTING SYSTEMS
by
Ling Zhuo
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMPUTER ENGINEERING)
August 2007
Copyright 2007 Ling Zhuo
Object Description
| Title | High-performance linear algebra on reconfigurable computing systems |
| Author | Zhuo, Ling |
| Author email | lzhuo@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Computer Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2007-06-21 |
| Date submitted | 2007 |
| Restricted until | Unrestricted |
| Date published | 2007-08-01 |
| Advisor (committee chair) | Prasanna, Viktor K. |
| Advisor (committee member) |
Dubois, Michel Hall, Mary Singh, Manbir |
| Abstract | Recently, high-end computing systems have been introduced that employ reconfigurable hardware as application-specific hardware accelerators for general-purpose processors. These systems provide new opportunities for high-performance implementations of scientific applications. However, they also pose new design challenges, including utilization of available hardware resources, exploitation of multiple levels of memory, and hardware/software co-design.; In this work, we investigate high-performance designs for floating-point based linear algebra on reconfigurable computing systems. The operations studied are fundamental kernels for scientific computing, including dense and sparse matrix-vector multiplication, matrix multiplication and matrix factorization. We first study the existing systems and propose a high-level design model. This model captures the architectural details of a system through various parameters at both node level and system level.; We next propose optimized designs on reconfigurable hardware using a parameterized design approach. Using the approach, we identify the design parameters, explore the design space and analyze the design trade-offs for each target operation. By tuning the parameters, the proposed designs can adapt to various hardware devices and achieve optimal performance under the available hardware resources. We also develop high-throughput and area-efficient designs for reduction, a fundamental primitive in performing linear algebra operations. Our designs are then incorporated into hybrid designs that utilize both the processors and the reconfigurable hardware in the system. A design methodology is proposed for hybrid designs to perform workload partitioning and hardware/software coordination.; Experimental results show that our designs for the vector operations achieve more than 90% of the peak performance under the available memory bandwidth. For the matrix operations, our designs achieve the optimal latency and minimize the required memory bandwidth with the available hardware resources. In addition, when newer and faster floating-point cores become available, the performance of our designs increases correspondingly. The proposed hybrid designs have been implemented on a state-of-the-art reconfigurable computing system. With 6 processors and 6 reconfigurable devices, our designs achieve more than 20 GFLOPS for matrix multiplication and matrix factorization. Furthermore, our designs achieve up to 90% of the total computing power of the system and more than 85% of the performance predicted using thehigh-level design model. |
| Keyword | reconfigurable computing; high-performance computing; algorithm design; matrix operations |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Type | texts |
| Legacy record ID | usctheses-m735 |
| Rights | Zhuo, Ling |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Zhuo-20070801 |
| Archival file | uscthesesreloadpub_Volume40/etd-Zhuo-20070801.pdf |
Description
| Title | Page 1 |
| Full text | HIGH-PERFORMANCE LINEAR ALGEBRA ON RECONFIGURABLE COMPUTING SYSTEMS by Ling Zhuo A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (COMPUTER ENGINEERING) August 2007 Copyright 2007 Ling Zhuo |
Comments
Post a Comment for Page 1
