Architectural optimization of decomposition algorithms for wireless communication systems

Authors:
Ali Irturk;Bridget Benson;Nikolay Laptev;Ryan Kastner
Affiliations:
Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA;Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA;Department of Computer Science, University of California, Los Angeles, Los Angeles, CA;Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA
Venue:
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Year:
2009

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Abstract

Matrix decomposition is required in various algorithms used in wireless communication applications. FPGAs strike a balance between ASICs and DSPs, as they have the programmability of software with performance capacity approaching that of a custom hardware implementation. However, FPGA architectures require designers to make a countless number of system, architectural and logic design decisions. By performing design space exploration, a designer can find the optimal device for a specific application, however very few tools exist which can accomplish this task. This paper presents automatic generation and optimization of decomposition methods using a core generator tool, GUSTO, that we developed to enable easy design space exploration with different parameterization options such as resource allocation, bit widths of the data, number of functional units and organization of controllers and interconnects. We present a detailed study of area and throughput tradeoffs of matrix decomposition architectures using different parameterizations.