Coprocessor design to support MPI primitives in configurable multiprocessors
Integration, the VLSI Journal
Reconfiguration support for vector operations
International Journal of High Performance Systems Architecture
A joint interchannel and network coding schema for nVoD services over wireless mesh networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
An FPGA-Based parallel accelerator for matrix multiplications in the newton-raphson method
EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing
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Configurable computing, where hardware resources are configured appropriately to match specific hardware designs, has recently demonstrated its ability to significantly improve performance for a wide range of computation-intensive applications. With steady advances in silicon technology, as predicted by Moore's Law, Field-Programmable Gate Array (FPGA) technologies have enabled the implementation of System-on-a-Programmable-Chip (SOPC or SOC) computing platforms, which, in turn, have given a significant boost to the field of configurable computing. It is possible to implement various specialized parallel machines in a single silicon chip. In this paper, we describe our design and implementation of a parallel machine on an SOPC development board, using multiple instances of a soft IP configurable processor; we use this machine for LU factorization. LU factorization is widely used in engineering and science to solve efficiently large systems of linear equations. Our implementation facilitates the efficient solution of linear equations at a cost much lower than that of supercomputers and networks of workstations. The intricacies of our FPGA-based design are presented along with tradeoff choices made for the purpose of illustration. Performance results prove the viability of our approach. Copyright © 2004 John Wiley & Sons, Ltd.