Séamas McGettrick

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Sparse matrix by vector multiplication (SMV) is a key operation of many scientific and engineering applications. Field programmable gate arrays (FPGAs) have the potential to significantly improve the performance of computationally intensive applications which are dominated by SMV. A shortcoming of most existing FPGA SMV implementations is that they use(More)
Although interest in crossbreeding within dairy systems has increased, the role of Jersey crossbred cows within high concentrate input systems has received little attention. This experiment was designed to examine the performance of Holstein-Friesian (HF) and Jersey × Holstein-Friesian (J × HF) cows within a high concentrate input total confinement system(More)
Googlepsilas PageRank (PR) eigenvector problem is the worldpsilas largest matrix calculation. The algorithm is dominated by Sparse Matrix by Vector Multiplication (SMVM) where the matrix is very sparse, unsymmetrical and unstructured. The computation presents a serious challenge to general-purpose processors (GPP) and the result is a very lengthy(More)
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Implementation of carrier-sensing-based medium access control (MAC) protocols on inexpensive reconfigurable radio platforms has proven challenging due to long and unpredictable delays associated with both signal processing on a general purpose processor (GPP) and the interface between the RF front-end and the GPP. This paper describes the development and(More)
A hardware solver, implemented on an FPGA, for calculating the Page Rank eigenvector using the Power method is described. The critical operation is a very large sparse matrix by vector multiplication (SMVM). However, we show that the SMVM can be replaced with a pattern adder (a term coined to denote SMVM without multiplication), and a dense element by(More)