Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which ...
Regular distributions for storing dense matrices on parallel systems are not always used in practice. In many scientific applicati RUMMA) [1] to handle irregularly distributed mat...
We perform forward error analysis for a large class of recursive matrix multiplication algorithms in the spirit of [D. Bini and G. Lotti, Stability of fast algorithms for matrix m...
James Demmel, Ioana Dumitriu, Olga Holtz, Robert K...
We present a fast and scalable matrix multiplication algorithm on distributed memory concurrent computers, whose performance is independent of data distribution on processors, and...
FPGAs (Field-Programmable Gate Arrays) are often used as coprocessors to boost the performance of dataintensive applications [1, 2]. However, mapping algorithms onto multimillion-...