Abstract. The innovation of this work is a simple vectorizable algorithm for performing sparse matrix vector multiply in compressed sparse row (CSR) storage format. Unlike the vect...
Eduardo F. D'Azevedo, Mark R. Fahey, Richard Tran ...
The paper describes two methods for the design of matrix-oriented SAT solvers based on data compression. The first one provides matrix compression in a host computer and decompress...
Valery Sklyarov, Iouliia Skliarova, Bruno Figueire...
Sparse matrix problems are di cult to parallelize e ciently on message-passing machines, since they access data through multiple levels of indirection. Inspector executor strategie...
Manuel Ujaldon, Shamik D. Sharma, Joel H. Saltz, E...
This paper provides an algorithmic framework for learning statistical models involving directed spanning trees, or equivalently non-projective dependency structures. We show how p...
Terry Koo, Amir Globerson, Xavier Carreras, Michae...
In this work, we provide two heuristic algorithms for the matrix bandwidth reduction problem. The first is a genetic algorithm and the second uses node label adjustments. Experime...