In this paper we explore the impact of the block shape on blocked and vectorized versions of the Sparse Matrix-Vector Multiplication (SpMV) kernel and build upon previous work by ...
Vasileios Karakasis, Georgios I. Goumas, Nectarios...
This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood a...
Many large-scale Web applications that require ranked top-k retrieval are implemented using inverted indices. An inverted index represents a sparse term-document matrix, where non...
George Beskales, Marcus Fontoura, Maxim Gurevich, ...
In this paper we use a Unified Relationship Matrix (URM) to represent a set of heterogeneous data objects (e.g., web pages, queries) and their interrelationships (e.g., hyperlinks...
Wensi Xi, Edward A. Fox, Weiguo Fan, Benyu Zhang, ...
Abstract. The efficient use of multicore architectures for sparse matrixvector multiplication (SpMV) is currently an open challenge. One algorithm which makes use of SpMV is the ma...