Presentation
P37 - LIBRSB: Multicore Sparse Matrix Performance Across Languages and Architectures
Presenter
DescriptionLIBRSB (http://librsb.sf.net/) is a highly interoperable multicore CPU-oriented library for sparse matrix computations.
It serves as a component in sparse linear solvers. LIBRSB builds upon its "RSB" hierarchical and coarse-grained sparse matrices storage. The RSB data structure and algorithms are geared for efficient "Sparse BLAS"-like operations, namely variants of sparse multiply and triangular solution. In addition to Sparse BLAS, LIBRSB also provides the operations commonly required by interpreted languages. Thanks to that, it can serve the needs of higher level numerical languages like GNU Octave or Python, without sacrificing much of its performance characteristics. This poster presents an overview of usage modes, their advantages, and what's in the works. Emphasis is on multi-language support, as well as the different portability aspects.
It serves as a component in sparse linear solvers. LIBRSB builds upon its "RSB" hierarchical and coarse-grained sparse matrices storage. The RSB data structure and algorithms are geared for efficient "Sparse BLAS"-like operations, namely variants of sparse multiply and triangular solution. In addition to Sparse BLAS, LIBRSB also provides the operations commonly required by interpreted languages. Thanks to that, it can serve the needs of higher level numerical languages like GNU Octave or Python, without sacrificing much of its performance characteristics. This poster presents an overview of usage modes, their advantages, and what's in the works. Emphasis is on multi-language support, as well as the different portability aspects.
TimeTuesday, June 2719:30 - 21:30 CEST
LocationHall
SessionPoster Session and Reception
Event Type
Poster