Many numerical algorithms are specified in terms of operations on vectors and matrices. Matrix operations can be executed extremely efficiently using specialized linear algebra k...
Large sparse matrices play important role in many modern information retrieval methods. These methods, such as clustering, latent semantic indexing, performs huge number of computa...
Computations with sparse matrices on "multicore cache based" computers are affected by the irregularity of the problem at hand, and performance degrades easily. In this ...
Abstract. This paper presents a real time parallel hardware architecture for image feature detection based on the SIFT (Scale Invariant Feature Transform) algorithm. This architect...
Vanderlei Bonato, Eduardo Marques, George A. Const...
We investigate the use of the multistep successive preconditioning strategies (MSP) to construct a class of parallel multilevel sparse approximate inverse (SAI) preconditioners. W...