In this paper, a method has been developed to construct the membership surfaces of row and column vectors and arithmetic operations of imprecise matrix. A matrix with imprecise elements would be called an imprecise matrix. The membership surface of imprecise vector has been already shown based on Randomness-Impreciseness Consistency Principle. The RandomnessImpreciseness Consistency Principle l...

This paper presents a preliminary experimental study of the performance of basic sparse matrix computations on the CM-200 and the CM-5. We concentrate on examining various ways of performing general sparse matrix-vector operations and the basic primitives on which these are based. We compare various data structures for storing sparse matrices and their corresponding matrix – vector operations. ...

This paper presents a preliminary experimental study of the performance of basic sparse matrix computations on the CM-200 and the CM-5. We concentrate on examining various ways of performing general sparse matrix-vector operations and the basic primitives on which these are based. We compare various data structures for storing sparse matrices and their corresponding matrix – vector operations. ...

In [23] we showed that a large class of fast recursive matrix multiplication algorithms is stable in a normwise sense, and that in fact if multiplication of n-by-n matrices can be done by any algorithm in O(n) operations for any η > 0, then it can be done stably in O(n) operations for any η > 0. Here we extend this result to show that essentially all standard linear algebra operations, includin...

Basic Linear Algebra Subprograms (BLAS) play key role in high performance and scientific computing applications. Experimentally, yesteryear multicore and General Purpose Graphics Processing Units (GPGPUs) are capable of achieving up to 15 to 57% of the peak performance at 65W to 240W of power respectively in underlying platform for compute bound operations like Double/Single Precision General M...