in this paper, the numerical technique based on hybrid bernoulli and block-pulse functions has been developed to approximate the solution of system of linear volterra integral equations. system of volterra integral equations arose in many physical problems such as elastodynamic, quasi-static visco-elasticity and magneto-electro-elastic dynamic problems. these functions are formed by the hybridi...

In this paper we introduce a vector ISA extension to facilitate sparse matrix manipulation on vector processors (VPs). First we introduce a new Block Based Compressed Storage (BBCS) format for sparse matrix representation and a Block-wise Sparse Matrix-Vector Multiplication approach. Additionally, we propose two vector instructions, Multiple Inner Product and Accumulate (MIPA) and LoaD Section ...

Sparse matrix multiplication is an important component of linear algebra computations. In this paper, an architecture based on Content Addressable Memory (CAM) and Resistive Content Addressable Memory (ReCAM) is proposed for accelerating sparse matrix by sparse vector and matrix multiplication in CSR format. Using functional simulation, we show that the proposed ReCAM-based accelerator exhibits...

We evaluate and compare the storage efficiency of different sparse matrix storage formats as index structure for text collection and their corresponding sparse matrixvector multiplication algorithm to perform query processing in information retrieval (IR) application. We show the results of our implementations for several sparse matrix algorithms such as Coordinate Storage (COO), Compressed Spa...

This paper describes ideas and tools that help with the visualization of sparse matrix computations. The paper uses the Sparse Matrix Manipulation System, an environment for handling sparse matrices of all types in a vy flexible manner via ASCII file interfaces. Two commands in this environment are ShowMalrix and ShowTree. The first illustrates the pattern of nonzeroes of a sparse matrix. The s...

In certain applications the non-zero elements of large sparse matrices are formed by adding several smaller contributions in random order before the final values of the elements are known. For some sparse matrix representations this procedure is laborious. We present an efficient method for assembling large irregular sparse matrices where the nonzero elements have to be assembled by adding toge...

In the age of statistical and scientific databases, there is an emerging trend of integrating analytical algorithms into database systems. Many of these algorithms are based on linear algebra with large, sparse matrices. However, linear algebra expressions often contain multiplications of more then two matrices. The execution of sparse matrix chains is nontrivial, since the runtime depends on t...