This paper presents a natural and efficient implementation for the classical broadcast message passing routine which optimizes performance of Ethernet based clusters. A simple algorithm for parallel matrix multiplication is specifically designed to take advantage of both, parallel computing facilities (CPUs) provided by clusters, and optimized performance of broadcast messages on Ethernet based...

Computing the simulation preorder of a given Kripke structure (i.e., a directed graph with n labeled vertices) has crucial applications in model checking of temporal logic. It amounts to solving a specific two-players reachability game, called simulation game. We offer the first conditional lower bounds for this problem, and we relate its complexity (for computation, verification, and certifica...

This paper is concerned with accurate computations for matrix multiplication. An error-free transformation of matrix multiplication is developed by the authors. It transforms a product of two floatingpoint matrices to a sum of several floating-point matrices by using only floating-point arithmetic. This transformation is useful not only for accurate matrix multiplication but also for interval e...

The objective of this paper is to develop algorithms for efficient and fast implementation in a multilayered mode of signal-processing tasks such as convolution, correlation, matrix multiplication, Fourier transformation, Hilbert transformation, etc., using structures built out of a large number of simple cells. Some of these designs are essentially conceptual, while others, such as the ones fo...

Although reliable long precision floating-point arithmetic libraries such as QD and MPFR/GMP are necessary to solve ill-conditioned problems in numerical simulation, long precision BLAS-level computation such as matrix multiplication has not been fully optimized because tuning costs are very high compared to IEEE float and double precision arithmetic. In this study, we develop a technique to sh...

Linear algebra operations have been widely used in big data analytics and scientific computations. Many works done on optimizing linear GPUs with regular-shaped input. However, few focus fully utilizing GPU resources when the input is not regular-shaped. Current optimizations do consider memory bandwidth computing power; therefore, they can only achieve sub-optimal performance. In this paper, w...

Today’s hardware platforms have parallel processing capabilities and many programming models been developed. It is necessary to research an efficient implementation of compute-intensive applications using available platforms. Dense matrix-matrix multiplication important kernel that used in applications, while it computationally intensive, especially for large matrix sizes. To improve the perfor...