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The sparse matrix-vector (SpMV) multiplication routine is an important building block used in many iterative algorithms for solving scientific and engineering problems. One of the main challenges of SpMV is its memory-boundedness. Although compression has been proposed previously to improve SpMV performance on CPUs, its use has not been demonstrated on the(More)
This article describes a new priority queue implementation for managing the pending event set in discrete event simulation. Extensive empirical results demonstrate that it consistently outperforms other current popular candidates. This new implementation, called Ladder Queue, is also theoretically justified to have <i>O</i>(1) amortized access time(More)
Recently, the Intel Xeon Phi coprocessor has received increasing attention in high performance computing due to its simple programming model and highly parallel architecture. In this paper, we implement sparse matrix vector multiplication (SpMV) for scale-free matrices on the Xeon Phi architecture and optimize its performance. Scale-free sparse matrices are(More)
Stencils represent an important class of computations that are used in many scientific disciplines. Increasingly, many of the stencil computations in scientific applications are being offloaded to GPUs to improve running times. Since a large part of the simulation time is spent inside the stencil kernels, optimizing the kernel is therefore important in the(More)
Parallelization of existing code for modern multicore processors is tedious as the person performing these tasks must understand the algorithms, data structures and data dependencies in order to do a good job. Current options available to the programmer include either automatic parallelization or a complete rewrite in a parallel programming language.(More)
Directive-based programming approaches such as OpenMP and OpenACC have gained popularity due to their ease of programming. These programming models typically involve adding compiler directives to code sections such as loops in order to parallelize them for execution on multicore CPUs or GPUs. However, one problem with this approach is that existing(More)
The resolution of conventional surface-plasmon-resonance (SPR) imaging has been limited by the diffraction nature of light. A wide-field extended-resolution optical imaging technique, standing-wave SPR fluorescence (SW-SPRF) microscopy, has been developed. Based on evanescent SPR standing waves, SW-SPRF provides lateral resolution approaching 100 nm and(More)
Sparse matrix-vector multiplication (SpMV) is an important kernel that is used in many iterative algorithms for solving scientific and engineering problems. One of the main challenges of SpMV is its memory-boundedness due to the low arithmetic intensity of the kernel. Although compression has been proposed previously to improve SpMV performance on CPUs, its(More)