The Kaczmarz algorithm is a popular solver for overdetermined linear systems due to its simplicity and speed. In this paper, we propose a modification that speeds up the convergence of the randomized Kaczmarz algorithm for systems of linear equations with sparse solutions. The speedup is achieved by projecting every iterate onto a weighted row of the linear system while maintaining the random r...

This paper describes and evaluates a parallel program for determining the three-dimensional structure of nucleic acids. A parallel constraint satisfaction algorithm is used to search a discrete space of shapes. Using two realistic data sets, we compare a previous sequential version of the program written in Miranda to the new sequential and parallel versions written in C, Scheme, and Multilisp,...

High-performance reconfigurable computing (HPRC) is a novel approach to provide large-scale computing power to modern scientific applications. Using both general-purpose processors and FPGAs allows application designers to exploit fine-grained and coarse-grained parallelism, achieving high degrees of speedup. One scientific application that benefits from this technique is backprojection, an ima...

Demonstrating speedup for parallel code on a multicore shared memory PC can be challenging in MATLAB due to underlying parallel operations that are often opaque to the user. This can limit potential for improvement of serial code even for the so-called embarrassingly parallel applications. One such application is the computation of the Jacobian matrix inherent to most nonlinear equation solvers...

This paper describes and evaluates a parallel program for determining the threedimensional structure of nucleic acids. A parallel constraint satisfaction algorithm is used to search a discrete space of shapes. Using two realistic data sets, we compare a previous sequential version of the program written in Miranda to the new sequential and parallel versions written in C, Scheme, and Multilisp, ...

Radial basis function-generated finite difference (RBF-FD) methods have recently been proposed as very interesting for global scale geophysical simulations, and have been shown to outperform established pseudo-spectral and discontinuous Galerkin methods for shallow water test problems. In order to be competitive for very large scale simulations, the implementation of the RBF-FD methods needs to...

This paper deals with the problem of predicting structures in the context of NLP. Typically, in structured prediction, an inference procedure is applied to each example independently of the others. In this paper, we seek to optimize the time complexity of inference over entire datasets, rather than individual examples. By considering the general inference representation provided by integer line...

In this paper, we report our parallel implementations of the Lanczos sparse linear system solving algorithm over large prime fields, on a multi-core platform. We employ several load-balancing methods suited to these platforms. We have carried out process-level and threadlevel parallel implementations under two different arithmetic libraries, and the best speedup obtained is 6.57 on eight cores....

We improve upon a baseline smoothed-particle hydrodynamics algorithm to bring it down from O(n2) time to O(n) time for n particles. We do so through a number of optimizations, which allow us to achieve up to a 67x speedup for large particle sizes over the baseline serial implementation. From this, we construct a parallel version of the code using OpenMP. We can achieve a 3.8x speedup over our o...