Recent technological advances have led to a number of emerging platforms such as multi-cores, reconfigurable computing, and graphics processing units. We present a comparative study of multi-cores, field-programmable gate arrays, and graphics processing units for a Quantum Monte Carlo chemistry application. The speedups of these implementations are measured relative to a multi-core implementati...

In the process of real time image processing, the amount of image processing computing and data is very large, the use of single core or a single DSP can not meet the needs of real-time image processing. This paper designs the new generation multi-core DSP real-time image processing system, the system is a multi-core high performance DSP as the core circuit, and also uses FPGA counterweight dev...

Video surveillance must automatically detect targets and suspicious behaviors in order to effectively monitor large networks of cameras. Single processor designs have limited previous attempts at video content analysis and computer vision. We present a cost-effective multi-core approach that utilizes 16 DSP and 8 RISC processors on one chip, working in parallel to analyze video feeds for use in...

The use of GPUs to accelerate the factoring of large sparse symmetric indefinite matrices shows the potential of yielding important benefits to a large group of widely used applications. This paper examines how a multifrontal sparse solver performs when exploiting both the GPU and its multi-core host. It demonstrates that the GPU can dramatically accelerate the solver relative to one host CPU. ...

A parallel method for computing Boolean expressions based on the properties of finite free Boolean algebras is presented. We also show how various finite combinatorial objects can be codded in the formalism of Boolean algebras and counted by this procedure. Particularly, using a translation of first order predicate formulas to propositional formulas, we give a method for constructing and counti...

Genetic Programming (GP) is a computationally intensive technique which also has a high degree of natural parallelism. Parallel computing architectures have become commonplace especially with regards Graphics Processing Units (GPU). Hence, versions of GP have been implemented that utilise these highly parallel computing platforms enabling significant gains in the computational speed of GP to be...

This paper presents CUDA-based parallelization of implicit incompressible SPH (IISPH) on the GPU. Along with the detailed exposition of our implementation, we analyze various components involved for their costs. We show that our CUDA version achieves near linear scaling with the number of particles and is faster than the multi-core parallelized IISPH on the CPU. We also present a basic comparis...

Multi-core processors are no longer the future of computing-they are the present day reality. A typical mass-produced CPU features multiple processor cores, while a GPU (Graphics Processing Unit) may have hundreds or even thousands of cores. With the rise of multi-core architectures has come the need to teach advanced programmers a new and essential skill: how to program massively parallel proc...

In this paper we present GPU-based techniques for the interactive visualization of large unsteady 3D flow fields on uniform grids. We propose a novel dual-core approach to asynchronously stream such fields from the CPU, thus enabling the efficient exploration of large time-resolved sequences. This approach decouples visualization from data handling, resulting in interactive frame rates. Built u...