high performance computing on graphics processing units: hgpu.org

As the era of Moore’s Law and increasing CPU clock rates nears its stopping point the focus of chip and hardware design has shifted to increasing the number of computation cores present on the chip. This increase can be most clearly seen in the rise of Graphic Processing Units (GPU) where hundreds or thousands of […]

BLAST, short for Basic Local Alignment Search Tool, is a fundamental algorithm in the life sciences that compares biological sequences. However, with the advent of next-generation sequencing (NGS) and increase in sequence read-lengths, whether at the outset or downstream from NGS, the exponential growth of sequence databases is arguably outstripping our ability to analyze the […]

Large-scale simulation can provide a wide range of information needed to develop and validate theoretical models for multiphase flow in porous medium systems. In this paper, we consider a coupled solution in which a multiphase flow simulator is coupled to an analysis approach used to extract the interfacial geometries as the flow evolves. This has […]

The proverb above describes the essence of this paper and the motivation behind the development of our Interactive Parallelization Tool (IPT) that can transform serial applications into multiple parallel variants. The end-users of the IPT are required to develop an understanding about the basic concepts involved in parallel programming (viz. concurrency, data distribution and data […]

Many-Core computing is an actual growing concept that allows the true parallelization of computational tasks. In the particular case of this paper, the vector quantization algorithm was adapted to the many-core concept with the objective of compressing images encoded in the PGM format. For that, a given sequential implementation of the algorithm was optimized and […]

RGB-D data is getting ever more interest from the research community as both cheap cameras appear in the market and the applications of this type of data become more common. A current trend in processing image data is the use of convolutional neural networks (CNNs) that have consistently beat competition in most benchmark data sets. […]

Simulation has become an important method that is widely used in studying the propagation behaviors during the process of viral advertisement diffusion. With the increased computing and memory resources required for large-scale network processing, General Purpose Graphics Processing Units (GPGPUs) have been used in high performance computing platforms to accelerate simulation performance. In this paper, […]

Sparse matrix-vector multiplication (SMVM) is a crucial primitive used in a variety of scientific and commercial applications. Despite having significant parallelism, SMVM is a challenging kernel to optimize due to its irregular memory access characteristics. Numerous studies have proposed the use of FPGAs to accelerate SMVM implementations. However, most prior approaches focus on parallelizing multiply-accumulate […]

The XeonPhi is a highly parallel x86 architecture chip made by Intel. It has a number of novel features which make it a particularly challenging target for the compiler writer. This paper describes the techniques used to port the Glasgow Vector Pascal Compiler (VPC) to this architecture and assess its performance by comparisons of the […]

Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and thus the use of high-performance computing (HPC) platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs) have democratized the use of HPC as they push desktop computers to cluster-level […]

The Poisson-Boltzmann equation models the electrostatic potential generated by fixed charges on a polarizable solute immersed in an ionic solution. This approach is often used in computational Structural Biology to estimate the electrostatic energetic component of the assembly of molecular biological systems. In the last decades the amount of structural data concerning proteins and other […]

An effective approach termed Recursive Gaussian Maximum Likelihood Estimation (RGMLE) is developed in this paper to suppress 2-D impulse noise. And two algorithms termed RGMLE-C and RGMLE-CS are derived by using spatially-adaptive variances, which are respectively estimated based on certainty and joint certainty & similarity information. To give reliable implementation of RGMLE-C and RGMLE-CS algorithms, […]