high performance computing on graphics processing units: hgpu.org

The significant growth in computational power of modern Graphics Processing Units (GPUs) coupled with the advent of general purpose programming environments like NVIDIA’s CUDA, has seen GPUs emerging as a very popular parallel computing platform. Till recently, there has not been a performance model for GPGPUs. The absence of such a model makes it difficult […]

Particle-in-cell (PIC) simulations with Monte-Carlo collisions are used in plasma science to explore a variety of kinetic effects. One major problem is the long run-time of such simulations. Even on modern computer systems, PIC codes take a considerable amount of time for convergence. Most of the computations can be massively parallelized, since particles behave independently […]

General-Purpose Computing on Graphics Processing Units (GPGPU) has lately been of great interest due to the release of architectures and software that simplifies programming graphics cards. This study explores how performance scales with FIR digital filters by varying the number of taps and the samples. We also discuss the trade-offs with various techniques for GPGPU […]

This paper introduces a general purpose graphics processing unit (GPGPU) stream processing implementation of moment invariants using an integral image or summed area table approach. Summed area tables have been used to help attain real-time performance for some classifier systems, however due to the computational complexity of moment invariants, a high throughput computational platform is […]

Outsourcing database as service instead of using in-house database management is a new trend emerging in a computing industry; there has been growing interest in outsourcing database services in both the commercial world and the research community. In this paper, we present analysis of non-concurrent model of fast single-database Private Information Retrieval (PIR) scheme for […]

Numerical simulations with the numerical human model using the finite-difference time domain (FDTD) method have recently been performed frequently in a number of fields in biomedical engineering. However, the FDTD calculation runs too slowly. We focus, therefore, on general purpose programming on the graphics processing unit (GPGPU). The three-dimensional FDTD method was implemented on the […]

In this paper, the mixed precision algorithm to solve the linear system of equations and the implementation of HPL package are introduced. We use this mixed precision algorithm to improve HPL package on CPU + GPGPU heterogeneous clusters, which is named for GHPL, and give the implementation mechanisms in detail. The experimental results are measured […]

Graphics cards, traditionally designed as accelerators for computer graphics, have evolved to support more general-purpose computation. General Purpose Graphical Processing Units (GPGPUs) are now being used as highly efficient, cost-effective platforms for executing certain simulation applications. While most of these applications belong to the category of timestepped simulations, little is known about the applicability of […]

The computational power provided by the massive parallelism of modern graphics processing units (GPUs) has moved increasingly into focus over the past few years. In particular, general purpose computing on GPUs (GPGPU) is attracting attention among researchers and practitioners alike. Yet GPGPU research is still in its infancy, and a major challenge is to rearrange […]

Graphics Processing Units (GPUs) has been applied to graphics applications to implement realistic perspectives of virtual scenes especially in entertainment market. Due to the demands from the market for creating super high definition scenes with high frame rate that simulates physics phenomenon naturally in visualization applications, the last decade promoted drastic performance improvement of GPUs. […]

Heterogeneous multicores, such as Cell BE processors and GPGPUs, typically do not have caches for their accelerator cores because coherence traffic, cache misses, and latencies from different types of memory accesses add overhead and adversely affect instruction scheduling. Instead, the accelerator cores have internal local memory to place their code and data. Programmers of such […]

A cluster of commodity computers and general-purpose computers with accelerators such as GPGPUs are now common platforms to solve computationally intensive tasks like scientific simulations. Both technologies provide users with high performance at relatively low cost. However, the low bandwidth of interconnect compared to the computing performance hinders efficient operation of both cluster and accelerator […]