high performance computing on graphics processing units: hgpu.org

GPUs are excellent accelerators for data parallel applications with regular data access patterns. It is challenging, however, to optimize computations with irregular data access patterns on GPUs. One such computation is the Symmetric Matrix Vector product (SYMV) for dense linear algebra. Optimizing the SYMV kernel is important because it forms the basis of fundamental algorithms […]

Efficient cloth simulation is an important problem for interactive applications that involve virtual humans, such as computer games. A common aspect of many methods that have been developed to simulate cloth is a linear system of equations, which is commonly solved using conjugate gradient or multi-grid approaches. In this paper, we introduce to the computer […]

It has been widely shown that GPGPU architectures offer large performance gains compared to their traditional CPU counterparts for many applications. The downside to these architectures is that the current programming models present numerous challenges to the programmer: lower-level languages, explicit data movement, loss of portability, and challenges in performance optimization. In this paper, we […]

Finite element and finite volume methods on unstructured meshes offer a powerful approach to solving partial differential equations in complex domains. It has diverse application in areas such as industrial and geophysical fluid dynamics, structural mechanics, and radiative transfer. A key strength of the approach is the unstructured meshes exibility in conforming to complex geometry […]

Graphics processing units (GPUs) have been accepted as a powerful and viable coprocessor solution in high-performance computing domain. In order to maximize the benefit of GPUs for a multicore platform, a mechanism is needed for CPU threads in a parallel application to share this computing resource for efficient execution. NVIDIA’s Fermi architecture pioneers the feature […]

High quality cloth simulation is based on implicit methods. A variety of methods have been proposed to solve the linear systems of equations, with the conjugate gradient and multi-grid being the most commonly used. In this technical report we examine the preconditioned conjugate gradient method .More precisely, we analyze the quality of different preconditioning schemes […]

Scalable systems employing a mix of GPUs with CPUs are becoming increasingly prevalent in high-performance computing (HPC). The presence of such accelerators introduces significant challenges and complexities to both language developers and end users. This paper provides a close study of efficient coordination mechanisms to handle parallel requests from multiple hosts of control to a […]

Stochastic simulations are often sensitive to the randomness source that characterizes the statistical quality of their results. Consequently, we need highly reliable Random Number Generators (RNGs) to feed such applications. Recent developments try to shrink the computation time by using more and more General Purpose Graphics Processing Units (GP-GPUs) to speed-up stochastic simulations. Such devices […]

In this article, we consider hybrid architectures that consist of standard CPU cores associated with accelerators (such as GPUs). These architectures are increasingly employed in large computing centers. We develop a strategy designed to deal with hybrid computing architectures from the computing performance and programmability points of view. We focus on hybrid computing clusters that […]

OP2 is an "active" library framework for the development and solution of unstructured mesh-based applications. It aims to decouple the scientific specification of an application from its parallel implementation to achieve code longevity and near-optimal performance through re-targeting the backend to different multi-core/many-core hardware. This paper presents a summary of a predictive performance analysis and […]

Since its introduction over two decades ago, graphics hardware has continued to evolve to improve rendering performance and increase programmability. While most undergraduate courses in computer graphics focus on rendering algorithms and programming APIs, we have recently created an undergraduate senior elective course that focuses on graphics processing and architecture, with a strong emphasis on […]

MapReduce is a programming model from Google that facilitates parallel processing on a cluster of thousands of commodity computers. The success of MapReduce in cluster environments has motivated several studies of implementing MapReduce on a graphics processing unit (GPU), but generally focusing on the NVIDIA GPU. Our investigation reveals that the design and mapping of […]