high performance computing on graphics processing units: hgpu.org

With the invention of multi-core processing unit technology, the graphics processing unit has evolved from single core graphic processing unit to multi-core programmable graphics processing units. Because of the GPUs’ architecture, people found that it is not only good at processing graphics related data, but also suitable for performing general purpose parallel computations. However, since […]

Interest in many-core architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of many-core devices when applied to a typical HEP online task: the selection of events based on the trajectories of charged particles. We use as benchmark a scaled-up version of the […]

SkePU is a C++ template library with a simple and unified interface for expressing data parallel computations in terms of generic components, called skeletons, on multi-GPU systems using CUDA and OpenCL. The smart containers in SkePU, such as Matrix and Vector, perform data management with a lazy memory copying mechanism that reduces redundant data communication. […]

A system for live high quality surface reconstruction using a single moving depth camera on a commodity hardware is presented. High accuracy and real-time frame rate is achieved by utilizing graphics hardware computing capabilities via OpenCL and by using sparse data structure for volumetric surface representation. Depth sensor pose is estimated by combining serial texture […]

Recently, parallel programming has become necessary in order to obtain performance gains, primarily due to power limitations. However parallel architectures differ substantially from each other, often require specialized knowledge, and typically necessitate reimplementation and fine tuning of application code. These slow tasks frequently result in situations where most of the time is spent reimplementing old […]

This thesis is composed of two parts, that relate to both parallel and heterogeneous processing. The first describes DistCL, a distributed OpenCL framework that allows a cluster of GPUs to be programmed like a single device. It uses programmer-supplied meta-functions that associate work-items to memory. DistCL achieves speedups of up to 29x using 32 peers. […]

With the emergence of social networks and improvements in computational photography, billions of JPEG images are shared and viewed on a daily basis. Desktops, tablets and smartphones constitute the vast majority of hardware platforms used for displaying JPEG images. Despite the fact that these platforms are heterogeneous multicores, no approach exists yet that is capable […]

Since 2004, the clock frequency of CPUs has not increased significantly. Computer Vision applications have an increasing demand for more processing power and are limited by the performance capabilities of sequential processor architectures. The only way to get better performance using commodity hardware is to adopt parallel programming. Many other related research projects have considered […]

With the proliferation of general purpose GPUs, workload parallelization and datatransfer optimization became an increasing concern. The natural evolution from using a single GPU, is multiplying the amount of available processors, presenting new challenges, as tuning the workload decompositions and load balancing, when dealing with heterogeneous systems. Higher-level programming is a very important asset in […]

In earlier work, we have developed the SkePU skeleton programming library for modern multicore systems equipped with one or more programmable GPUs. The library internally provides four types of implementations (implementation variants) for each skeleton: serial C++, OpenMP, CUDA and OpenCL targeting either CPU or GPU execution respectively. Deciding which implementation would run faster for […]

Graphics Processing Units (GPUs) are increasingly used for general-purpose applications because of their low price, energy efficiency and enormous computing power. Considering the importance of GPU applications, it is vital that the behaviour of GPU programs can be specified and proven correct formally. This paper presents a logic to verify GPU kernels written in OpenCL, […]

We present Sailfish, an open source fluid simulation package implementing the lattice Boltzmann method (LBM) on modern Graphics Processing Units (GPUs) using CUDA/OpenCL. We take a novel approach to GPU code implementation and use run-time code generation techniques and a high level programming language (Python) to achieve state of the art performance, while allowing easy […]