high performance computing on graphics processing units: hgpu.org

Open Compute Language (OpenCL) has been proposed as a platform-independent, parallel execution model to target heterogeneous systems, including multiple central processing units, graphics processing units (GPUs), and digital signal processors (DSPs). OpenCL parallelism scales with the available resources and hardware generational improvements due to the data-parallel nature of its kernels. Such parallel expressions must adhere […]

Computational Science has emerged as a third pillar of science along with theory and experiment, where the parallelization for scientific computing is promised by different shared and distributed memory architectures such as, super-computer systems, grid and cluster based systems, multi-core and multiprocessor systems etc. In the recent years the use of GPUs (Graphic Processing Units) […]

We study the performance portability of OpenCL across diverse architectures including NVIDIA GPU, Intel Ivy Bridge CPU, and AMD Fusion APU. We present detailed performance analysis at assembly level on three exemplar OpenCL benchmarks: SGEMM, SpMV, and FFT. We also identify a number of tuning knobs that are critical to performance portability, including threads-data mapping, […]

This paper presents the design and implementation of several fundamental dense linear algebra (DLA) algorithms in OpenCL. In particular, these are linear system solvers and eigenvalue problem solvers. Further, we give an overview of the clMAGMA library, an open source, high performance OpenCL library that incorporates the developments presented, and in general provides to heterogeneous […]

Recently, general-purpose computing on graphics processing units (GPGPU) has been enabled on mobile devices thanks to the emerging heterogeneous programming models such as OpenCL. The capability of GPGPU on mobile devices opens a new era for mobile computing and can enable many computationally demanding computer vision algorithms on mobile devices. As a case study, this […]

With its design concept of cross-platform portability, OpenCL can be used not only on GPUs (for which it is quite popular), but also on CPUs. Whether porting GPU programs to CPUs, or simply writing new code for CPUs, using OpenCL brings up the performance issue, usually raised in one of two forms: "OpenCL is not […]

Over the last few decades, computer modelling and computer simulation have become an invaluable tool for computational chemists interested in advancing their research and experiment in a more efficient, cost effective way with new molecules. As computer capabilities increase the demand for more accurate models and faster simulations has also grown. Some of these models […]

Integration of GPUs in a Cloud Computing environment is an emerging research area. The GPUs are used to perform processing extremely exigent in terms of power computation and the Cloud computing has the potential to become a major tool for scientists and engineers to access high performance resource and storage. The proposed work has been […]

This thesis details the refinement and numerical solution of a preexisting model for predicting the strengths and positions of so-called wake-vortices that are generated from the lift of heavy aircraft. The ultimate objective is to implement a numerical scheme for the model that is fast enough to allow for probabilistic methods, such as Monte Carlosimulations, […]

Cuda and OpenCL are aimed at programmers developing parallel applications targeting GPUs and embedded micro-processors. These systems often have explicitly managed memories exposed directly though a notion of disjoint address spaces. OpenCL address spaces are based on a similar concept found in Embedded C. A limitation of OpenCL is that a specific pointer must be […]

This paper investigates the development of a molecular dynamics code that is highly portable between architectures. Using OpenCL, we develop an implementation of Sandia’s miniMD benchmark that achieves good levels of performance across a wide range of hardware: CPUs, discrete GPUs and integrated GPUs. We demonstrate that the performance bottlenecks of miniMD’s short-range force calculation […]

Wide baseline matching is the state of the art for object recognition and image registration problems in computer vision. Robust feature descriptors can give vast improvements in the quality and speed of subsequent steps, but intensive computation is still required. With the release of general purpose parallel computing interfaces, opportunities for increases in performance arise. […]