high performance computing on graphics processing units: hgpu.org

We present CrowdCL, an open-source framework for the rapid development of volunteer computing and OpenCL applications on the web. Drawing inspiration from existing GPU libraries like PyCUDA, CrowdCL provides an abstraction layer for WebCL aimed at reducing boilerplate and improving code readability. CrowdCL also provides developers with a framework to easily run computations in the […]

Shared memory multi-core processor technology has seen a drastic development with faster and increasing number of processors per chip. This new architecture challenges computer programmers to write code that scales over these many cores to exploit full computational power of these machines. Shared-memory parallel programming paradigms such as OpenMP and Intel Threading Building Blocks (TBB) […]

With the proliferation of general purpose computation, GPUs are becoming extremely important to significantly improve system performance for many computing systems, including embedded systems. Running massively parallel kernels on GPUs is challenging for system’s overall performance especially when a large number of workloads (kernels) are running together. In this paper, we establish a mechanism to […]

Molecular dynamics simulations are a very useful tool to study the behavior and interaction of atoms and molecules in chemical and bio-molecular systems. With the fast rising complexity of such simulations hybrid systems with both, multi-core processors (CPUs) and multiple graphics processing units (GPUs), become more and more popular. To obtain an optimal performance this […]

In this paper, we discuss the acceleration of a climate model known as Community Earth System Model (CESM). The use of Graphics Processor Units (GPUs) to accelerate scientific applications that are computationally intensive is well known. This project attempts to extract the performance of GPUs to enable fast execution of CESM to obtain better model […]

We present a simplification algorithm for triangular meshes, implemented on the GPU. The algorithm performs edge collapses driven by a quadric error metric. It uses data parallelism as provided by OpenCL and has no sequential segments in its main iterative structure in order to fully exploit the processing power of the GPU. Our implementation produces […]

Hardware acceleration using FPGAs has shown orders of magnitude reduction in runtime of computationally-intensive applications in comparison to traditional stand-alone computers [1]. This is possible because on an FPGA many computations can be performed at the same time in a truly-parallel fashion. However, parallel computation at a hardware level requires a great deal of expertise, […]

For the past few decades, both the scientific community and the general public have been becoming more aware that the Earth lives in a shooting gallery of small objects. We classify all of these asteroids and comets, known or unknown, that cross Earth’s orbit as near-Earth objects (NEOs). A look at our geologic history tells […]

The Travelling Salesman Problem (TSP) is one of the most studied combinatorial optimization problem which is significant in many practical applications in transportation problems. The TSP problem is NP-hard problem and requires large computation power to be solved by the exact algorithms. In the past few years, fast development of general-purpose Graphics Processing Units (GPUs) […]

We present a generalization of the inertial coupling (IC) [Usabiaga et al. J. Comp. Phys. 2013] which permits the resolution of radiation forces on small particles with arbitrary acoustic contrast factor. The IC method is based on a Eulerian-Lagrangian approach: particles move in continuum space while the fluid equations are solved in a regular mesh […]

This paper presents the development of a two-dimensional (2-D) finite-difference time-domain (FDTD) solver that features reliable calculations and reduced simulation times. The accuracy of computations is guaranteed by specially-designed spatial operators with extended stencils, which are assisted by an optimized version of a high-order leapfrog integrator. Both discretization schemes rely on error-minimization concepts, and a […]

The goal of this work is to explore novel approaches to CUDA accelerated breadth-first search (BFS) algorithm and analyze their application in a state-of-the-art algorithm for graph decomposition into strongly connected components via CUDA capable devices, i.e. GPUs. A previous method [7], as will be shown, does not reasonably work on real-world graphs. Therefore, we […]