high performance computing on graphics processing units: hgpu.org

In this paper we investigate the use of GPUs as digital beamformers. We specify a parallel implementation of a beamformer in time and frequency domain and measure its performance. We also give examples of the processing limits of NVIDIA Geforce 8800 GPU with respect to application parameters: number of sensors, sampling frequency, bandwidth, and number […]

By organizing the control mesh of subdivision in texture memory so that irregularities occur strictly inside independently refinable fragment meshes, all major features of subdivision algorithms can be realized in the framework of highly parallel stream processing. Our implementation of Catmull-Clark subdivision as a GPU kernel in programmable graphics hardware can model features like semi-smooth […]

This workshop will cover advances and innovations in graphic processor unit (GPU) capabilities and functionality into nontraditional, general-purpose computing as an adjunct vector/matrix processor. Examples include game physics, image processing, scientific computing, sorting and database query processing, to name a few.This workshop consists of invited speakers and poster presenters who provide insights into GP2 practice […]

Simulations of light scattering from nano-structured surface areas require substantial amount of computing time. The emergence of General Purpose Graphics Processing Units (GPGPUs) as affordable PC SIMD arithmetic coprocessors brings the necessary computing power to modern desktop PCs. In this paper we examine how the computation time of the Finite-Difference Time-Domain (FDTD), a classic numerical […]

State of the art graphics processors provide high processing power and furthermore, the high programmability of GPUs offered by frameworks like CUDA increases their usability as high-performance coprocessors for general-purpose computing. Sorting is well-investigated in Computer Science in general, but (because of this new field of application for GPUs) there is a demand for high-performance […]

The benefits of using Finite-Difference alike methods for coverage prediction comprise highly accurate electromagnetic simulations that serve as a reliable input for wireless networks planning and optimization algorithms. These algorithms usually require several thousands of iterations in order to find the optimal network configuration, so to obtain results within reasonable computation times, the applied propagation […]

Finite-Difference Time-Domain (FDTD) has been proved to be a very useful computational electromagnetic algorithm. However, the scheme based on traditional general purpose processors can be computationally prohibitive and require thousands of CPU hours, which hinders the large-scale application of FDTD. With rapid progress on GPU hardware capability and its programmability, we propose in this paper […]

Heterogeneous systems, systems with multiple processors tailored for specialized tasks, are challenging programming environments. While it may be possible for domain experts to optimize a high performance application for a very specific and well documented system, it may not perform as well or even function on a different system. Developers who have less experience with […]

The use of virtualization to abstract underlying hardware can aid in sharing such resources and in efficiently managing their use by high performance applications. Unfortunately, virtualization also prevents efficient access to accelerators, such as Graphics Processing Units (GPUs), that have become critical components in the design and architecture of HPC systems. Supporting General Purpose computing […]

Centroidal Voronoi tessellations (CVT) are widely used in computational science and engineering. The most commonly used method is Lloyds method, and recently the L-BFGS method is shown to be faster than Lloyds method for computing the CVT. However, these methods run on the CPU and are still too slow for many practical applications. We present […]

Random numbers are extensively used on the GPU. As more computation is ported to the GPU, it can no longer be treated as rendering hardware alone. Random number generators (RNG) are expected to cater general purpose and graphics applications alike. Such diversity adds to expected requirements of a RNG. A good GPU RNG should be […]

We discuss hardware and software aspects of GPGPU, specifically focusing on NVIDIA cards and CUDA, from the viewpoints of parallel computing. The major weak points of GPU against newest supercomputers are identified to be and summarized as only four points: large SIMD vector length, small memory, absence of fast L2 cache, and high register spill […]