high performance computing on graphics processing units: hgpu.org

Co-located with 27th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2013). his workshop aims to bring the programming community together to explore and discuss various options to make programming heterogeneous systems less challenging and more interesting. The workshop seeks to explore programming methodologies in the form of directive-based approaches, language extensions, novel tools and […]

Concurrency has recently come to the forefront of computing as multi-core processors become more and more common. General purpose graphics processing unit computing brings with them new language support for dealing with co-processor environments such as OpenCL and CUDA. Programming language support for multi-core architectures introduces a fundamentally new mechanism for modularity – a kernel. […]

The parallelized algorithm for hyperspectral biometrics uses the processing power of a GPU (Graphical Processing Unit) to compare hyperspectral images of people’s faces. The feature extraction algorithm first retrieves uniquely identifiable features from raw hyperspectral data from 64 bands and creates both a database and individual target files. Using these files, the comparison algorithm written […]

The reconstruction and simulation of collision events is a major task in modern HEP experiments involving several ten thousands of standard CPUs. On the other hand the graphics processors (GPUs) have become much more powerful and are by far outperforming the standard CPUs in terms of floating point operations due to their massive parallel approach. […]

Considering the digital simulation of complex systems, General-Purpose Computing on Graphics Processing Units (GPGPU) is a relevant approach for addressing scalability issues. However, GPU programming is a very specific approach that strongly limits both the accessibility and the re-usability of the frameworks developed using GPGPU. This paper presents our approach for the integration of GPU […]

A novel metric is introduced to compare the supercomputing resources available to academic researchers on a national basis. Data from the supercomputing Top 500 and the top 500 universities in the Academic Ranking of World Universities (ARWU) are combined to form the proposed "500/500" score for a given country. Australia scores poorly in the 500/500 […]

The CUDA programming model provides better abstraction for GPU programming. However, it is still hard to write programs with CUDA because both some specific techniques and knowledge about GPU architecture is required. Hence, many programming frameworks for CUDA have been developed. OpenMPC is one of them based on OpenMP. OpenMPC s an easy-to-write framework for […]

We present a parallel Preconditioned Bi-Conjugate Gradient Stabilized(BICGstab) solver for the Poisson problem. Given a real, nosymmetric and positive definite coefficient matrix, the parallized Preconditioned BICGstab – solver is able to find a solution for that system by exploiting the massive compute power of todays GPUs. Comparing sequential CPU implementations and that algorithm.we achieve a […]

GPGPU computing offers extraordinary increases in pure processing power for parallelizable applications. In IceCube we use GPUs for ray-tracing of cherenkov photons in the Antarctic ice as part of detector simulation. We report on how we implemented the mixed simulation production chain to include the processing on the GPGPU cluster for the IceCube Monte-Carlo production. […]

We present a new technique for bi-scale material editing using Spherical Gaussians (SGs). To represent large-scale appearances, an effective BRDF that is the average reflectance of small-scale details is used. The effective BRDF is calculated from the integral of the product of the Bidirectional Visible Normal Distribution (BVNDF) and BRDFs of small-scale geometry. Our method […]

In recent years, the development in the architecture of graphics processing units (GPUs) has revolutionized the area of high performance computing by offering massive parallelism and performance improvements in many applications including matrix algebra. While it is possible to harness the power of GPUs for dense matrix computations, sparse matrix computations are still complex since […]

Rendering multi-fragment effects using GPUs is attractive for high speed. However, the efficiency is seriously compromised, because ordering fragments on GPUs is not easy and the GPU’s memory may not be large enough to store the whole scene geometry. Hitherto, existing methods have been unsuitable for large models or have required many passes for data […]