high performance computing on graphics processing units: hgpu.org

In the recent years, multi-objective particle swarm optimization (MOPSO) has become quite popular in the field of multi-objective optimization. However, due to a large amount of fitness evaluations as well as the task of archive maintaining, the running time of MOPSO for optimizing some difficult problems may be quite long. This paper proposes a parallel […]

We describe an implementation of the Communication-Avoiding QR (CAQR) factorization that runs entirely on a single graphics processor (GPU). We show that the reduction in memory traffic provided by CAQR allows us to outperform existing parallel GPU implementations of QR for a large class of tall-skinny matrices. Other GPU implementations of QR handle panel factorizations […]

In this paper, we propose a fine-grained cycle sharing (FGCS) system capable of exploiting idle graphics processing units (GPUs) for accelerating sequence homology search in local area network environments. Our system exploits short idle periods on GPUs by running small parts of guest programs such that each part can be completed within hundreds of milliseconds. […]

Information retrieval from large databases is becoming crucial for many applications in different fields such as content searching in multimedia objects, text retrieval or computational biology. These databases are usually indexed off-line to enable an acceleration of on-line searches. Furthermore, the available parallelism has been exploited using clusters to improve query throughput. Recently some authors […]

The problem of decomposing a directed graph into its strongly connected components is a fundamental graph problem inherently present in many scientific and commercial applications. In this paper we show how some of the existing parallel algorithms can be reformulated in order to be accelerated by NVIDIA CUDA technology. In particular, we design a new […]

Though researchers in computer graphics have started to use the GPGPU (General Purposed Graphics Processing Unit) method to speed up their procedural programs, these techniques are seldom used in the building simulation field. It is possible to apply the GPGPU method to many simulation scenarios (i.e. human evacuation, shadow simulation) to speed up performance. In […]

High-fidelity geopotential calculation using spherical harmonics (SH) is expensive and relies on recursive non-parallel relations. Here, a global point mascon (PMC) model is proposed that is memory light, extremely simple to implement (at any derivative level), and is naturally amenable to parallelism. The gravity inversion problem is posed classically as a large and dense least […]

The multi-directional (MD) technique is a general purpose tool for optimisation, that is, finding the global maxima or minima of some objective function in a given domain. Any function that produces a relatively continuous surface may therefore be suitable. Using a graphics processing unit (GPU) for MD optimisation demonstrates an increase in speed of up […]

Real-time visualization is an important tool for immediately inspecting results for scientific simulations. Graphics Processing Units (GPUs) as commodity computing devices offer massive parallelism that can greatly improve performance for data-parallel applications. However, a single GPU provides limited support which is only suitable for smaller scale simulations. Multi-GPU computing, on the other hand, allows concurrent […]

Physical simulation is important for a wide range of problems, particularly so in the field of robotics. The need for faster simulation to provide larger amounts of data is increasingly growing. The trend in computing is growing towards more cores as opposed to faster cores, and the graphical processing unit, or GPU, shows great promise […]

In the last years CPU performance increases came with an increase in software development complexity. One of the next big changes in CPU architecture may be so-called hybrid multicore chips, which combine both multicore and manycore technologies on the same chip. Unfortunately, this increase in performance again may lead to an increase in development complexity. […]

Computational power of Graphical Processing Units and multicore CPUs was harnessed by the nuclear data evaluation code SAMMY to speed up computations of large Resonance Parameter Covariance Matrices (RPCMs). This was accomplished by linking SAMMY to vendor-optimized implementations of the matrix-matrix multiplication subroutine of the Basic Linear Algebra Library to compute the most time-consuming step. […]