high performance computing on graphics processing units: hgpu.org

Intersection of inverted lists is a frequently used operation in search engine systems. Efficient CPU and GPU intersection algorithms for large problem size are well studied. We propose an efficient GPU algorithm for high performance intersection of inverted index lists on CUDA platform. This algorithm feeds queries to GPU in batches, thus can take full […]

Driven by the market demand for high-definition 3D graphics, commodity graphics processing units (GPUs) have evolved into highly parallel, multi-threaded, many-core processors, which are ideal for data parallel computing. Many applications have been ported to run on a single GPU with tremendous speedups using general C-style programming languages such as CUDA. However, large applications require […]

Force directed approach is one of the most widely used methods in graph drawing research. However, the running time is increased intolerablely along with the enlargement of the graph size, which restricts the algorithm’s practicability. By the aid of GPU (graphics processing unit) computing platform, we can speed-up the graph layout with low cost, but […]

Solution of large-scale dense nonsymmetric eigenvalue problem is required in many areas of scientific and engineering computing, such as vibration analysis of automobiles and analysis of electronic diffraction patterns. In this study, we focus on the Hessenberg reduction step and consider accelerating it using GPU. Our main strategy is to use the CUBLAS, an optimized […]

Graphics processing units provide a large computational power at a very low price which position them as an ubiquitous accelerator. Efficient primitives that can expand the range of operations performed on the GPU are thus important. Discrete Range Searching(DRS) is one such primitive with direct applications to string processing, document and text retrieval systems, and […]

The evolution of the graphics processing units (GPU) driven by the computer games business brought a graphics hardware as a high performance, programmable and non-expensive chips. Nowadays, the graphic card has a truly programmable architecture which allows to process data with high parallelism and high memory access rate. That is the key motivation fact for […]

The method Finite Difference Time Domain (FDTD) is widely used in electromagnetic simulations. Since this method is a data intensive and computation intensive problem, there are a lot of initiatives to improve the scalability and the performance of the FDTD. Specifically the use of GPU to accelerate the FDTD is in focus, which has a […]

Nowadays, several industrial applications are being ported to parallel architectures. These applications take advantage of the potential parallelism provided by multiple core processors. Many-core processors, especially the GPUs(Graphics Processing Unit), have led the race of floating-point performance since 2003. While the performance improvement of general- purpose microprocessors has slowed significantly, the GPUs have continued to […]

The generation of molecular conformations and the evaluation of interaction potentials are common tasks in molecular modeling applications, particularly in protein-ligand or protein-protein docking programs. In this work, we present a GPU-accelerated approach capable of speeding up these tasks considerably. For the evaluation of interaction potentials in the context of rigid protein-protein docking, the GPU-accelerated […]

BACKGROUND: In actual surgery, smoke and bleeding due to cauterization processes provide important visual cues to the surgeon, which have been proposed as factors in surgical skill assessment. While several virtual reality (VR)-based surgical simulators have incorporated the effects of bleeding and smoke generation, they are not realistic due to the requirement of real-time performance. […]

The answers to data assimilation questions can be expressed as path integrals over all possible state and parameter histories. We show how these path integrals can be evaluated numerically using a Markov Chain Monte Carlo method designed to run in parallel on a Graphics Processing Unit (GPU). We demonstrate the application of the method to […]

The rapidly increasing number of cores in modern microprocessors is pushing the current high performance computing (HPC) systems into the petascale and exascale era. The hybrid nature of these systems – distributed memory across nodes and shared memory with non-uniform memory access within each node – poses a challenge to application developers. In this paper, […]