high performance computing on graphics processing units: hgpu.org

Intensive home-care surveillance programs are associated with a marked decrease in the need for hospitalization. They can improve the functional statuses of elderly patients with severe congestive diseases. The GPU-based home-care surveillance system is effective and has a major impact on health expenditure than traditional surveillance equipments. In this work, we propose a spike sorting […]

Deformable image registration in the presence of considerable contrast differences and large size and shape changes presents significant research challenges. First, it requires a robust registration framework that does not depend on intensity measurements and can handle large nonlinear shape variations. Second, it involves the expensive computation of nonlinear deformations with high degrees of freedom. […]

We present a software approach to hardware-oriented numerics which builds upon an augmented, previously published set of open-source libraries facilitating portable code development and optimisation on a wide range of modern computer architectures. In order to maximise efficiency, we exploit all levels of parallelism, including vectorisation within CPU cores, the Cell BE and GPUs, shared […]

Stochastic simulations need multiple replications in order to build confidence intervals for their results. Even if we do not need a large amount of replications, it is a good practice to speed-up the whole simulation time using the Multiple Replications In Parallel (MRIP) approach. This approach usually supposes to have access to a parallel computer […]

An option is a financial instrument which derives its value from an underlying asset. There are a wide range of options traded today. Some are simple and plain, like the European options, while others are very difficult to evaluate. Both buyers and sellers continue to look for efficient algorithms and faster technology to price options […]

Structured real world data can be represented with graphs whose structure encodes independence assumptions within the data. Due to statistical advantages over generative graphical models, Conditional Random Fields (CRFs) are used in a wide range of classification tasks on structured data sets. CRFs can be learned from both, fully or partially supervised data, and may […]

The starting point of any lattice QCD computation is the generation of a Markov chain of gauge field configurations. Due to the large number of lattice links and due to the matrix multiplications, generating SU(Nc) lattice QCD configurations is a highly demanding computational task, requiring advanced computer parallel architectures such as clusters of several Central […]

The kd-tree is a fundamental tool in computer science. Among other applications, the application of kd-tree search (by the tree method) to the fast evaluation of particle interactions and neighbor search is highly important, since the computational complexity of these problems is reduced from O(N^2) for a brute force method to O(N log N) for […]

Random number generation continues to be a critical component in much of computational science and the tradeoff between quality and computational performance is a key issue for many numerical simulations. We review the performance and statistical quality of some well known algorithms for generating pseudo random numbers. Graphical Processing Units (GPUs) are a powerful platform […]

In this paper, a novel GPU accelerated scheme for the PK-means gene clustering algorithm is proposed. According to the native particle-pair structure of the PKmeans algorithm, a fragment shader program is tailor-made to process a pair of particles in one pass for the computationintensive portion. As the output channel of a fragment consisting of 4 […]

In this research, we developed a framework to execute genetic algorithms (GA) in various parallel environments. GA researchers can prepare implementations of GA operators and fitness functions using this framework. We have prepared several types of communication library in various parallel environments. Combining GA implementations and our libraries, GA researchers can benefit from parallel processing […]

Molecular Dynamics simulations are an essential tool for many applications. The simulation of large molecules – like proteins – over long trajectories is of high importance e. g. for pharmaceutical, biochemical and medical research. For analyzing these data sets interactive visualization plays a crucial role as details of the interactions of molecules are often affected […]