high performance computing on graphics processing units: hgpu.org

Heterogeneous programming complicates software development. We present CLOP, a platform that embeds code targeting heterogeneous compute devices in a convenient and clean way, allowing unobstructed data flow between the host code and the devices, reducing the amount of source code by an order of magnitude. The CLOP compiler uses the standard facilities of the D […]

The efficiency of boundary element methods depends crucially on the time required for setting up the stiffness matrix. The far-field part of the matrix can be approximated by compression schemes like the fast multipole method or $mathcal{H}$-matrix techniques. The near-field part is typically approximated by special quadrature rules like the Sauter-Schwab technique that can handle […]

We propose a method to perform collision detection with cloths with ray-tracing. Our method is able to perform collision detection between cloths and volumetric objects (rigid or deformable) as well as collision detection between cloths (including auto-collision). Our method casts rays between objects to perform collision detection, and an inversion-handling algorithm is introduced to correct […]

Bidirectional Long Short-Term Memory Recurrent Neural Network (BLSTM-RNN) has been shown to be very effective for tagging sequential data, e.g. speech utterances or handwritten documents. While word embedding has been demoed as a powerful representation for characterizing the statistical properties of natural language. In this study, we propose to use BLSTM-RNN with word embedding for […]

* Call for Papers * Now in its fourth year, the International Workshop on OpenCL (IWOCL) will be hosted by TU Wien in Vienna, Austria, at the C3 Convention Center on April 19th – 21st 2016. April 19th is reserved for an Advanced Hands On OpenCL tutorial with April 20th – 21st consisting of a […]

1st SYCL workshop (SYCL’16) – co-located with PPoPP’16 Barcelona, Spain Sunday, 13th March, 2016 http://conf.researchr.org/track/PPoPP-2016/SYCL-2016-papers SYCL (sɪkəl – as in sickle) is a royalty-free, cross-platform C++ abstraction layer that builds on the underlying concepts, portability and efficiency of OpenCL, while adding the ease-of-use and flexibility of C++. For example, SYCL enables single source development where […]

The work deals with assessing the quality of a multi-stage Riemann solver for relativistic hydrodynamic simulations of heavy-ion collisions. The physical system is described using hydrodynamic conservation laws and then solved numerically. Because of the nature of such hydrodynamic simulations the numerical method has to cope with problems containing both strong discontinuities and smooth solutions, […]

In this paper we consider the pair-wise sequence alignment problem with gaps, which is motivated by the resequencing problem that requires to assemble short reads sequences into a genome sequence by referring to a reference sequence. The problem has been studied before for single gap and bounded number of gaps. For single gap, there was […]

GPUs can enable significant performance improvements for certain classes of data parallel applications and are widely used in recent computer systems. However, GPU execution currently requires explicit low-level operations such as 1) managing memory allocations and transfers between the host system and the GPU, 2) writing GPU kernels in a low-level programming model such as […]

High-level languages such as Java increase both productivity and portability with productive language features such as managed runtime, type safety, and precise exception semantics. Additionally, Java 8 provides parallel stream APIs with lambda expressions to facilitate parallel programming for mainstream users of multi-core CPUs and many-core GPUs. These high-level APIs avoid the complexity of writing […]

We report on our efforts to implement overlap fermions on NVIDIA GPUs using CUDA, commenting on the algorithms used, implemetation details, and the performance of our code.

Convolutional networks (ConvNets) have become a popular approach to computer vision. It is important to accelerate ConvNet training, which is computationally costly. We propose a novel parallel algorithm based on decomposition into a set of tasks, most of which are convolutions or FFTs. Applying Brent’s theorem to the task dependency graph implies that linear speedup […]