high performance computing on graphics processing units: hgpu.org

Today, a plethora of parallel execution platforms are available. One platform in particular is the GPGPU – a massively parallel architecture designed for exploiting data parallelism. However, GPGPUS are notoriously difficult to program due to the way data is accessed and processed, and many interconnected factors affect the performance. This makes it an exceptionally challengingtask […]

High-performance scientific applications require more and more compute power. The concurrent use of multiple distributed compute resources is vital for making scientific progress. The resulting distributed system, a so-called Jungle Computing System, is both highly heterogeneous and hierarchical, potentially consisting of grids, clouds, stand-alone machines, clusters, desktop grids, mobile devices, and supercomputers, possibly with accelerators […]

Image processing and pattern recognition algorithms take more time for execution on a single core processor. Graphics Processing Unit (GPU) is more popular now-a-days due to their speed, programmability, low cost and more inbuilt execution cores in it. Most of the researchers started work to use GPUs as a processing unit with a single core […]

The Ray Tracing Visualization Toolkit (rtVTK) is a collection of programming and visualization tools supporting visual analysis of ray-based rendering algorithms. rtVTK leverages layered visualization within the spatial domain of computation, enabling investigators to explore the computational elements of any ray-based renderer. Renderers utilize a library for recording and processing ray state, and a configurable […]

With the emergence of highly multithreaded architectures, performance monitoring techniques face new challenges in efficiently locating sources of performance discrepancies in the program source code. For example, the state-of-the-art performance counters in highly multithreaded graphics processing units (GPUs) report only the overall occurrences of microarchitecture events at the end of program execution. Furthermore, even if […]

In this dissertation we examine the efficiency of GPUs with a limited number of stream processors (up to 32), located in desktops and laptops, in the execution of algorithms such as hashing (MD5, SHA1), encryption (Salsa20) and compression (LZ78). For the implementation part, the OpenCL framework was used under OS X. The graphic cards tested […]

Split-field finite-difference time-domain (SF-FDTD) method can overcome the limitation of ordinary FDTD in analyzing periodic structures under oblique incidence. On the other hand, huge run times of 3D SF-FDTD, is practically a major burden in its usage for analysis and design of nanostructures, particularly when having dispersive media. Here, details of parallel implementation of 3D […]

Graphics processing units (GPUs) are powerful devices capable of rapid parallel computation. GPU programming, however, can be quite difficult, limiting its use to experienced programmers and keeping it out of reach of a large number of potential users. We present Chestnut, a domain-specific GPU parallel programming language for parallel multi-dimensional grid applications. Chestnut is designed […]

This paper presents a side-channel analysis of the bitstream encryption mechanism provided by Xilinx Virtex FPGAs. This work covers our results analyzing the Virtex-4 and Virtex-5 family showing that the encryption mechanism can be completely broken with moderate effort. The presented results provide an overview of a practical real-world analysis and should help practitioners to […]

Structured real world data can be represented with graphs whose structure encodes indepen dence 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 […]

Heterogeneous multi-cores-platforms comprised of both general purpose and accelerator cores-are becoming increasingly common. Further, with processor designs in which there are many cores on a chip, a recent trend is to include functional and performance asymmetries to balance their power usage vs. performance requirements. Coupled with this trend in CPUs is the development of high […]

We consider deployment of the particle filter on modern massively parallel hardware architectures, such as Graphics Processing Units (GPUs), with a focus on the resampling stage. While standard multinomial and stratified resamplers require a sum of importance weights computed collectively between threads, a Metropolis resampler favourably requires only pair-wise ratios between weights, computed independently by […]