high performance computing on graphics processing units: hgpu.org

Using the histogram procedure, this work studies performance determining factors in computing in parallel on SIMD and SIMT devices. Modern graphics pro-cessing units (GPUs) support SIMT, multiple threads running the same instruction, whereas central processing units (CPUs) use SIMD, in which one instruction op-erates on multiple operands. As part of this work, a cross-technology framework […]

The paper describes an approach to the parallel natural join execution on computing clusters with GPU and MIC Coprocessors. This approach is based on a decomposition of natural join relational operator using the column indices and domain-interval fragmentation. This decomposition admits parallel executing the resource-intensive relational operators without data transfers. All column index fragments are […]

Classic path finding algorithms are not adequate in real world path planning, where environment information is incomplete or dynamic and Markov Decision Processes have been used as an alternative. The problem with the MDP formalism is that its state space grows exponentially with the number of domain variables, and its inference methods grow with the […]

We propose a tool-flow methodology that can be applied to analyze and track the performance of OpenCL applications on heterogeneous platforms. Using a case study on a datacenter representative workload, we evaluate our tool flow on three distinct heterogeneous platforms and demonstrate how it can be employed more widely to provide insight and track attainable […]

MXNet is a multi-language machine learning (ML) library to ease the development of ML algorithms, especially for deep neural networks. Embedded in the host language, it blends declarative symbolic expression with imperative tensor computation. It offers auto differentiation to derive gradients. MXNet is computation and memory efficient and runs on various heterogeneous systems, ranging from […]

We present an idea of efficient query answering over an RDF dataset employing a consumer-grade graphic card for an efficient computation. We consider tree-shaped SPARQL queries and static datasets, to facilitate data mining over RDF graphs in warehouse-like setups. Reasons to see the poster: a) presentation of the approach with examples; b) possibility of discussion […]

Deep learning methods are proven to be state-of-theart in addressing many challenges in machine learning domains. However, it comes at the cost of high computational requirements and energy consumption. The emergence of Processing In Memory (PIM) with diestacking technology presents an opportunity to speed up deep learning computation and reduce energy consumption by providing low-cost […]

A graphics processing unit (GPU) parallelization approach was implemented to improve the efficiency of nonlinear dynamic analysis. The GPU parallelization approach speeded up the computation of implicit time integration and reduced total calculation time. In addition, a parallel equations solver is introduced to solve the equation system. Numerical examples of reinforced concrete (RC) frames were […]

Process variation –deviation in parameters from their nominal specifications– threatens to slow down and even pause technological scaling and mitigation of it is the way to continue the benefits of chip miniaturization. In this paper, we present a survey of architectural techniques for managing process variation (PV) in modern processors. We also classify these techniques […]

The need to transfer data through PCI Express bus is considered as one of main bottlenecks in programming for manycore coprocessors and GPUs. This paper focuses on using data compression methods, such as RLE, Null Suppression, LZSS and combination of RLE and Null Suppression to increase efficiency of data transfer between main memory and coprocessor. […]

This thesis reviews the parallel languages according to their computational complexities, in terms of time, while using sorting algorithms coded in CUDA and OpenMP. The thesis evaluates the solution for parallelism at a maintainable cost of money and other efforts, for achieving acceptable results of timing when compared to parallel languages together, as well as […]

The implementations of 2D vortex element method adapted to different types of parallel computers are considered. The developed MPI-implementation provides close to linear acceleration for small number of computational cores and approximately 40-times acceleration for 80-cores cluster when solving model problem. OpenMP-based modification allows to obtain 5% additional acceleration due to shared memory usage. Approximate […]