high performance computing on graphics processing units: hgpu.org

With their high computation throughput and outstanding performance-per-watt figures, the graphics processing units (GPU) are becoming increasingly important for high-performance computing (HPC) systems. Existing GPU execution environment restricts the GPU usage to local host node. This is suitable for standalone computer nodes, but becomes inefficient for HPC systems that consist of a large number of […]

Research scientists and medical professionals use imaging technology, such as computed tomography (CT) and magnetic resonance imaging (MRI) to measure a wide variety of biological and physical objects. The increasing sophistication of imaging technology creates demand for equally sophisticated computational techniques to analyze and visualize the image data. Analysis and visualization codes are often crafted […]

Modern programmers must exploit parallelism for performance gains, possibly through the use of an attached or on-chip GPU. To take advantage of the GPU in C++ programs, the programmer must use either a new language (CUDA or OpenCL) or an external library (Thrust). Rather than requiring that programmers learn new tools, modify existing code, and […]

Clusters of seemingly homogeneous compute nodes are increasingly heterogeneous within each node due to replication and distribution of node-level subsystems. This intra-node heterogeneity can adversely affect program execution performance by inflicting additional data-access costs when accessing non-local data. In this work-in-progress paper, we present extensions to the Cbench Scalable Testing Framework for analyzing main memory […]

In the past, evaluating the architectural innovation of parallel computing devices relied on a benchmark suite based on existing programs, e.g., EEMBC or SPEC. However, with the growing ubiquity of parallel computing devices, we argue that it is unclear how best to express parallel computation, and hence, a need exists to identify a higher level […]

The design of graphics processing unit (GPU) audio signals processing extensions to Pure Data (Pd) is discussed with attention to future growth in GPU computing and the complexity of programming a general solution. An implementation named PdCUDA is presented for use of GPU general programming capability for audio signals processing with Pd and the CUDA […]

We develop a highly optimized code for simulating the Edwards-Anderson Heisenberg model on graphics processing units (GPUs). Using a number of computational tricks such as tiling, data compression and appropriate memory layouts, the simulation code combining over-relaxation, heat bath and parallel tempering moves achieves a peak performance of 0.29 ns per spin update on realistic […]

High-performance streams of (pseudo) random numbers are crucial for the efficient implementation for countless stochastic algorithms, most importantly, Monte Carlo simulations and molecular dynamics simulations with stochastic thermostats. A number of implementations of random number generators has been discussed for GPU platforms before and some generators are even included in the CUDA supporting libraries. Nevertheless, […]

In this work, we have explored the advantages and drawbacks of using GPUs instead of CPUs in the calculation of a standard 2-point correlation function algorithm, which is useful for the analysis of Large Scale Structure of galaxies. Taking into account the huge volume of data foreseen in upcoming surveys, our main goal has been […]

Stochastic Differential Equations are important in many models of various physical or artificial phenomena. To get meaningful results it is desirable to solve the initial value numerical integration problem for a sufficiently large ensemble of realizations. Each element of the ensemble has the same form, thus exposing inherent data-parallelism. We implemented a cross-platform library written […]

We recast the Cosegmentation problem using Random Walker (RW) segmentation as the core segmentation algorithm, rather than the traditional MRF approach adopted in the literature so far. Our formulation is similar to previous approaches in the sense that it also permits Cosegmentation constraints (which impose consistency between the extracted objects from >= 2 images) using […]

Stencil computations arise in many scientific computing domains, and often represent time-critical portions of applications. There is significant interest in offloading these computations to high-performance devices such as GPU accelerators, but these architectures offer challenges for developers and compilers alike. Stencil computations in particular require careful attention to off-chip memory access and the balancing of […]