high performance computing on graphics processing units: hgpu.org

We study the use of polar codes for both discrete and continuous variables Quantum Key Distribution (QKD). Although very large blocks must be used to obtain the efficiency required by quantum key distribution, and especially continuous variables quantum key distribution, their implementation on generic x86 CPUs is practical. Thanks to recursive decoding, they exhibit excellent […]

Computed tomography (CT) to cone-beam computed tomography (CBCT) deformable image registration (DIR) is a crucial step in adaptive radiation therapy. Current intensity-based registration algorithms, such as demons, may fail in the context of CT-CBCT DIR because of inconsistent intensities between the two modalities. In this paper, we propose a variant of demons, called Deformation with […]

Simulation of x-ray projection images plays an important role in cone beam CT (CBCT) related research projects. A projection image contains primary signal, scatter signal, and noise. It is computationally demanding to perform accurate and realistic computations for all of these components. In this work, we develop a package on GPU, called gDRR, for the […]

We present a framework to interactively volume-render three-dimensional data cubes using distributed ray-casting and volume bricking over a cluster of workstations powered by one or more graphics processing units (GPUs) and a multi-core CPU. The main design target for this framework is to provide an in-core visualization solution able to provide three-dimensional interactive views of […]

High performance computing (HPC) is a very attractive and relatively new area of research, which gives promising results in many applications. In this paper HPC is used for pricing of American options. Although the American options are very significant in computational finance; their valuation is very challenging, especially when the Monte Carlo simulation techniques are […]

The paper introduces an optimized multicore CPU implementation of the genetic algorithm and compares its performance with a fine-tuned GPU version. The main goal is to show the true performance relation between modern CPUs and GPUs and eradicate some of myths surrounding GPU performance. It is essential for the evolutionary community to provide the same […]

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 […]