high performance computing on graphics processing units: hgpu.org

This paper is an introduction to general-purpose computing on graphics processing units. This involves taking advantage of the parallel processing power of modern graphics cards to do general purpose computation. The CUDA architecture used for general purpose computations on NVIDIA graphics cards is described, and important features affecting the run times of CUDA programs are […]

A parallel prefix network of width n takes n inputs, a_1, a_2, … , a_n, and computes each yi = a_1 o a_2 o … o a_i for 1 <= i <= n, for an associative operator o. This is one of the fundamental problems in computer science, because it gives insight into how parallel […]

As the resolution of output device increases, the demand of high resolution contents has become more eagerly. Therefore, the image superresolution algorithms become more important. In digital image, the edges in the image are related to human perception heavily. Because of this, most recent research topics tend to enhance the image edges to achieve better […]

Logic simulation of a VLSI chip is a computationally intensive process. There exists an urgent need to map functional validation algorithms onto parallel architectures to aid hardware designers in meeting time-to-market constraints. In this paper, we propose three novel methods for logic simulation of combinational circuits on GPGPUs. Initial experiments run on two methods using […]

Graphics processors (GPUs) are highly parallel devices that promise high performance, and they are now flexible enough to be used for general-purpose computing. A programming language based on implicitly data-parallel collective array operations can permit high-level, effective programming of GPUs. I describe three optimizations for such a language: automatic use of GPU shared memory cache, […]

Embedded systems are designed to perform a specific set of tasks, and are frequently found in mobile, power-constrained environments. There is growing interest in the use of parallel computation as a means to increase performance while reducing power consumption. In this paper, we highlight fundamental limits to what can and cannot be improved by parallel […]

Fourier transform, wavelet transformation, and Hilbert-Huang transformation (HHT) can be used to discuss the frequency characteristics of linear and stationary signals, the time-frequency features of linear and non-stationary signals, the time-frequency features of non-linear and non-stationary signals, respectively [1-6]. HHT is a combination of empirical mode decomposition (EMD) and Hilbert spectral analysis. EMD uses the […]

Over the last 20 years, the open-source community has provided more and more software on which the world’s high-performance computing systems depend for performance and productivity. The community has invested millions of dollars and years of effort to build key components. However, although the investments in these separate software elements have been tremendously valuable, a […]

The sparse grid discretization technique enables a compressed representation of higher-dimensional functions. In its original form, it relies heavily on recursion and complex data structures, thus being far from well-suited for GPUs. In this paper, we describe optimizations that enable us to implement compression and decompression, the crucial sparse grid algorithms for our application, on […]

This paper extends the stochastic transparency algorithm that models partial coverage to also model wavelength-varying transmission. It then applies this to the problem of casting shadows between any combination of opaque, colored transmissive, and partially covered (i.e., ?-matted) surfaces in a manner compatible with existing hardware shadow mapping techniques. Colored Stochastic Shadow Maps have a […]

Performance of applications running on GPUs is mainly affected by hardware occupancy and global memory latency. Scientific applications that rely on analysis using unstructured grids could benefit from the high performance capabilities provided by GPUs, however, its memory access pattern and algorithm limit the potential benefits. In this paper we analyze the algorithm for unstructured […]

We present a novel 2-approximation algorithm for deploying stream graphs on multicore computers and a stream graph transformation that eliminates bottlenecks. The key technical insight is a data rate transfer model that enables the computation of a "closed form", i.e., the data rate transfer function of an actor depending on the arrival rate of the […]