high performance computing on graphics processing units: hgpu.org

In spiking neural networks, asynchronous spike events are processed in parallel by neurons. Emulations of such networks are traditionally computed by CPUs or realized using dedicated neuromorphic hardware. In many neuromorphic systems, the address-event-representation (AER) is used for spike communication. In this paper we present the acceleration of AER based spike processing using a graphics […]

In this paper we describe a double precision floating point sparse matrix-vector multiplier (SpMV) and its performance as implemented on a Convey HC-1 reconfigurable computer. The primary contributions of this work are a novel streaming reduction architecture for floating point accumulation, a novel on-chip cache optimized for streaming compressed sparse row (CSR) matrices, and end-to-end […]

SPICE based circuit simulation is a traditional workhorse in the VLSI design process. Given the pivotal role of SPICE in the IC design flow, there has been significant interest in accelerating SPICE. Since a large fraction (on average 75%) of the SPICE runtime is spent in evaluating transistor model equations, a significant speedup can be […]

In this paper we present two efficient GPU-based visual hull computation algorithms. We compare them in terms of performance using image sets of varying size and different voxel resolutions. In addition, we present a real-time 3D reconstruction system which uses the proposed GPU-based reconstruction method to achieve real-time performance (30 fps) using 16 cameras and […]

Quadrature based methods for numerical integration provide a means of quickly and accurately pricing financial products such as options. These methods can be applied to multi-dimensional products, such as options on multiple underlying assets, but suffer from an exponential increase in computational complexity as the dimension increases. This paper examines the theoretical complexity of quadrature […]

In this article, we investigate using multi-core graphics processing units (GPUs) for video encoding and decoding. After an overview of video coding and GPUs, we review some previous work on structuring video coding modules so that the massive parallel processing capability of GPUs can be harnessed. We also review previous work on partitioning the video […]

We present a fast parallel algorithm to compute the nonequispaced fast Fourier transform on commodity graphics hardware (the GPU). We focus particularly on a novel implementation of the convolution step in the transform as it was previously its most time consuming part. We describe the performance for two common sample distributions in medical imaging (radial […]

This article presents a real-time GPU-based post-filtering method for rendering acceptable depth-of-field effects suited for virtual reality. Blurring is achieved by nonlinearly interpolating mipmap images generated from a pinhole image. Major artifacts common in the post-filtering techniques such as bilinear magnification artifact, intensity leakage, and blurring discontinuity are practically eliminated via magnification with a circular […]

Graphics processing units (GPUs) have recently attracted a lot of interest in several fields struggling with massively large computation tasks. The application of a GPU for fast and accurate transient stability simulation of the large-scale power systems is presented in this paper. The computationally intensive parts of the simulation were offloaded to the GPU to […]

We present the first parallel surface reconstruction algorithm that runs entirely on the GPU. Like existing implicit surface reconstruction methods, our algorithm first builds an octree for the given set of oriented points, then computes an implicit function over the space of the octree, and finally extracts an isosurface as a watertight triangle mesh. A […]

Graphics processing units (GPUs) are a powerful tool for numerical computation. The GPU architecture and computational model are uniquely designed for high-resolution high-speed grid-based calculations. This capability can be utilized to accelerate certain classes of compute-intensive radar signal processing algorithms. Characteristics of a problem well-suited for computation on a GPU include high levels of data […]

GPU-based transmission simulations with different channel counts (1~81) are used to determine the minimum required channel number for correctly simulating fiber nonlinearities that impact 40G/100G CP-QPSK signals in dispersion un-compensated transmission systems.