high performance computing on graphics processing units: hgpu.org

Fast Fourier Transform is one of the most important numerical algorithms in history. It has wide range of applications: audio signal processing, medical imaging, image processing, pattern recognition, computational chemistry, error correcting codes and spectral methods for PDE’s. The goal of this project is to implement an OpenCL based FFT algorithm that has comparable performance […]

PURPOSE: Optoacoustic tomography (OAT) is inherently a three-dimensional (3D) inverse problem. However, most studies of OAT image reconstruction still employ two-dimensional (2D) imaging models. One important reason is because 3D image reconstruction is computationally burdensome. The aim of this work is to accelerate existing image reconstruction algorithms for 3D OAT by use of parallel programming […]

Hybrid computational architectures based on the joint power of Central Processing Units and Graphic Processing Units (GPUs) are becoming popular and powerful hardware tools for a wide range of simulations in biology, chemistry, engineering, physics, etc.. In this paper we present a comparison of performance of various GPUs available on market when applied to the […]

We present an interface and an implementation of the General Matrix Multiply (GEMM) routine for multiple small matrices processed simultaneously on NVIDIA graphics processing units (GPUs). We focus on matrix sizes under 16. The implementation can be easily extended to larger sizes. For single precision matrices, our implementation is 30% to 600% faster than the […]

Power-hungry Graphics processing unit (GPU) accelerators are ubiquitous in high performance computing data centers today. GPU virtualization frameworks introduce new opportunities for effective management of GPU resources by decoupling them from application execution. However, power management of GPU-enabled server clusters faces significant challenges. The underlying system infrastructure shows complex power consumption characteristics depending on the […]

Applications exhibiting irregular behavior through poor memory locality have been a constant challenge for high-performance computing. Architectures supporting hardware multithreading (e.g. Tera MTA and Cray XMT) have been shown to deliver superior performance on such applications by masking memory latency. FPGAs have outperformed traditional architectures on applications that exhibit very large spatial locality and where […]

Fully utilizing the power of modern heterogeneous systems requires judiciously dividing work across all of the available computational devices. Existing approaches for partitioning work require offline training and generate fixed partitions that fail to respond to fluctuations in device performance that occur at run time. We present a novel dynamic approach to work partitioning that […]

In this paper we describe the extension of system FOTOM capabilities with respect to segmentation of specific mining images. We focus on methods that are inherently resistant against noise present in experimental pit at VSB Technical University. Here, we describe procedures employing proven active contours and evolutionary algorithms for recognizing points of interest in the […]

We present a highly scalable algorithm for multiplying sparse multivariate polynomials represented in a distributed format. This algo- rithm targets not only the shared memory multicore computers, but also computers clusters or specialized hardware attached to a host computer, such as graphics processing units or many-core coprocessors. The scal- ability on the large number of […]

Atomic instructions are a key ingredient of codes that operate on irregular data structures like trees and graphs. It is well known that atomics can be expensive, especially on massively parallel GPUs, and are often on the critical path of a program. In this paper, we present two high-level methods to eliminate atomics in irregular […]

One of the most striking features of quantum mechanics is the exponential growth of resources, required to find the states of a composite system, with the size of the system. This also is the origin of the two main bottlenecks in numerical studies of complex quantum systems, that are (i) diagonalizations of big matrices and […]

Multiplying large integers is an operation that has many applications in Computational Science. Many cryptographic algorithms require operations on very large subsets of the integer numbers. Using Fast Fourier Transforms (FFT) and Graphics Processing Unit (GPU), we can speed up integer multiplication and make an effective multiplication algorithm. CUDA technology used to perform FFT on […]