high performance computing on graphics processing units: hgpu.org

Modern graphics processing units (GPUs) provide high computational power which can significantly decrease simulation time. We present two implementations of the FDTD algorithm on GPU and compare their performance with the CPU version.

We present a Graphics Processing Unit (GPU) parallelization of the computation of the price of cross-currency interest rate derivatives via a Partial Differential Equation (PDE) approach. In particular, we focus on the GPU-based parallel computation of the price of long-dated foreign exchange interest rate hybrids, namely Power Reverse Dual Currency (PRDC) swaps with Bermudan cancelable […]

In this paper we evaluate the potential for using an NVIDIA graphics processing unit (GPU) to accelerate high precision integer multiplication. The reported peak vector performance for a typical GPU appears to offer considerable potential for accelerating such a regular computation. Because of limitations in the on-chip memory, the high cost of kernel launches, and […]

Graphics processor (GPU) architectures have evolved rapidly in recent years with increasing performance demanded by 3D graphics applications such as games. However, challenges exist in integrating complex GPUs into mobile devices because of power and energy constraints, motivating the need for energy efficiency in GPUs. While a significant amount of power optimisation research effort has […]

Sequence alignment algorithms such as the Smith-Waterman algorithm are among the most important applications in the development of bioinformatics. Sequence alignment algorithms must process large amounts of data which may take a long time. Here, we introduce our Adaptive Hybrid Multiprocessor technique to accelerate the implementation of the Smith-Waterman algorithm. Our technique utilizes both the […]

An efficient micromagnetic solver running on graphics processing units (GPU) is demonstrated. The solver implements a nonuniform grid interpolation method (NGIM) to compute the superposition integral for the magnetostatic field with operations and memory requirements. The NGIM divides the computational domain into a hierarchy of boxes containing sources and observers, and it uses spatial interpolation […]

The Discrete Wavelet Transform (DWT) has a wide range of applications from signal processing to video and image compression. We show that this transform, by means of the lifting scheme, can be performed in a memory and computation-efficient way on modern, programmable GPUs, which can be regarded as massively parallel coprocessors through NVidia’s CUDA compute […]

In this paper, acceleration on the GPU for option pricing by the COS method is demonstrated. In particular, both European and Bermudan options will be discussed in detail. For Bermudan options, we consider both the Black-Scholes model and Levy processes of infinite activity. Moreover, the influence of the number of terms in the Fourier-cosine expansion, […]

In this manuscript, we present an implementation of a correlation method for face recognition application on GPU. Our correlator is based on the famous "4f" setup and the use of a Phase Only Filter (POF). Traditionally, the correlation method is implemented using optical components for real-time application. Unfortunately, optical implementation is complex and has exorbitant […]

This paper presents techniques for tuning an accelerated preconditioned conjugate gradient solver with a multilevel preconditioner. The solver is optimized for a fast solution of sparse systems of equations arising in computational electromagnetics in a finite element method using higher order elements. The goal of the tuning is to increase the throughput while at the […]

Due to widespread broadband connections in normal households, the use of video chats via Internet is no longer limited to business meetings. However, the camera configuration usually makes it impossible to achieve direct eye contact between the conversational partners. This effect can be compensated using virtual view synthesis methods based on disparity maps. The virtual […]

MOTIVATION: The only algorithm guaranteed to find the optimal local alignment is the Smith-Waterman. It is also one of the slowest due to the number of computations required for the search. To speed up the algorithm, Single-Instruction Multiple-Data (SIMD) instructions have been used to parallelize the algorithm at the instruction level. RESULTS: A faster implementation […]