high performance computing on graphics processing units: hgpu.org

As general purpose computing on Graphics Processing Units (GPGPU) matures, more complicated scientific applications are being targeted to utilize the data-level parallelism available on a GPU. Implementing physically-based simulation on data-parallel hardware requires preprocessing overhead which affects application performance. We discuss our implementation of physics-based data structures that provide significant performance improvements when used on […]

A new approach to solve the power flow problem based on graphic processing units is presented in this paper. A Newton method is implemented to solve the set of nonlinear equations of the power flow formulation. A parallel kernel for the biconjugate gradient method allows solving the voltage corrections on a graphic processing card. While […]

We consider the use of commodity graphics processing units (GPUs) for the common task of numerically integrating ordinary differential equations (ODEs), achieving speed-ups of up to 115-fold over comparable serial CPU implementations, and 15-fold over multithreaded CPU code with SIMD intrinsics. Using Lorenz ’96 models as a case study, single and double precision benchmarks are […]

Commodity off-the-shelf GPUs lack error checking mechanisms for graphics memory, whereas conventional HPC platforms have used hardware-based ECC for DRAMs. To alleviate this reliability concern, we propose a software-based ECC for GPGPU applications. We add small program codes to normal CUDA programs that compute ECCs for data residing in graphics memory so that transient bit-flips […]

A parallel implementation of root finding on an SIMD application accelerator is reported. These are roots of stochastic differential equations in the computational finance domain which require a stochastic simulation to be performed for each evaluation of the pricing function. Experiments show that a speedup of 15X can be achieved over using a stand-alone CPU […]

Graphics Processing Units (GPUs) are highly parallel Single Instruction Multiple Data (SIMD) engines, with extremely high degrees of available hardware parallelism. The task of implementing a software routine on a GPU currently requires significant manual design, iteration and experimentation. This paper presents an automated approach to partition a software application into kernels (which are executed […]

Understanding the neural circuitry of the retina requires us to map the connectivity of individual neurons in large neuronal tissue sections and analyze signal communication across processes from the electron microscopy images. One of the major bottlenecks in the critical path is the image mosaicing process where 2D slices are assembled from scanned microscopy image […]

In order for scientists to learn more about molecular biology, it is imperative that they have the ability to construct accurate models that predict the reactions of species of molecules. Generating these models using deterministic approaches is not feasible as these models may violate some of the assumptions underlying classical differential equations models (e.g., small […]

Since the introduction of organized trading of options for commodities and equities, computing fair prices for options has been an important problem in financial engineering. A variety of numerical methods, including Monte Carlo methods, binomial trees, and numerical solution of stochastic differential equations, are used to compute fair prices. Traders and brokerage firms constantly strive […]

Since CUDA programing model appeared on the general purpose computations, the developers can extract all the power contained in GPUs (Graphics Processing Unit) across many computational domains. Among these domains, P systems or membrane systems provide a high level computational modeling framework that allows, in theory, to obtain polynomial time solutions to NP-complete problems by […]

The finite element method (FEM) is widely used for numerical solution of partial differential equations. Two computationally expensive tasks have to be performed in FEM – equations assembly and solution of the system of equations. We present mapping of the equations assembly problem for StVenant-Kirchhoff material to GPU computation model and show results of its […]

In recent years, Graphics Processing Units (GPUs) have emerged as a powerful accelerator for general-purpose computations. GPUs are attached to every modern desktop and laptop host CPU as graphics accelerators. GPUs have over a hundred cores with lots of parallelism. Initially, they were used only for graphics applications such as image processing and video games. […]