## Posts

Nov, 9

### High Performance Direct Gravitational N-body Simulations on Graphics Processing Units: An implementation in CUDA (thesis)

At the end of 2006 NVIDIA introduced a new generation of graphical processing units (GPUs) (the so called G80 architecture). These GPUs are more powerful than any of the GPUs released before; they offer up to 350 billion floating-point operations per second (GFLOP/s) in certain situations. With the introduction of this hardware NVIDIA released a […]

Nov, 9

### High Performance Direct Gravitational N-body Simulations on Graphics Processing Units

We present the results of gravitational direct $N$-body simulations using the commercial graphics processing units (GPU) NVIDIA Quadro FX1400 and GeForce 8800GTX, and compare the results with GRAPE-6Af special purpose hardware. The force evaluation of the $N$-body problem was implemented in Cg using the GPU directly to speed-up the calculations. The integration of the equations […]

Nov, 9

### Running the NIM Next-Generation Weather Model on GPUs

We are using GPUs to run a new weather model being developed at NOAA’s Earth System Research Laboratory (ESRL). The parallelization approach is to run the entire model on the GPU and only rely on the CPU for model initialization, I/O, and inter-processor communications. We have written a compiler to convert Fortran into CUDA, and […]

Nov, 9

### Nonlinear optimization with a massively parallel Evolution Strategy-Pattern Search algorithm on graphics hardware

This paper presents a massively parallel Evolution Strategy-Pattern Search Optimization (ES-PS) algorithm with graphics hardware acceleration on bound constrained nonlinear continuous optimization problems. The algorithm was specifically designed for a graphic processing unit (GPU) hardware platform featuring ‘Single Instruction Multiple Thread’ (SIMT). Evolution Strategy is a population-based evolutionary algorithm for solving complex optimization problems. GPU […]

Nov, 9

### Deployment of parallel linear genetic programming using GPUs on PC and video game console platforms

We present a general method for deploying parallel linear genetic programming (LGP) to the PC and Xbox 360 video game console by using a publicly available common framework for the devices called XNA (for “XNA’s Not Acronymed”). By constructing the LGP within this framework, we effectively produce an LGP “game” for PC and XBox 360 […]

Nov, 9

### Fast and informative flow simulations in a building by using fast fluid dynamics model on graphics processing unit

Fast indoor airflow simulations are necessary for building emergency management, preliminary design of sustainable buildings, and real-time indoor environment control. The simulation should also be informative since the airflow motion, temperature distribution, and contaminant concentration are important. Unfortunately, none of the current indoor airflow simulation techniques can satisfy both requirements at the same time. Our […]

Nov, 9

### Gravitational tree-code on graphics processing units: implementation in CUDA

We present a new very fast tree-code which runs on massively parallel Graphical Processing Units (GPU) with NVIDIA CUDA architecture. The tree-construction and calculation of multipole moments is carried out on the host CPU, while the force calculation which consists of tree walks and evaluation of interaction list is carried out on the GPU. In […]

Nov, 9

### Efficient pseudo-random number generators for biomolecular simulations on graphics processors

Langevin Dynamics, Monte Carlo, and all-atom Molecular Dynamics simulations in implicit solvent, widely used to access the microscopic transitions in biomolecules, require a reliable source of random numbers. Here we present the two main approaches for implementation of random number generators (RNGs) on a GPU, which enable one to generate random numbers on the fly. […]

Nov, 9

### Massively parallel differential evolution-pattern search optimization with graphics hardware acceleration: an investigation on bound constrained optimization problems

This paper presents a novel parallel Differential Evolution (DE) algorithm with local search for solving function optimization problems, utilizing graphics hardware acceleration. As a population-based meta-heuristic, DE was originally designed for continuous function optimization. Graphics Processing Units (GPU) computing is an emerging desktop parallel computing technology that is becoming popular with its wide availability in […]

Nov, 9

### Viewpoints: A high-performance high-dimensional exploratory data analysis tool

Scientific data sets continue to increase in both size and complexity. In the past, dedicated graphics systems at supercomputing centers were required to visualize large data sets, but as the price of commodity graphics hardware has dropped and its capability has increased, it is now possible, in principle, to view large complex data sets on […]

Nov, 9

### ABC-SysBio–approximate Bayesian computation in Python with GPU support

Motivation: The growing field of systems biology has driven demand for flexible tools to model and simulate biological systems. Two established problems in the modeling of biological processes are model selection and the estimation of associated parameters. A number of statistical approaches, both frequentist and Bayesian, have been proposed to answer these questions. Results: Here […]

Nov, 9

### DiVinE-CUDA – A Tool for GPU Accelerated LTL Model Checking

In this paper we present a tool that performs CUDA accelerated LTL Model Checking. The tool exploits parallel algorithm MAP adjusted to the NVIDIA CUDA architecture in order to efficiently detect the presence of accepting cycles in a directed graph. Accepting cycle detection is the core algorithmic procedure in automata-based LTL Model Checking. We demonstrate […]