## Posts

Nov, 9

### Parallel Graph Component Labelling with GPUs and CUDA

Graph component labelling, which is a subset of the general graph colouring problem, is a computationally expensive operation that is of importance in many applications and simulations. A number of data-parallel algorithmic variations to the component labelling problem are possible and we explore their use with general purpose graphical processing units (GPGPUs) and with the […]

Nov, 9

### A molecular docking system using CUDA

A Molecular Docking System enables biologists to check whether two molecular models can be combined at a specific position and remain in their stable states by simulation. It can be used in developing new materials and designing new drugs. Since the docking simulation consists of several complicated computations at the level of atoms, it requires […]

Nov, 9

### A framework for simulating and estimating the state and functional topology of complex dynamic geometric networks

We present a framework for simulating signal propagation in geometric networks (i.e. networks that can be mapped to geometric graphs in some space) and for developing algorithms that estimate (i.e. map) the state and functional topology of complex dynamic geometric net- works. Within the framework we define the key features typically present in such networks […]

Nov, 9

### HONEI: A collection of libraries for numerical computations targeting multiple processor architectures

We present HONEI, an open-source collection of libraries offering a hardware oriented approach to numerical calculations. HONEI abstracts the hardware, and applications written on top of HONEI can be executed on a wide range of computer architectures such as CPUs, GPUs and the Cell processor. We demonstrate the flexibility and performance of our approach with […]

Nov, 9

### Fast Calculation of the Lomb-Scargle Periodogram Using Graphics Processing Units

I introduce a new code for fast calculation of the Lomb-Scargle periodogram, that leverages the computing power of graphics processing units (GPUs). After establishing a background to the newly emergent field of GPU computing, I discuss the code design and narrate the key parts of the source. Benchmarking calculations indicate no significant differences in accuracy […]

Nov, 9

### The Chamomile Scheme: An Optimized Algorithm for N-body simulations on Programmable Graphics Processing Units

We present an algorithm named “Chamomile Scheme”. The scheme is fully optimized for calculating gravitational interactions on the latest programmable Graphics Processing Unit (GPU), NVIDIA GeForce8800GTX, which has (a) small but fast shared memories (16 K Bytes * 16) with no broadcasting mechanism and (b) floating point arithmetic hardware of 500 Gflop/s but only for […]

Nov, 9

### Spherical harmonic transform with GPUs

We describe an algorithm for computing an inverse spherical harmonic transform suitable for graphic processing units (GPU). We use CUDA and base our implementation on a Fortran90 routine included in a publicly available parallel package, S2HAT. We focus our attention on the two major sequential steps involved in the transforms computation, retaining the efficient parallel […]

Nov, 9

### Nodal Discontinuous Galerkin Methods on Graphics Processors

Discontinuous Galerkin (DG) methods for the numerical solution of partial differential equations have enjoyed considerable success because they are both flexible and robust: They allow arbitrary unstructured geometries and easy control of accuracy without compromising simulation stability. Lately, another property of DG has been growing in importance: The majority of a DG operator is applied […]

Nov, 9

### SIML: A Fast SIMD Algorithm for Calculating LINGO Chemical Similarities on GPUs and CPUs

LINGOs are a holographic measure of chemical similarity based on text comparison of SMILES strings. We present a new algorithm for calculating LINGO similarities amenable to parallelization on SIMD architectures (such as GPUs and vector units of modern CPUs). We show that it is nearly 3x as fast as existing algorithms on a CPU, and […]

Nov, 9

### An exploration of CUDA and CBEA for a gravitational wave source-modelling application

In this paper, we accelerate a gravitational physics numerical modelling application using hardware accelerators — Cell processor and Tesla CUDA GPU. We describe these new technologies and our approach in detail, and then present our final performance results. We obtain well over an order-of-magnitude performance gain in our application by making use of these many-core […]

Nov, 9

### Accelerating Scientific Computations with Mixed Precision Algorithms

On modern architectures, the performance of 32-bit operations is often atleast twice as fast as the performance of 64-bit operations. By using acombination of 32-bit and 64-bit floating point arithmetic, the performance ofmany dense and sparse linear algebra algorithms can be significantly enhancedwhile maintaining the 64-bit accuracy of the resulting solution. The approachpresented here can […]

Nov, 9

### Teraflop per second gravitational lensing ray-shooting using graphics processing units

Gravitational lensing calculation using a direct inverse ray-shooting approach is a computationally expensive way to determine magnification maps, caustic patterns, and light-curves (e.g. as a function of source profile and size). However, as an easily parallelisable calculation, gravitational ray-shooting can be accelerated using programmable graphics processing units (GPUs). We present our implementation of inverse ray-shooting […]