Posts
Feb, 15
Generation of Kernels for Calculating Electron Repulsion Integrals of High Angular Momentum Functions on GPUs – Preliminary Results
Evaluation of electron repulsion integrals (ERIs) takes considerable time in modern quantum chemistry applications and also presents a certain difficulty to be efficiently computed on GPUs. Here, we describe a novel methodology for generating high-arithmetic-density kernels for ERI evaluation of d and higher angular momentum functions, as well as highlight challenges associated with the efficient […]
Feb, 15
Accelerating Quantum Chromodynamics Calculations with GPUs
We present a CUDA C implementation of the Conjugate Gradient (CG) and multi-mass CG solver from the MILC quantum chromodynamics package to speedup improved staggered quarks computations on NVIDIA GPUs. The implementation is built on the QUDA package from Boston University.
Feb, 15
PRNG Random Numbers on GPU
Limited numerical precision of nVidia GeForce 8800 GTX and other GPUs requires careful implementation of PRNGs. The Park-Miller PRNG is programmed using G80’s native Value4f floating point in RapidMind C++. Speed up is more than 40. Code is available via ftp ftp://cs.ucl.ac.uk/genetic/gp-code/random-numbers/gpu park-miller.tar.gz
Feb, 15
A Fast High Quality Pseudo Random Number Generator for Graphics Processing Units
Limited numerical precision of nVidia GeForce 8800 GTX and other GPUs requires careful implementation of PRNGs. The Park-Miller PRNG is programmed using G80’s native Value4f floating point in RapidMind C++. Speed up is more than 40. Code is available via ftp cs.ucl.ac.uk genetic/gp-code/random-numbers/gpu_park-miller.tar.gz.
Feb, 15
A CUDA SIMT Interpreter for Genetic Programming
A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel evaluation of the whole GP population of 1/4 million RPN expressions on graphics cards and nVidia Tesla T10P. Using sub-machine code GP a sustain peak performance of 212 billion GP operations per second (3300 speed up) and an average of 4.5 peta GP ops […]
Feb, 15
Evolving gzip matches Kernel from an nVidia CUDA Template
Rather than attempting to evolve a complete program from scratch we demonstrate genetic interface programming by automatically generating a parallel CUDA kernel with identical functionality to existing highly optimised ancient sequential C code. Generic GPGPU nVidia kernel C++ code is converted into a BNF grammar. Strongly typed genetic programming uses the BNF to generate compilable […]
Feb, 15
Graphics Processing Units and Genetic Programming: An overview
A top end graphics card (GPU) plus a suitable SIMD interpreter, can deliver a several hundred fold speed up, yet cost less than the computer holding it. We give highlights of AI and computational intelligence applications in the new field of general purpose computing on graphics hardware (GPGPU). In particular we survey genetic programming (GP) […]
Feb, 14
Simulation Modelling and Visualisation: Toolkits for Building Artificial Worlds
Simulations users at all levels make heavy use of compute resources to drive computational simulations for greatly varying applications areas of research using different simulation paradigms. Simulations are implemented in many software forms, ranging from highly standardised and general models that run in proprietary software packages to ad hoc hand-crafted simulations codes for very specific […]
Feb, 14
Numerical Simulation of the Complex Ginzburg-Landau Equation on GPUs with CUDA
The Time Dependent Ginzburg Landau(TDGL) equation models a complex scalar field and is used to study a variety of different physical systems and exhibits phase transitional behaviours that necessitate study using numerical simulation methods. We employ fast data-parallel simulation algorithms on Graphical Processing Units (GPUs) and report on performance data and stability tradeoffs from using […]
Feb, 14
Data Parallel Three-Dimensional Cahn-Hilliard Field Equation Simulation on GPUs with CUDA
Computational scientific simulations have long used parallel computers to increase their performance. Recently graphics cards have been utilised to provide this functionality. GPGPU APIs such as NVidia’s CUDA can be used to harness the power of GPUs for purposes other than computer graphics. GPUs are designed for processing twodimensional data. In previous work we have […]
Feb, 14
Visualising Interfaces in Scalar and Vector Field-Model Simulations
Many scientific simulations and models are based upon one or more coupled field equations. Fields are often modelled as a regular mesh or grid of individual field variables where each degrees of freedom or site variable is a scalar or vector quantity. Visualising such quantities interactively can be a great aid to debugging as well […]
Feb, 14
Modelling, simulating and visualising the Cahn-Hilliard-Cook field equation
The Cahn-Hilliard-Cook equation continues to be a useful model describing binary phase separation in systems such as alloys and other physical and chemical applications. We describe our investigation of this field equation and report on the various discretisation schemes we used to integrate the system in one-, two- and three-dimensions. We also discuss how the […]