Posts
Jan, 21
Evolving a CUDA kernel from an nVidia template
Rather than attempting to evolve a complete program from scratch we demonstrate genetic interface programming (GIP) by automatically generating a parallel CUDA kernel with identical functionality to existing highly optimised ancient sequential C code (gzip). Generic GPGPU nVidia kernel C++ code is converted into a BNF grammar. Strongly typed genetic programming uses the BNF to […]
Jan, 21
Genetic Programming An Introductory Tutorial and a Survey of Techniques and Applications
This paper introduces genetic programming (GP) – a set of evolutionary computation techniques for getting computers to automatically solve problems without having to tell them explicitly how to do it. Since its inception, GP has been used to solve many practical problems, producing a number of human competitive results and even patentable new inventions. We […]
Jan, 21
A Field Guide to Genetic Programming
Genetic programming (GP) is a collection of evolutionary computation techniques that allow computers to solve problems automatically. Since its inception twenty years ago, GP has been used to solve a wide range of practical problems, producing a number of human-competitive results and even patentable new inventions. Like many other areas of computer science, GP is […]
Jan, 21
A CUDA SIMT interpreter for genetic programming. Revised
A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel evaluation of the whole GP population of quarter of a 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 […]
Jan, 21
Accelerating Genetic Programming through Graphics Processing Units
Graphics Processing Units (GPUs) are in the process of becoming a major source of computational power for numerical applications. Originally designed for application of time-consuming graphics operations, GPUs are stream processors that implement the SIMD paradigm. The true degree of parallelism of GPUs is often hidden from the user, making programming even more flexible and […]
Jan, 21
A Many Threaded CUDA 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 reverse polish notation (RPN) expressions on graphics cards and nVidia Tesla. Using sub-machine code tree GP a sustain peak performance of 665 billion GP operations per second (10,000 speed up) and an average of 22 […]
Jan, 21
Large Scale Bioinformatics Data Mining with Parallel Genetic Programming on Graphics Processing Units
A suitable single instruction multiple data GP interpreter can achieve high (Giga GPop/second) performance on a SIMD GPU graphics card by simultaneously running multiple diverse members of the genetic programming population. SPMD dataflow parallelisation is achieved because the single interpreter treats the different GP programs as data. On a single 128 node parallel nVidia GeForce […]
Jan, 20
Gaussian split Ewald: A fast Ewald mesh method for molecular simulation
Gaussian split Ewald (GSE) is a versatile Ewald mesh method that is fast and accurate when used with both real-space and k-space Poisson solvers. While real-space methods are known to be asymptotically superior to k-space methods in terms of both computational cost and parallelization efficiency, k-space methods such as smooth particle-mesh Ewald (SPME) have thus […]
Jan, 20
Radiometric Compensation through Inverse Light Transport
Radiometric compensation techniques allow seamless projections onto complex everyday surfaces. Implemented with projector-camera systems they support the presentation of visual content in situations where projection-optimized screens are not available or not desired – as in museums, historic sites, air-plane cabins, or stage performances. We propose a novel approach that employs the full light transport between […]
Jan, 20
Simultaneous and fast 3D tracking of multiple faces in video by GPU-based stream processing
In this work, we implement a real-time visual tracker that targets the position and 3D pose of objects in video sequences, specifically faces. Using stream processors for performing the computations as well as efficient sparse-template-based particle filtering allows us to achieve real-time processing even when tracking multiple objects simultaneously in high- resolution video frames. Stream […]
Jan, 20
Contouring for Power Systems Using Graphical Processing Units
To improve situational awareness in power systems, one useful tool used in control centers is bus (or substation) data contouring. Traditionally, the methods developed have used CPU processing, leading to long contour rendering times that reduce interactivity with the visualization. To improve interactivity and increase the data rate which can be handled, contouring methods utilizing […]
Jan, 20
SPRAT: Runtime processor selection for energy-aware computing
A commodity personal computer (PC) can be seen as a hybrid computing system equipped with two different kinds of processors, i.e. CPU and a graphics processing unit (GPU). Since the superiorities of GPUs in the performance and the power efficiency strongly depend on the system configuration and the data size determined at the runtime, a […]