2714

Posts

Jan, 21

Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling

This paper shows that it is possible to use General Purpose Graphic Processing Unit cards for a fast evaluation of different Genetic Programming trees on as few as 32 fitness cases by using the hardware scheduling of NVIDIA cards. Depending on the function set, observed speedup ranges between x50 and x250 on one half of […]
Jan, 21

GP on SPMD parallel graphics hardware for mega Bioinformatics data mining

We demonstrate a SIMD C++ genetic programming system on a single 128 node parallel nVidia GeForce 8800 GTX GPU under RapidMind’s GPGPU Linux software by predicting ten year+ outcome of breast cancer from a dataset containing a million inputs. NCBI GEO GSE3494 contains hundreds of Affymetrix HG-U133A and HG-U133B GeneChip biopsies. Multiple GP runs each […]
Jan, 21

Evolving GeneChip correlation predictors on parallel graphics hardware

A GPU is used to datamine five million correlations between probes within Affymetrix HG-U133A probesets across 6685 human tissue samples from NCBIpsilas GEO database. These concordances are used as machine learning training data for genetic programming running on a Linux PC with a RapidMind OpenGL GLSL backend. GPGPU is used to identify technological factors influencing […]
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 […]

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