Abstract The NCBI GEO GSE3494 breast cancer dataset contains hundreds of Affymetrix HG-
U133A and HG-U133B GeneChip biopsies each with a million variables. Multiple genetic …

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 …

Genetic Programming (GP) is a computationally intensive technique which is also highly
parallel in nature. In recent years, significant performance improvements have been …

Current genomics methods are designed to handle tens to thousands of samples but will
need to scale to millions to match the pace of data and hypothesis generation in biomedical …

Recently a GPGPU application had to be redesigned to overcome performance problems. A
number of software engineering lessons were learnt from this and other projects. We …

Abstract A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel
evaluation of the whole GP population of 14 million reverse polish notation (RPN) …

Using of a cluster of Graphics Processing Unit (GPU) equipped computers, it is possible to
accelerate the evaluation of individuals in Genetic Programming. Program compilation …

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 …

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 …

The emergence of GPU-CPU heterogeneous architectures has led to a fundamental
paradigm shift in parallel programming. Accelerating Genetic Algorithms (GAs) on these …