Validity of the single processor approach to achieving large scale computing capabilities
AFIPS '67 (Spring) Proceedings of the April 18-20, 1967, spring joint computer conference
Linear Feature Detection on GPUs
DICTA '10 Proceedings of the 2010 International Conference on Digital Image Computing: Techniques and Applications
Bioinformatics
GPU Acceleration of Runge-Kutta Integrators
IEEE Transactions on Parallel and Distributed Systems
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This paper presents a summary and overview of heterogeneous algorithms and applications developed by the Commonwealth Scientific and Industrial Research Organisation CSIRO for solving practical and challenging science problems such as: 1 high-content analysis of brain cell images for medical research and drug discovery; 2 genetic analysis of complex experimental designs for crop breeding; 3 solving computational fluid dynamics problems; 4 deconvolving 3D images from microscopy and medical imaging; 5 reconstructing large 3D computed tomography CT images from medical and materials science; 6 quantifying uncertainty in complex environmental models. Applications discussed utilise GPUs and multicore CPUs on a scale ranging from single desktop workstations through to large GPU clusters. Results demonstrate that both types of system can successfully accelerate a variety of practical science applications. We have seen significant gains in productivity and opportunity as a result of leveraging GPUs, tackling computational problems in which execution time was previously infeasible.