high performance computing on graphics processing units: hgpu.org

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Massively parallelized replica-exchange simulations of polymers on GPUs

Jonathan Gross, Wolfhard Janke, Michael Bachmann

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Tags: Biomolecules, Computational Physics, Condensed matter, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Physics, Polymer Systems, Tesla C1060

July 19, 2011 by hgpu

EQUIPE: Parallel equivalence checking with GP-GPUs

Debapriya Chatterjee, Valeria Bertacco

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Tags: Computer science, CUDA, Electronic design automation, nVidia, nVidia GeForce 8800 GT, SAT

July 19, 2011 by hgpu

System integration of FastSPECT III, a dedicated SPECT rodent-brain imager based on BazookaSPECT detector technology

Brian W. Miller, Lars R. Furenlid, Stephen K. Moore, H. Bradford Barber, Vivek V. Nagarkar, Harrison H. Barrett

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Tags: Computed tomography, CT, CUDA, GPU cluster, Image reconstruction, Medicine, nVidia, nVidia GeForce GTX 295, OpenMP, Tomography

July 19, 2011 by hgpu

Discrete fourier transform on multicore

Franz Franchetti, Markus Puschel, Yevgen Voronenko, Srinivas Chellappa, Jose M. F. Moura

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Tags: Cell processor, CUDA, FFT, nVidia, nVidia GeForce GTX 280, Signal processing

July 19, 2011 by hgpu

Towards fully user transparent task and data parallel image processing

Jan Lemeire, Yan Zhao, Peter Schelkens, Steve De Backer, Frans Cornelissen, Bert Torfs

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Tags: Algorithms, CUDA, Image processing, nVidia

July 19, 2011 by hgpu

Tracking humans interacting with the environment using efficient hierarchical sampling and layered observation models

Jan Bandouch, Michael Beetz

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Tags: Computer science, Computer vision, CUDA, nVidia, Video tracking

July 19, 2011 by hgpu

An auto-tuning framework for parallel multicore stencil computations

Shoaib Kamil, Cy Chan, Leonid Oliker, John Shalf, Samuel Williams

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Tags: Code generation, Computer science, CUDA, Fortran, nVidia, nVidia GeForce GTX 280

July 18, 2011 by hgpu

Accelerating Partitional Algorithms for Flow Cytometry on GPUs

Jeremy Espenshade, Andrew Pangborn, Gregor von Laszewski, Douglas Roberts, James S. Cavenaugh

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Tags: Algorithms, Biology, Clustering, CUDA, nVidia, Tesla C870

July 18, 2011 by hgpu

Implementing LNS using filtering units of GPUs

Mark Arnold, Sylvain Collange, David Defour

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Tags: CUDA, Filtering, nVidia, nVidia GeForce GTX 280, Signal processing

July 17, 2011 by hgpu

Dynamic scheduling Monte-Carlo framework for multi-accelerator heterogeneous clusters

Anson H.T. Tse, David B. Thomas, K.H. Tsoi, Wayne Luk

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, Monte Carlo simulation, nVidia, Tesla C1060

July 17, 2011 by hgpu

Improving the Performance of the Sparse Matrix Vector Product with GPUs

F. Vazquez, G. Ortega, J.J. Fernandez, E.M. Garzon

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Partial differential equations, PDEs, Sparse matrix

July 17, 2011 by hgpu

Boosting sphere decoding speed through Graphic Processing Units

Muhammad S. Khairy, Christian Mehlfuhrer, Markus Rupp

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Source codes

Tags: Computer science, CUDA, MIMO, Network communications, nVidia, nVidia GeForce 8400 GS, nVidia GeForce GTX 285, Package

July 17, 2011 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Massively parallelized replica-exchange simulations of polymers on GPUs

EQUIPE: Parallel equivalence checking with GP-GPUs

System integration of FastSPECT III, a dedicated SPECT rodent-brain imager based on BazookaSPECT detector technology

Discrete fourier transform on multicore

Towards fully user transparent task and data parallel image processing

Tracking humans interacting with the environment using efficient hierarchical sampling and layered observation models

An auto-tuning framework for parallel multicore stencil computations

Accelerating Partitional Algorithms for Flow Cytometry on GPUs

Implementing LNS using filtering units of GPUs

Dynamic scheduling Monte-Carlo framework for multi-accelerator heterogeneous clusters

Improving the Performance of the Sparse Matrix Vector Product with GPUs

Boosting sphere decoding speed through Graphic Processing Units

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Tutoring LLM into a Better CUDA Optimizer

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