high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

CUDA Based Fast Implementation of Very Large Matrix Computation

Yinghong Sun, Yuanman Tong

Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia

June 10, 2011 by hgpu

Single molecule detection of tuberculosis nucleic acid using dark field Tethered Particle Motion

Sanneke Brinkers, Heidelinde R.C. Dietrich, Sjoerd Stallinga, Jurriaan J. Mes, Ian T. Young, Bernd Rieger

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Tags: Algorithms, Biology, Biophysics, RNA

June 9, 2011 by hgpu

cuGWAM: Genome-wide association multifactor dimensionality reduction using CUDA-enabled high-performance graphics processing unit

Min-Seok Kwon, Kyunga Kim, Sungyoung Lee, Taesung Park

Source codes

Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, Package

June 9, 2011 by hgpu

Low-Frequency MLFMA on Graphics Processors

M. Cwikla, J. Aronsson, V. Okhmatovski

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Tags: CUDA, Electrodynamics, Fast multipole method, nVidia, nVidia Quadro FX 5800

June 9, 2011 by hgpu

Adaptive Optimization for Petascale Heterogeneous CPU/GPU Computing

Canqun Yang, Feng Wang, Yunfei Du, Juan Chen, Jie Liu, Huizhan Yi, Kai Lu

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Tags: ATI, ATI Radeon HD 4870, ATI Stream, Computer science, Heterogeneous systems, Linear Algebra, Optimization, Presentation

June 9, 2011 by hgpu

SAR focusing of P-band ice sounding data using back-projection

Anders Kusk, Jorgen Dall

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Tags: CUDA, Earth and Space Sciences, nVidia, nVidia GeForce GTX 260

June 9, 2011 by hgpu

Parallelism of Clonal Selection for PSP on CUDA

Hongbing Zhu, Heng Xiao, JinGuang Gu

Tags: Biology, CUDA, Macromolecule, nVidia

June 9, 2011 by hgpu

Parallel multi-level analytical global placement on graphics processing units

Jason Cong, Yi Zou

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Tags: Algorithms, CAD, Computer science, CUDA, nVidia, Performance, Tesla C1060

June 9, 2011 by hgpu

Parallelization of tau-leap coarse-grained Monte Carlo simulations on GPUs

Lifan Xu, Michela Taufer, Stuart Collins, Dionisios G. Vlachos

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Tags: Chemistry, CUDA, Data parallelism, GPU cluster, Monte Carlo simulation, nVidia, Physics, Tesla S1070

June 9, 2011 by hgpu

Compensating Indirect Scattering for Immersive and Semi-Immersive Projection Displays

Oliver Bimber, Anselm Grundhofer, Thomas Zeidler, Daniel Danch, Pedro Kapakos

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Tags: Algorithms, Computer science, Presentation, Rendering, Sparse matrix, Virtual reality

June 8, 2011 by hgpu

Realtime Ray Tracing on a Hibrid Parallel Architecture

Xin Yang, Duan-qing Xu, Wen-zhi Chen

Tags: Algorithms, Computer science, Rendering

June 8, 2011 by hgpu

Parallel accelerators for GlimmerHMM bioinformatics algorithm

Nafsika Chrysanthou, Grigorios Chrysos, Euripides Sotiriades, Ioannis Papaefstathiou

Tags: Algorithms, Bioinformatics, Biology, FPGA, Genetics

June 8, 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

Programming

CUDA Based Fast Implementation of Very Large Matrix Computation

Single molecule detection of tuberculosis nucleic acid using dark field Tethered Particle Motion

cuGWAM: Genome-wide association multifactor dimensionality reduction using CUDA-enabled high-performance graphics processing unit

Low-Frequency MLFMA on Graphics Processors

Adaptive Optimization for Petascale Heterogeneous CPU/GPU Computing

SAR focusing of P-band ice sounding data using back-projection

Parallelism of Clonal Selection for PSP on CUDA

Parallel multi-level analytical global placement on graphics processing units

Parallelization of tau-leap coarse-grained Monte Carlo simulations on GPUs

Compensating Indirect Scattering for Immersive and Semi-Immersive Projection Displays

Realtime Ray Tracing on a Hibrid Parallel Architecture

Parallel accelerators for GlimmerHMM bioinformatics algorithm

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Tutoring LLM into a Better CUDA Optimizer

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

Kernel Library for LLM Serving

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