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Molecular dynamics simulations through GPU video games technologies

Styliani Loukatou, Louis Papageorgiou, Paraskevas Fakourelis, Arianna Filntisi, Eleftheria Polychronidou, Ioannis Bassis, Vasileios Megalooikonomou, Wojciech Makalowski, Dimitrios Vlachakis, Sophia Kossida

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Tags: Bioinformatics, Biology, Chemistry, CUDA, Medicine, Molecular dynamics, nVidia, OpenCL, Physics

July 4, 2014 by hgpu

A second generation of DEFG: Declarative Framework for GPUs

Robert Senser, Tom Altman

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Tags: Computer science, High-level Languages, nVidia, OpenCL, Tesla T20

July 4, 2014 by hgpu

The Design and Implementation of a GPU-enabled Multi-objective Tabu-search Intended for Real World and High-dimensional Applications

Christos Tsotskas, Timoleon Kipouros, Anthony Mark Savill

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Tags: Computer science, CUDA, Heterogeneous systems, Metaheuristics, nVidia, nVidia Quadro 1000 M

July 4, 2014 by hgpu

GPUvm: Why Not Virtualizing GPUs at the Hypervisor?

Yusuke Suzuki, Shinpei Kato, Hiroshi Yamada, Kenji Kono

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Tags: Cloud, Computer science, CUDA, nVidia, nVidia Quadro 6000, Operating systems, Virtualization

July 4, 2014 by hgpu

A Road Marking Extraction Method Using GPGPU

Dajun Ding, Jongsu Yoo, Jekyo Jung, Kwon Soon

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce GTX 760, OpenCL, Vehicular traffic

July 4, 2014 by hgpu

Exploiting parallel features of modern computer architectures in bioinformatics: applications to genetics, structure comparison and large graph analysis

Guillaume Chapuis

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Genetics, Graph theory, nVidia, Path problems, Tesla C2050, Thesis

July 3, 2014 by hgpu

The Framework and Compilation Techniques for Directive-based GPU Cluster Programming

Pisit Makpaisit, Putchong Uthayopas

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Tags: Compilers, Computer science, CUDA, GPU cluster, nVidia, OpenACC, Tesla M2050

July 3, 2014 by hgpu

Historic Learning Approach for Auto-tuning OpenACC Accelerated Scientific Applications

Shahzeb Siddiqui, Saber Feki

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Tags: Computer science, CUDA, nVidia, OpenACC, Performance, Tesla K20

July 3, 2014 by hgpu

Reducing the Code Degree Of Parallelism to Increase GPUs Reliability

P. Rech, L. Carro

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Tags: Computer science, CUDA, Fault simulation, nVidia, nVidia GeForce GTX 480, Tesla C2050

July 3, 2014 by hgpu

Toward Auto-tuned Krylov Basis Computations with minimized Communication on Clusters of Accelerators

Langshi Chen, Serge Petiton, Leroy Drummond, Maxime Hugues

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Tesla K20

July 3, 2014 by hgpu

Mixed-precision Orthogonalization Scheme and Adaptive Step Size for CA-GMRES on GPUs

Ichitaro Yamazaki, Stanimire Tomov, Tingxing Dong, Jack Dongarra

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Tags: Computer science, Linear Algebra, nVidia, Performance, Tesla K20, Tesla K40, Tesla M2090

July 1, 2014 by hgpu

Energy Efficiency Benefits of Reducing the Voltage Guardband on the Kepler GPU Architecture

Jingwen Leng, Yazhou Zu, Vijay Janapa Reddi

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 680

July 1, 2014 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

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

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

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

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high performance computing on graphics processing units: hgpu.org

Molecular dynamics simulations through GPU video games technologies

A second generation of DEFG: Declarative Framework for GPUs

The Design and Implementation of a GPU-enabled Multi-objective Tabu-search Intended for Real World and High-dimensional Applications

A Road Marking Extraction Method Using GPGPU

Exploiting parallel features of modern computer architectures in bioinformatics: applications to genetics, structure comparison and large graph analysis

The Framework and Compilation Techniques for Directive-based GPU Cluster Programming

Historic Learning Approach for Auto-tuning OpenACC Accelerated Scientific Applications

Reducing the Code Degree Of Parallelism to Increase GPUs Reliability

Toward Auto-tuned Krylov Basis Computations with minimized Communication on Clusters of Accelerators

Mixed-precision Orthogonalization Scheme and Adaptive Step Size for CA-GMRES on GPUs

Energy Efficiency Benefits of Reducing the Voltage Guardband on the Kepler GPU Architecture

Recent source codes

Kernel Library for LLM Serving

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

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

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

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