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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

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

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

Accelerated Computation of Minimum Enclosing Balls by GPU Parallelization and Distance Filtering

Linus Kallberg, Thomas Larsson

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Filtering, nVidia, nVidia Quadro K 4000 M

July 1, 2014 by hgpu

Fast Galactic Structure Finding using Graphics Processing Units

Daniel Wood

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Tags: Astrophysics, CUDA, Gravitation, KD-tree, N-body simulation, nVidia, nVidia GeForce GTX 260 Ti, nVidia GeForce GTX 460 Ti

July 1, 2014 by hgpu

The design and verification of Mumax3

Arne Vansteenkiste, Jonathan Leliaert, Mykola Dvornik, Felipe Garcia-Sanchez, Bartel Van Waeyenberge

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Source codes

Tags: Computational Physics, CUDA, Image generation, Mesoscale and Nanoscale Physics, nVidia, nVidia GeForce GTX Titan, Package, Physics

July 1, 2014 by hgpu

Modified Bloom filter for high performance hybrid NoSQL systems

A.B. Vavrenyuk, N.P. Vasilyev, V.V. Makarov, K.A. Matyukhin, M.M. Rovnyagin, A.A. Skitev

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Tags: Bloom filter, Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 260

June 28, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

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

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

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

Accelerated Computation of Minimum Enclosing Balls by GPU Parallelization and Distance Filtering

Fast Galactic Structure Finding using Graphics Processing Units

The design and verification of Mumax3

Modified Bloom filter for high performance hybrid NoSQL systems

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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