high performance computing on graphics processing units: hgpu.org

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Parallel implementation of 3D protein structure similarity searches using a GPU and the CUDA

Dariusz Mrozek, Milosz Brozek, Bozena Malysiak-Mrozek

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 560 Ti, Package, Tesla C1060

February 4, 2014 by hgpu

GPUs for real-time processing in HEP trigger systems

R. Ammendola, A. Biagioni, L. Deri, M. Fiorini, O. Frezza, G. Lamanna, F. Lo Cicero, A. Lonardo, A. Messina, M. Sozzi, F. Pantaleo, P.S. Paolucci, D. Rossetti, F. Simula, L. Tosoratto, P. Vicini

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Tags: CUDA, Data acquisition, High Energy Physics - Experiment, nVidia, nVidia GeForce GTX 680, Physics, Tesla C1060, Tesla C2050

January 14, 2014 by hgpu

Similarity Search in Metric Spaces on Parallel multi-core and multi-GPU Platforms

Ricardo Javier Barrientos Rojel

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Package, Search strategies, Tesla C1060, Tesla M2070, Thesis

December 6, 2013 by hgpu

The Use of Automated Search in Deriving Software Testing Strategies

Simon Marcus Poulding

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, Tesla C1060, Thesis

November 28, 2013 by hgpu

Autotuning of Pattern Runtimes for Accelerated Parallel Systems

Enes Bajrovic, Siegfried Benkner, Jiri Dokulil, Martin Sandrieser

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C1060, Tesla C2050

November 27, 2013 by hgpu

Multi-GPU Support on the Marrow Algorithmic Skeleton Framework

Fernando Jorge Marques Alexandre

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Tags: ATI, ATI Radeon HD 7950, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Tesla C1060, Thesis

November 20, 2013 by hgpu

Adaptive implementation selection in the SkePU skeleton programming library

Usman Dastgeer, Lu Li, Christoph Kessler

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Tags: Computer science, CUDA, Machine learning, nVidia, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

November 19, 2013 by hgpu

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Michal Januszewski, Marcin Kostur

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Tags: Code generation, Computational Physics, CUDA, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 285, OpenCL, Package, Physics, Python, Tesla C1060, Tesla C2050, Tesla K10, Tesla K20

November 12, 2013 by hgpu

Towards a Portable and Future-proof Particle-in-Cell Plasma Physics Code

R. F. Bird, S. J. Pennycook, S. A. Wright, S. A. Jarvis

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Tags: Algorithms, Computer science, nVidia, OpenCL, Particle-in-cell methods, Physics, Plasma physics, Tesla C1060, Tesla C2050, Tesla K20

November 10, 2013 by hgpu

The Plasma Simulation Code: A modern particle-in-cell code with load-balancing and GPU support

Kai Germaschewski, William Fox, Narges Ahmadi, Liang Wang, Stephen Abbott, Hartmut Ruhl, Amitava Bhattacharjee

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Tags: Computational Physics, CUDA, nVidia, Particle-in-cell methods, Physics, Plasma physics, Tesla C1060, Tesla K20

October 30, 2013 by hgpu

Online Performance Projection for Clusters with Heterogeneous GPUs

Lokendra S. Panwar, Ashwin M. Aji, Jiayuan Mengz, Pavan Balajiy, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Computer science, GPGPU-sim, GPU cluster, Heterogeneous systems, nVidia, OpenCL, Performance, Tesla C1060, Tesla C2050

October 25, 2013 by hgpu

A Framework for Management of Distributed Data Processing and Event Selection for the Icecube Neutrino Observatory

Juan Carlos Diaz Velez

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Tags: CUDA, High Energy Physics - Experiment, nVidia, Physics, Python, Tesla C1060, Tesla C2050, Tesla M2070, Thesis

October 24, 2013 by hgpu

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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high performance computing on graphics processing units: hgpu.org

Parallel implementation of 3D protein structure similarity searches using a GPU and the CUDA

GPUs for real-time processing in HEP trigger systems

Similarity Search in Metric Spaces on Parallel multi-core and multi-GPU Platforms

The Use of Automated Search in Deriving Software Testing Strategies

Autotuning of Pattern Runtimes for Accelerated Parallel Systems

Multi-GPU Support on the Marrow Algorithmic Skeleton Framework

Adaptive implementation selection in the SkePU skeleton programming library

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Towards a Portable and Future-proof Particle-in-Cell Plasma Physics Code

The Plasma Simulation Code: A modern particle-in-cell code with load-balancing and GPU support

Online Performance Projection for Clusters with Heterogeneous GPUs

A Framework for Management of Distributed Data Processing and Event Selection for the Icecube Neutrino Observatory

Recent source codes

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

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