high performance computing on graphics processing units: hgpu.org

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Parallel GPU Processing for Fast Radio Signal Propagation Computation in GRASS-RaPlaT

Igor Ozimek, Andrej Hrovat, Andrej Vilhar, Tomaz Javornik

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Tags: nVidia, nVidia GeForce GTX 580, OpenCL, Physics, Signal processing

December 7, 2014 by hgpu

Coulomb and Landau Gauge Fixing in GPUs using CUDA and MILC

Nuno Cardoso

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Tags: Computational Physics, High Energy Physics - Lattice, Physics

December 5, 2014 by hgpu

Software Polarization Spectrometer "PolariS"

Izumi Mizuno, Seiji Kameno, Amane Kano, Makoto Kuroo, Fumitaka Nakamura, Noriyuki Kawaguchi, Katsunori M. Shibata, Seisuke Kuji, Nario Kuno

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Tags: Astrophysics, CUDA, FFT, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GT 640, Package

December 5, 2014 by hgpu

Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

David Abdurachmanov, Brian Bockelman, Peter Elmer, Giulio Eulisse, Robert Knight, Shahzad Muzaffar

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Tags: ARM, Computational Physics, Computer science, Distributed computing, Heterogeneous systems, High Energy Physics - Experiment, Intel Xeon Phi, Physics

December 5, 2014 by hgpu

Numerical cosmology on the GPU with Enzo and Ramses

Claudio Gheller, Peng Wang, Franco Vazza, Romain Teyssier

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Tags: Astrophysics, Cosmology, CUDA, Instrumentation and Methods for Astrophysics, nVidia, OpenACC, Tesla K20

December 3, 2014 by hgpu

24.77 Pflops on a Gravitational Tree-Code to Simulate the Milky Way Galaxy with 18600 GPUs

Jeroen Bedorf, Evghenii Gaburov, Michiko S. Fujii, Keigo Nitadori, Tomoaki Ishiyama, Simon Portegies Zwart

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Tags: Algorithms, Astrophysics, CUDA, GPU cluster, Gravitation, Instrumentation and Methods for Astrophysics, nVidia, Tesla K20

December 3, 2014 by hgpu

Anisotropic interfacial tension, contact angles, and line tensions: A graphics-processing-unit-based Monte Carlo study of the Ising model

Benjamin J. Block, Suam Kim, Peter Virnau, Kurt Binder

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Tags: Computational Physics, CUDA, Ising model, nVidia, OpenCL, Physics

November 25, 2014 by hgpu

Ageing at the Spin-Glass/Ferromagnet Transition: Monte Carlo Simulation using GPUs

Markus Manssen, Alexander K. Hartmann

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Tags: Condensed matter, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 570, Physics, Statistical Mechanics

November 25, 2014 by hgpu

CL2QCD – Lattice QCD based on OpenCL

Owe Philipsen, Christopher Pinke, Alessandro Sciarra, Matthias Bach

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Tags: AMD FirePro S10000, ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, High Energy Physics - Lattice, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Physics, QCD, Tesla K40

November 20, 2014 by hgpu

Using Graphics Processing Units to solve the classical N-body problem in physics and astrophysics

Mario Spera

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Tags: Astrophysics, CUDA, Electrodynamics, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, QCD

November 20, 2014 by hgpu

Conjugate gradient solvers on Intel Xeon Phi and NVIDIA GPUs

O. Kaczmarek, C. Schmidt, P. Steinbrecher, M. Wagner

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Tags: Computational Physics, Conjugate gradient solver, CUDA, High Energy Physics - Lattice, Intel Xeon Phi, Mathematical Software, nVidia, Physics, Tesla K20, Tesla K40

November 18, 2014 by hgpu

Parallel Neutrino Triggers using GPUs for an underwater telescope

Bachir Bouhadef, Mauro Morganti, Giuseppe Terreni

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Tags: CUDA, High Energy Physics - Experiment, Instrumentation and Detectors, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX Titan, Physics, Tesla C2050

November 18, 2014 by hgpu

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

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

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

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high performance computing on graphics processing units: hgpu.org

Applications

Parallel GPU Processing for Fast Radio Signal Propagation Computation in GRASS-RaPlaT

Coulomb and Landau Gauge Fixing in GPUs using CUDA and MILC

Software Polarization Spectrometer "PolariS"

Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

Numerical cosmology on the GPU with Enzo and Ramses

24.77 Pflops on a Gravitational Tree-Code to Simulate the Milky Way Galaxy with 18600 GPUs

Anisotropic interfacial tension, contact angles, and line tensions: A graphics-processing-unit-based Monte Carlo study of the Ising model

Ageing at the Spin-Glass/Ferromagnet Transition: Monte Carlo Simulation using GPUs

CL2QCD – Lattice QCD based on OpenCL

Using Graphics Processing Units to solve the classical N-body problem in physics and astrophysics

Conjugate gradient solvers on Intel Xeon Phi and NVIDIA GPUs

Parallel Neutrino Triggers using GPUs for an underwater telescope

Recent source codes

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

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

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

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