high performance computing on graphics processing units: hgpu.org

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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

Efficient Energyminimization in Finite-Difference Micromagnetics: Speeding up Hysteresis Computations

Claas Abert, Gregor Wautischer, Florian Bruckner, Armin Satz, Dieter Suess

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Tags: Computational Physics, CUDA, Electrodynamics, Finite difference, nVidia, Package, Physics, Python

May 14, 2014 by hgpu

Finite Difference Time-Domain Modelling of Metamaterials: GPU Implementation of Cylindrical Cloak

Attique Dawood

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Tags: Algorithms, Electrodynamics, FDTD, Finite difference, Finite-difference time-domain, Materials Science, nVidia, nVidia GeForce GTX 550 Ti, Package

August 7, 2013 by hgpu

B-Calm: an Open-Source Multi-Gpu-Based 3D-FDTD with Multi-Pole Dispersion for Plasmonics

Pierre Wahl, Dany-Sebastien Ly-Gagnon, Christof Debaes, Jurgen Van Erps, Nathalie Vermeulen, David A. B. Miller, Hugo Thienpont

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Tags: Algorithms, CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, Package, Tesla C2075

April 13, 2013 by hgpu

High Performance Computing using GPGPU’s

Omar Usman Khan

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Tags: Electrodynamics, FFT, nVidia, nVidia GeForce GTX 260, OpenCL, Package, Thesis

March 29, 2013 by hgpu

Fast Multipole Methods and High Performance Computing

Cristopher Ratkevich Cecka

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Tags: CUDA, Electrodynamics, Fast multipole method, nVidia, Package, Tesla C1060, Tesla C2050, Thesis

February 26, 2012 by hgpu

Efficient GPU Implementation for Particle in Cell Algorithm

Rejith George Joseph, Girish Ravunnikutty, Sanjay Ranka, Eduardo D'Azevedo, Scott Klasky

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Tags: Algorithms, CUDA, Electrodynamics, nVidia, Package, Particle-in-cell methods, Physics, Plasma physics, Tesla T10

November 13, 2011 by hgpu

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

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

Applications

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

Efficient Energyminimization in Finite-Difference Micromagnetics: Speeding up Hysteresis Computations

Finite Difference Time-Domain Modelling of Metamaterials: GPU Implementation of Cylindrical Cloak

B-Calm: an Open-Source Multi-Gpu-Based 3D-FDTD with Multi-Pole Dispersion for Plasmonics

High Performance Computing using GPGPU’s

Fast Multipole Methods and High Performance Computing

Efficient GPU Implementation for Particle in Cell Algorithm

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

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

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