high performance computing on graphics processing units: hgpu.org

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Design and Performance of the OP2 Library for Unstructured Mesh Applications

Carlo Bertolli, Adam Betts, Gihan Mudalige, Mike Giles, Paul Kelly

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, OpenCL, OpenMP, Package, Tesla C2050

October 18, 2011 by hgpu

Odeint – Solving ordinary differential equations in C++

Karsten Ahnert, Mario Mulansky

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Tags: Chaotic Dynamics, Computational Physics, Computer science, CUDA, Differential equations, Mathematical Software, nVidia, ODEs, Ordinary differential equations, Package

October 18, 2011 by hgpu

The Anatomy of High-Performance 2D Similarity Calculations

Imran S. Haque, Vijay S. Pande, W. Patrick Walters

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Tags: Algorithms, Biochemistry, Chemistry, Clustering, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Package

October 16, 2011 by hgpu

Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers

Naoya Maruyama, Tatsuo Nomura, Kento Sato, Satoshi Matsuoka

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Tags: Computer science, CUDA, MPI, nVidia, Optimization, Package, Performance, Programming Languages, Programming techniques, Tesla M2050

October 15, 2011 by hgpu

Accelerating code on multi-cores with FastFlow

Marco Aldinucci, Marco Danelutto, Peter Kilpatrick, Massimiliano Meneghin, Massimo Torquati

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Tags: Computer science, Memory, Package, Performance, Programming techniques

October 15, 2011 by hgpu

Efficient Mapping of Streaming Applications for Image Processing on Graphics Cards

Richard Membarth, Hritam Dutta, Frank Hannig, Jurgen Teich

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Tags: Algorithms, CUDA, Image processing, nVidia, Package, Tesla C1060

October 15, 2011 by hgpu

CudaDMA: Optimizing GPU Memory Bandwidth via Warp Specialization

Michael Bauer, Henry Cook, Brucek Khailany

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Tags: Benchmarking, Computer science, CUDA, Memory model, nVidia, Optimization, Package, Performance, Tesla C2050

October 14, 2011 by hgpu

Liszt: A Domain Specific Language for Building Portable Mesh-based PDE Solvers

Zachary DeVito, Niels Joubert, Francisco Palacios, Stephen Oakley, Montserrat Medina, Mike Barrientos, Erich Elsen, Frank Ham, Alex Aiken, Karthik Duraisamy, Eric Darve, Juan Alonso, Pat Hanrahan

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Package, Partial differential equations, PDEs, Performance, Programming Languages, Tesla C2050

October 14, 2011 by hgpu

Firepile: Run-time Compilation for GPUs in Scala

Nathaniel Nystrom, Derek White, Kishen Das

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Tags: Code generation, Compilers, Computer science, nVidia, nVidia GeForce 9800 GT, OpenCL, Package, Performance

October 13, 2011 by hgpu

Introduction to GPU Radix Sort

Takahiro Harada, Lee Howes

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Tags: Algorithms, ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, Computer science, OpenCL, Package, Sorting

October 13, 2011 by hgpu

gpustats: GPU Library for Statistical Computing in Python

Andrew Cron, Wes McKinney

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Tags: Algorithms, Bayesian, Code generation, CUDA, Mathematics, nVidia, nVidia GeForce GTS 250, OpenCL, Package, Probability, Python, Statistics

October 13, 2011 by hgpu

Cinematic Particle Systems with OpenCL

Tim Horton

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Tags: ATI, ATI Radeon HD 4890, Computer science, OpenCL, Package, Rendering, Visualization

October 12, 2011 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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

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high performance computing on graphics processing units: hgpu.org

Packages

Design and Performance of the OP2 Library for Unstructured Mesh Applications

Odeint – Solving ordinary differential equations in C++

The Anatomy of High-Performance 2D Similarity Calculations

Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers

Accelerating code on multi-cores with FastFlow

Efficient Mapping of Streaming Applications for Image Processing on Graphics Cards

CudaDMA: Optimizing GPU Memory Bandwidth via Warp Specialization

Liszt: A Domain Specific Language for Building Portable Mesh-based PDE Solvers

Firepile: Run-time Compilation for GPUs in Scala

Introduction to GPU Radix Sort

gpustats: GPU Library for Statistical Computing in Python

Cinematic Particle Systems with OpenCL

Recent source codes

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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

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