high performance computing on graphics processing units: hgpu.org

James Bergstra, Olivier Breuleux, Frederic Bastien, Pascal Lamblin, Razvan Pascanu, Guillaume Desjardins, Joseph Turian, David Warde-Farley, Yoshua Bengio

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Tags: Algorithms, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 285, Package, Python

December 12, 2011 by hgpu

A Common GPU n-Dimensional Array for Python and C

Frederic Bastien, Arnaud Bergeron, Pascal Vincent, Yoshua Bengio

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Python

December 12, 2011 by hgpu

Bringing Parallel Performance to Python with Domain-Specific Selective Embedded Just-in-Time Specialization

Shoaib Kamil, Derrick Coetzee, Armando Fox

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, Python

December 12, 2011 by hgpu

Self-Supervised Clustering for Codebook Construction: An Application to Object Localization

Arturo Ribes, Senshan Ji, Arnau Ramisa, Ramon Lopez De Mantaras

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Tags: Clustering, Computer science, Computer vision, CUDA, nVidia, SIFT

December 11, 2011 by hgpu

Aquila: An Open-Source GPU-Accelerated Toolkit for Cognitive Robotics Research

Martin Peniak, Anthony Morse, Christopher Larcombe, Salomon Ramirez-Contla, Angelo Cangelosi

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 470, Package, Tesla C1060

December 11, 2011 by hgpu

Gyrokinetic Toroidal Simulations on Leading Multi-and Manycore HPC Systems

Kamesh Madduri, Khaled Z. Ibrahim, Samuel Williams, Eun-Jin Im, Stephane Ethier, John Shalf, Leonid Oliker

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Tags: CUDA, Fortran, Hybrid computing, MPI, nVidia, OpenMP, Optimization, Particle-in-cell methods, Physics, Plasma physics, Tesla C2050

December 11, 2011 by hgpu

Accelerating Swarm Intelligence Algorithms with GPU-Computing

Robin M. Weiss

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Tags: Algorithms, Cluster analysis, Clustering, Computer science, CUDA, Data mining, nVidia, Tesla C1060

December 11, 2011 by hgpu

Allo: Accelerator Design Language

Dato: A Task-Based Programming Model for Dataflow Accelerators

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

A Rigid Body Physics Engine for Interactive Applications

Parallel Evaluation of a Spatial Traversability Cost Function on GPU for Efficient Path Planning

Accelerating non-linear image registration with GPUs

GPU Programming in a High Level Language: Compiling X10 to CUDA

A fast and intuitive visual programming language (VPL) for constructing Computer Vision and Image processing systems on GPUs

Theano: A CPU and GPU Math Compiler in Python

A Common GPU n-Dimensional Array for Python and C

Bringing Parallel Performance to Python with Domain-Specific Selective Embedded Just-in-Time Specialization

Self-Supervised Clustering for Codebook Construction: An Application to Object Localization

Aquila: An Open-Source GPU-Accelerated Toolkit for Cognitive Robotics Research

Gyrokinetic Toroidal Simulations on Leading Multi-and Manycore HPC Systems

Accelerating Swarm Intelligence Algorithms with GPU-Computing

Recent source codes

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

HPC Benchmark Survey

HDM: Home made Diffusion Models

General Matrix Multiplication (GEMM)

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

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