high performance computing on graphics processing units: hgpu.org

Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Caglar Gulcehre, Vincent Michalski, Kishore Konda, Sebastien Jean, Pierre Froumenty, Aaron Courville, Pascal Vincent, Roland Memisevic, Christopher Pal, Yoshua Bengio

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Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia

March 14, 2015 by hgpu

Parallel Statistical Multi-resolution Estimation

Jan Lebert, Lutz Kunneke, Johannes Hagemann, Stephan C. Kramer

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Tags: Computational Physics, Computer vision, CUDA, nVidia, Physics, Tesla K20

March 14, 2015 by hgpu

HELIOS-K: An Ultrafast, Open-source Opacity Calculator for Radiative Transfer

Simon L. Grimm, Kevin Heng

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Tags: Astrophysics, CUDA, Earth and Planetary Astrophysics, nVidia, Package, Tesla K20

March 14, 2015 by hgpu

Accelerating DEM simulations on GPUs by reducing the impact of warp divergences

Yasuhiro Nakahara, Teruyoshi Washizawa

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Tags: Computer science, nVidia, OpenCL, Particle simulation, Tesla M2050

March 14, 2015 by hgpu

GPGPU Performance and Power Estimation Using Machine Learning

Gene Wu, Joseph L. Greathouse, Alexander Lyashevsky, Nuwan Jayasena, Derek Chiou

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Tags: ATI, ATI Radeon HD 7970, Computer science, Energy-efficient computing, Machine learning, Neural networks, OpenCL

March 12, 2015 by hgpu

Implementing Machine Learning Algorithms on GPUs for Real-Time Traffic Sign Classification

Dashiell Bodington, Eric Greenstein, Matthew Hu

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 780

March 12, 2015 by hgpu

CUDA accelerated large scale vehicular area network simulator

Chok Meng Yip

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Tags: Computer science, CUDA, nVidia, Tesla C2075, Tesla K20, Thesis, Vehicular traffic

March 12, 2015 by hgpu

RadixBoost: A Hardware Acceleration Structure for Scalable Radix Sort on Graphic Processors

Xingyu Liu, Shikai Li, Kuan Fang, Yufei Ni, Zonghui Li, Yangdong Deng

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Tags: Algorithms, ASIC, Computer science, FPGA, nVidia, nVidia GeForce GTX 580, Sorting

March 12, 2015 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

Accelerating Direction-Optimized Breadth First Search on Hybrid Architectures

A Switched Dynamical System Framework for Analysis of Massively Parallel Asynchronous Numerical Algorithms

Fast Radix Sort for Sparse Linear Algebra on GPU

Heterogeneous Acceleration of Volumetric JPEG 2000

EmoNets: Multimodal deep learning approaches for emotion recognition in video

Parallel Statistical Multi-resolution Estimation

HELIOS-K: An Ultrafast, Open-source Opacity Calculator for Radiative Transfer

Accelerating DEM simulations on GPUs by reducing the impact of warp divergences

GPGPU Performance and Power Estimation Using Machine Learning

Implementing Machine Learning Algorithms on GPUs for Real-Time Traffic Sign Classification

CUDA accelerated large scale vehicular area network simulator

RadixBoost: A Hardware Acceleration Structure for Scalable Radix Sort on Graphic Processors

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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