high performance computing on graphics processing units: hgpu.org

Packages

hgpu.org » Applications

Efficient Random Sampling – Parallel, Vectorized, Cache-Efficient, and Online

Peter Sanders, Sebastian Lamm, Lorenz Hubschle-Schneider, Emanuel Schrade, Carsten Dachsbacher

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Mathematical Software, nVidia, nVidia GeForce GTX 980 Ti, Package

October 22, 2016 by hgpu

OpenMP, OpenMP/MPI, and CUDA/MPI C programs for solving the time-dependent dipolar Gross-Pitaevskii equation

Vladimir Loncar, Luis E. Young-S., Srdjan Skrbic, Paulsamy Muruganandam, Sadhan K. Adhikari, Antun Balaz

View

Download (PDF)

Source codes

Tags: Condensed matter, CUDA, MPI, nVidia, OpenMP, Package, Physics, Tesla M2090

October 22, 2016 by hgpu

CuMF_SGD: Fast and Scalable Matrix Factorization

Xiaolong Xie, Wei Tan, Liana L. Fong, Yun Liang

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Factorization, Machine learning, nVidia, nVidia GeForce GTX Titan X, Package

October 22, 2016 by hgpu

Machine Learning Based Intrusion Detection in Controller Area Networks

Roar Elias Georgsen

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, DSP, FPGA, Machine learning, OpenCL, Package, Python, Security, SoC

October 15, 2016 by hgpu

Embedded real-time stereo estimation via Semi-Global Matching on the GPU

Daniel Hernandez-Juarez, Alejandro Chacon, Antonio Espinosa, David Vazquez, Juan Carlos Moure, Antonio Manuel Lopez

View

Download (PDF)

Source codes

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1, Package

October 15, 2016 by hgpu

GPU-accelerated real-time stixel computation

Daniel Hernandez-Juarez, Antonio Espinosa, David Vazquez, Antonio Manuel Lopez, Juan Carlos Moure

View

Download (PDF)

Source codes

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1, Package

October 15, 2016 by hgpu

Neural Network Computing Using On-Chip Accelerators

Schuyler Eldridge

View

Download (PDF)

Source codes

Tags: Artificial intelligence, Computer science, Deep learning, Machine learning, Neural networks, Package, Thesis

October 12, 2016 by hgpu

BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images

Pilar Cossio, David Rohr, Fabio Baruffa, Markus Rampp, Volker Lindenstruth, Gerhard Hummer

View

Download (PDF)

Source codes

Tags: Bayesian, Biology, Biomolecules, CUDA, Electron microscopy, Heterogeneous systems, Medicine, Microscopy, MPI, nVidia, nVidia GeForce GTX Titan, OpenMP, Package, Tesla K20, Tomography

October 8, 2016 by hgpu

APL on GPUs: A TAIL from the Past, Scribbled in Futhark

Troels Henriksen, Martin Dybdal, Henrik Urms, Anna Sofie Kiehn, Daniel Gavin, Hjalte Abelskov, Martin Elsman, Cosmin Oancea

View

Download (PDF)

Source codes

Tags: Compilers, Computer science, nVidia, nVidia GeForce GTX 780 Ti, OpenCL, Package, PyOpenCL, Python, Visualization

October 4, 2016 by hgpu

Caffeinated FPGAs: FPGA Framework For Convolutional Neural Networks

Roberto DiCecco, Griffin Lacey, Jasmina Vasiljevic, Paul Chow, Graham Taylor, Shawki Areibi

View

Download (PDF)

Source codes

Tags: Benchmarking, Caffe, Computer science, Deep learning, FPGA, Machine learning, Neural networks, OpenCL, Package

October 4, 2016 by hgpu

Training a Feedback Loop for Hand Pose Estimation

Markus Oberweger, Paul Wohlhart, Vincent Lepetit

View

Download (PDF)

Source codes

Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX 780 Ti, Package, Theano

October 4, 2016 by hgpu

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 750, Package, Python

September 27, 2016 by hgpu

AutoDock-GPU: AutoDock for GPUs and other accelerators

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

NCCLX: collective communication framework

Collective Communication for 100k+ GPUs

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Packages

Efficient Random Sampling – Parallel, Vectorized, Cache-Efficient, and Online

OpenMP, OpenMP/MPI, and CUDA/MPI C programs for solving the time-dependent dipolar Gross-Pitaevskii equation

CuMF_SGD: Fast and Scalable Matrix Factorization

Machine Learning Based Intrusion Detection in Controller Area Networks

Embedded real-time stereo estimation via Semi-Global Matching on the GPU

GPU-accelerated real-time stixel computation

Neural Network Computing Using On-Chip Accelerators

BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images

APL on GPUs: A TAIL from the Past, Scribbled in Futhark

Caffeinated FPGAs: FPGA Framework For Convolutional Neural Networks

Training a Feedback Loop for Hand Pose Estimation

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Recent source codes

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

Most viewed papers (last 30 days)