high performance computing on graphics processing units: hgpu.org

hgpu.org » Machine learning

MatConvNet – Convolutional Neural Networks for MATLAB

Andrea Vedaldi, Karel Lenc

View

Tags: Computer science, CUDA, Machine learning, Mathematical Software, Neural and Evolutionary Computing, Neural networks, nVidia

December 16, 2014 by hgpu

Minerva: A Scalable and Highly Efficient Training Platform for Deep Learning

Minjie Wang, Tianjun Xiao, Jianpeng Li, Jiaxing Zhang, Chuntao Hong, Zheng Zhang

View

Download (PDF)

Tags: Computer science, CUBLAS, CUDA, Machine learning, Neural networks, nVidia

December 15, 2014 by hgpu

Graph Processing on GPU

Zhang Jingbo

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Data mining, Graph theory, Machine learning, nVidia, nVidia GeForce 9400 GT, nVidia GeForce GT 330, nVidia GeForce GT 520, Thesis

December 14, 2014 by hgpu

Real-Time Grasp Detection Using Convolutional Neural Networks

Joseph Redmon, Anelia Angelova

View

Download (PDF)

Tags: CNN, Computer science, CUDA, Machine learning, Neural networks, nVidia, Tesla K20

December 12, 2014 by hgpu

Theano-based Large-Scale Visual Recognition with Multiple GPUs

Weiguang Ding, Ruoyan Wang, Fei Mao, Graham Taylor

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Data parallelism, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan, Package, Python

December 9, 2014 by hgpu

MLitB: Machine Learning in the Browser

Edward Meeds, Remco Hendriks, Said al Faraby, Magiel Bruntink, Max Welling

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, Distributed computing, Heterogeneous systems, Java, Machine learning, Neural networks, Package

December 9, 2014 by hgpu

Neural Networks through Shared Maps in Mobile Devices

William Raveane, Maria Angelica Gonzalez Arrieta

View

Download (PDF)

Tags: Computer science, Computer vision, Image recognition, Machine learning, Neural networks, OpenGL

December 7, 2014 by hgpu

An Approach for Maximizing Performance on Heterogeneous Clusters of CPU and GPU

Nam-Luc Tran, Sabri Skhiri, Arnaud Schils, Edgar Isaac Hiroshi Leon Saiki

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan, Package

December 2, 2014 by hgpu

An Open-Source GPU-Accelerated Feature Extraction Tool

Josef Michalek, Jan Vanek

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 660, OpenCL, Speech recognition

December 1, 2014 by hgpu

Dogwild! – Distributed Hogwild for CPU & GPU

Cyprien Noel, Simon Osindero

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, Distributed computing, Machine learning, Neural networks, nVidia

November 9, 2014 by hgpu

Sparse Recovery on GPUs: Accelerating the Iterative Soft-Thresholding Algorithm

Achal Shah, Angshul Majumdar

View

Download (PDF)

Tags: Algorithms, CUDA, Machine learning, nVidia, nVidia GeForce GTX 680, Signal processing

October 29, 2014 by hgpu

Parallel training of Deep Neural Networks with Natural Gradient and Parameter Averaging

Daniel Povey, Xiaohui Zhang, Sanjeev Khudanpur

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, Speech recognition, Tesla K10, Tesla K20

October 29, 2014 by hgpu

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

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

* * *

high performance computing on graphics processing units: hgpu.org

MatConvNet – Convolutional Neural Networks for MATLAB

Minerva: A Scalable and Highly Efficient Training Platform for Deep Learning

Graph Processing on GPU

Real-Time Grasp Detection Using Convolutional Neural Networks

Theano-based Large-Scale Visual Recognition with Multiple GPUs

MLitB: Machine Learning in the Browser

Neural Networks through Shared Maps in Mobile Devices

An Approach for Maximizing Performance on Heterogeneous Clusters of CPU and GPU

An Open-Source GPU-Accelerated Feature Extraction Tool

Dogwild! – Distributed Hogwild for CPU & GPU

Sparse Recovery on GPUs: Accelerating the Iterative Soft-Thresholding Algorithm

Parallel training of Deep Neural Networks with Natural Gradient and Parameter Averaging

Recent source codes

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

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Most viewed papers (last 30 days)