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Orchestrating Multiple Data-Parallel Kernels on Multiple Devices

Janghaeng Lee, Mehrzad Samadi, Scott Mahlke

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 750, nVidia GeForce GTX 760, OpenCL

November 29, 2015 by hgpu

Reordering GPU Kernel Launches to Enable Efficient Concurrent Execution

Teng Li, Vikram K. Narayana, Tarek El-Ghazawi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580

November 29, 2015 by hgpu

Design, Implementation and Performance Evaluation of a Stochastic Gradient Descent Algorithm on CUDA

Emanuele De Falco

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GT 540 M

November 29, 2015 by hgpu

Acceleration of Agent-Based Pandemic Modeling on Multiple GPUs

Barzan Shekh

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20, Thesis

November 25, 2015 by hgpu

Efficient Resource Sharing Through GPU Virtualization on Accelerated High Performance Computing Systems

Teng Li, Vikram K. Narayana, Tarek El-Ghazawi

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Tags: Computer science, CUDA, nVidia, Tesla C2070, Virtualization

November 25, 2015 by hgpu

Optimization of a Machine Learning Algorithm on the Heterogeneous system using OpenCL

Min Gyung Song, Dongweon Yoon

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Tags: Algorithms, AMD Radeon R9 290, ATI, Clustering, Computer science, Heterogeneous systems, Machine learning, OpenCL

November 25, 2015 by hgpu

GPU-based Acceleration of Deep Convolutional Neural Networks on Mobile Platforms

Seyyed Salar Latifi Oskouei, Hossein Golestani, Mohamad Kachuee, Matin Hashemi, Hoda Mohammadzade, Soheil Ghiasi

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Tags: ARM, Computer science, Computer vision, Deep learning, Machine learning, Neural networks, RenderScript

November 25, 2015 by hgpu

Pulsar Acceleration Searches on the GPU for the Square Kilometre Array

Sofia Dimoudi, Wesley Armour

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX Titan X, Tesla K80

November 25, 2015 by hgpu

Learning Representation for Scene Understanding: Epitomes, CRFs, and CNNs

Liang-Chieh Chen

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Tags: Caffe, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 650 M, OpenCV, Tesla K40, Thesis

November 24, 2015 by hgpu

A parallel algorithm for the constrained shortest path problem on lattice graphs

Ivan Matic

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Tags: Algorithms, AMD Radeon R9 290X, Mathematics, OpenCL, Path problems

November 24, 2015 by hgpu

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, Dongjun Shin

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Tags: ARM, Bayesian, Caffe, CNN, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah

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Tags: Caffe, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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high performance computing on graphics processing units: hgpu.org

Applications

Orchestrating Multiple Data-Parallel Kernels on Multiple Devices

Reordering GPU Kernel Launches to Enable Efficient Concurrent Execution

Design, Implementation and Performance Evaluation of a Stochastic Gradient Descent Algorithm on CUDA

Acceleration of Agent-Based Pandemic Modeling on Multiple GPUs

Efficient Resource Sharing Through GPU Virtualization on Accelerated High Performance Computing Systems

Optimization of a Machine Learning Algorithm on the Heterogeneous system using OpenCL

GPU-based Acceleration of Deep Convolutional Neural Networks on Mobile Platforms

Pulsar Acceleration Searches on the GPU for the Square Kilometre Array

Learning Representation for Scene Understanding: Epitomes, CRFs, and CNNs

A parallel algorithm for the constrained shortest path problem on lattice graphs

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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