high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Priya Goyal, Piotr Dollar, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, Kaiming He

View

Download (PDF)

Source codes

Tags: Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla P100

June 10, 2017 by hgpu

Crane – Fast and Migratable GPU Passthrough for OpenCL applications

James Gleeson, Daniel Kats, Charlie Mei, Eyal de Lara

View

Download (PDF)

Tags: Computer science, nVidia, nVidia Grid K1, OpenCL, Virtualization

June 10, 2017 by hgpu

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

Qingqing Cao, Niranjan Balasubramanian, Aruna Balasubramanian

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Java, Neural networks, nVidia, Package, RNN, TensorFlow

June 10, 2017 by hgpu

CELES: CUDA-accelerated simulation of electromagnetic scattering by large ensembles of spheres

Amos Egel, Lorenzo Pattelli, Giacomo Mazzamuto, Diederik S. Wiersma, Uli Lemmer

View

Download (PDF)

Source codes

Tags: Computational Physics, CUDA, Matlab, nVidia, nVidia GeForce GTX 980 Ti, nVidia GeForce GTX Titan X, Optics, Package, Physics

June 10, 2017 by hgpu

Neneta: Heterogeneous Computing Complex-Valued Neural Network Framework

Vladimir Lekic, Zdenka Babic

View

Download (PDF)

Tags: ATI, ATI Radeon HD 5770, Computer science, Deep learning, Heterogeneous systems, Neural networks, OpenCL

June 5, 2017 by hgpu

Speedup and Parallelization Models for Energy-Efficient Many-Core Systems Using Performance Counters

Mohammed A. Noaman Al-hayanni, Rishad Shafik, Ashur Rafiev, Fei Xia, Alex Yakovlev

View

Download (PDF)

Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Performance

June 5, 2017 by hgpu

Program Acceleration in a Heterogeneous Computing Environment Using OpenCL, FPGA, and CPU

Herman Noel Hoffman

View

Download (PDF)

Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, SoC, Thesis

June 5, 2017 by hgpu

UT-OCL: An OpenCL Framework for Embedded Systems Using Xilinx FPGAs

Vincent Mirian

View

Download (PDF)

Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, SoC, Thesis

June 5, 2017 by hgpu

A Diversified Multi-Start Algorithm for Unconstrained Binary Quadratic Problems Leveraging the Graphics Processor Unit

Mark W. Lewis

View

Download (PDF)

Tags: Algorithms, Artificial intelligence, Benchmarking, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTS 780 Ti

June 5, 2017 by hgpu

Fast MPEG-CDVS Encoder with GPU-CPU Hybrid Computing

Lingyu Duan, Wei Sun, Xinfeng Zhang, Jie Chen, Jianxiong Yin, Simon See, Tiejun Huang, Alex C. Kot, Wen Gao

View

Download (PDF)

Tags: Benchmarking, CUDA, Hybrid computing, Image processing, Neural networks, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 1080, nVidia GeForce GTX 1080 Ti, nVidia Tegra TX1, Tesla M40

June 1, 2017 by hgpu

A performance spectrum for parallel computational frameworks that solve PDEs

J. Chang, K. B. Nakshatrala, M. G. Knepley, L. Johnsson

View

Download (PDF)

Tags: Computational Physics, Computer science, Intel Xeon Phi, Mathematical Software, MPI, Partial differential equations, PDEs

June 1, 2017 by hgpu

SparkJNI: A Reference Design for a Heterogeneous Apache Spark Framework

Tudor Alexandru Voicu

View

Download (PDF)

Tags: big data, Computer science, FPGA, Heterogeneous systems, Hybrid computing, Java, OpenCL, Spark, Thesis

June 1, 2017 by hgpu

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

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

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

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Crane – Fast and Migratable GPU Passthrough for OpenCL applications

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

CELES: CUDA-accelerated simulation of electromagnetic scattering by large ensembles of spheres

Neneta: Heterogeneous Computing Complex-Valued Neural Network Framework

Speedup and Parallelization Models for Energy-Efficient Many-Core Systems Using Performance Counters

Program Acceleration in a Heterogeneous Computing Environment Using OpenCL, FPGA, and CPU

UT-OCL: An OpenCL Framework for Embedded Systems Using Xilinx FPGAs

A Diversified Multi-Start Algorithm for Unconstrained Binary Quadratic Problems Leveraging the Graphics Processor Unit

Fast MPEG-CDVS Encoder with GPU-CPU Hybrid Computing

A performance spectrum for parallel computational frameworks that solve PDEs

SparkJNI: A Reference Design for a Heterogeneous Apache Spark Framework

Recent source codes

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

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

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

Most viewed papers (last 30 days)