high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » paper

A Semi-Automated Tool Flow for Roofline Anaylsis of OpenCL Kernels on Accelerators

Servesh Muralidharan, Kenneth O'Brien, Christian Lalanne

View

Download (PDF)

Tags: Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Performance, Tesla K20

December 8, 2015 by hgpu

MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, Zheng Zhang

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 980, Package

December 8, 2015 by hgpu

Towards Memory-Efficient Answering of Tree-Shaped SPARQL Queries using GPUs

Jedrzej Potoniec, Michal Madziar

View

Download (PDF)

Source codes

Tags: Computer science, Data mining, Databases, OpenCL, Package

December 8, 2015 by hgpu

Scaling Deep Learning on Multiple In-Memory Processors

Lifan Xu, Dong Ping Zhang, Nuwan Jayasena

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7970, Computer science, Deep learning, Machine learning, OpenCL

December 8, 2015 by hgpu

Nonlinear Dynamic Analysis Efficiency by Using a GPU Parallelization

Hong-yu Li, Jun Teng, Zuo-hua Li, Lu Zhang

View

Download (PDF)

Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GT 430, nVidia GeForce GT 720 M, nVidia GeForce GTX 460

December 8, 2015 by hgpu

A Survey Of Architectural Techniques for Managing Process Variation

Sparsh Mittal

View

Download (PDF)

Tags: cache, computer architecture, cpu, DVFS, GPU, Memory, survey

December 6, 2015 by sparsh0mittal

Using Data Compression for Increasing Efficiency of Data Transfer Between Main Memory and Intel Xeon Phi Coprocessor or NVidia GPU in Parallel DBMS

Konstantin Y. Besedin, Pavel S. Kostenetskiy, Stepan O. Prikazchikov

View

Download (PDF)

Tags: Algorithms, Compression, Computer science, CUDA, Databases, Intel Xeon Phi, nVidia, OpenMP, Tesla K40

December 6, 2015 by hgpu

A Study of Parallel Sorting Algorithms Using CUDA and OpenMP

Hakan Gokahmetoglu

View

Download (PDF)

Tags: Algorithms, Computational Complexity, Computer science, CUDA, nVidia, nVidia GeForce GTX 850 M, OpenMP, Sorting, Thesis

December 6, 2015 by hgpu

Parallel Implementation of Vortex Element Method on CPUs and GPUs

Kseniia Kuzmina, Ilia Marchevsky, Victoriya Moreva

View

Download (PDF)

Tags: CUDA, Fast multipole method, Fluid dynamics, MPI, nVidia, nVidia GeForce GTX 970, Tesla C2070

December 6, 2015 by hgpu

CuMF: scale matrix factorization using just ONE machine with GPUs

Wei Tan, Liangliang Cao

View

Download (PDF)

Tags: Computer science, CUDA, Data parallelism, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX Titan X

December 6, 2015 by hgpu

Parallelization Methods of the Template Matching Method on Graphics Accelerators

Gabor Kertesz, Sandor Szenasi, Zoltan Vamossy

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Image processing, nVidia, Tesla K40

December 6, 2015 by hgpu

The Genetic Convolutional Neural Network Model Based on Random Sample

You Zhining, Pu Yunming

View

Download (PDF)

Tags: Algorithms, CNN, Computer science, CUDA, Deep learning, Genetic algorithm, Neural networks, nVidia, nVidia GeForce GTX 770

December 4, 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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

A Semi-Automated Tool Flow for Roofline Anaylsis of OpenCL Kernels on Accelerators

MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

Towards Memory-Efficient Answering of Tree-Shaped SPARQL Queries using GPUs

Scaling Deep Learning on Multiple In-Memory Processors

Nonlinear Dynamic Analysis Efficiency by Using a GPU Parallelization

A Survey Of Architectural Techniques for Managing Process Variation

Using Data Compression for Increasing Efficiency of Data Transfer Between Main Memory and Intel Xeon Phi Coprocessor or NVidia GPU in Parallel DBMS

A Study of Parallel Sorting Algorithms Using CUDA and OpenMP

Parallel Implementation of Vortex Element Method on CPUs and GPUs

CuMF: scale matrix factorization using just ONE machine with GPUs

Parallelization Methods of the Template Matching Method on Graphics Accelerators

The Genetic Convolutional Neural Network Model Based on Random Sample

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

Most viewed papers (last 30 days)