high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Tangram: a High-level Language for Performance Portable Code Synthesis

Li-Wen Chang, Abdul Dakkak, Christopher I. Rodrigues, Wen-mei Hwu

View

Download (PDF)

Tags: Computer science, High-level Languages, nVidia, OpenCL, Tesla C2050

January 26, 2015 by hgpu

GPU computing architecture for irregular parallelism

Wilson Wai Lun Fung

View

Download (PDF)

Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance, Thesis

January 26, 2015 by hgpu

Performance Analysis of Join Algorithms on GPUs

Ran Rui, Hao Li, Yi-Cheng Tu

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Databases, Join, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, Performance

January 26, 2015 by hgpu

Real-time physically cloth simulation with CUDA

Li Huaming, Kang Baosheng

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, OpenGL, Rendering

January 23, 2015 by hgpu

Revisit Long Short-Term Memory: An Optimization Perspective

Qi Lyu, Jun Zhu

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, MapReduce, Neural networks, nVidia, nVidia GeForce GTX 770

January 23, 2015 by hgpu

Taming the complexities of the C11 and OpenCL memory models

John Wickerson, Mark Batty

View

Download (PDF)

Source codes

Tags: Computer science, Heterogeneous systems, Memory model, OpenCL, Package

January 23, 2015 by hgpu

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Ana Lucia Varbanescu, Merijn Verstraaten, Cees de Laat, Ate Penders, Alexandru Iosup, Henk Sips

View

Download (PDF)

Tags: Algorithms, Computer science, Graph theory, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Tesla C2050

January 23, 2015 by hgpu

Gunrock: A High-Performance Graph Processing Library on the GPU

Yangzihao Wang, Andrew Davidson, Yuechao Pan, Yuduo Wu, Andy Riffel, John D. Owens

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Graph theory, nVidia, Package, Tesla K40

January 23, 2015 by hgpu

Reproducible and Accurate Matrix Multiplication for GPU Accelerators

Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat

View

Download (PDF)

Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Matrix multiplication, nVidia, OpenCL, Performance, Tesla K20

January 21, 2015 by hgpu

GPU concurrency: Weak behaviours and programming assumptions

Jade Alglave, Mark Batty, Alastair F. Donaldson, Ganesh Gopalakrishnan, Jeroen Ketema, Daniel Poetzl, Tyler Sorensen, John Wickerson

View

Download (PDF)

Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Computer science, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 540 M, nVidia GeForce GTX 660, nVidia GeForce GTX 750, nVidia GeForce GTX Titan, OpenCL, Performance, PTX, Tesla C2075

January 21, 2015 by hgpu

A Novel Implementation of QuickHull Algorithm on the GPU

Jiayin Zhang, Gang Mei, Nengxiong Xu, Kunyang Zhao

View

Download (PDF)

Tags: Computational Geometry, Computer science, CUDA, Graphics, nVidia, Tesla K20

January 21, 2015 by hgpu

Global finite element matrix construction based on a CPU-GPU implementation

Francisco Javier Ramírez-Gil, Marcos de Sales Guerra Tsuzuki, Wilfredo Montealegre-Rubio

View

Download (PDF)

Tags: Analysis of PDEs, Computational Engineering, CUDA, FEM, Numerical Analysis, parallel computing, PDEs, Performance

January 21, 2015 by fjramireg

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Programming

Tangram: a High-level Language for Performance Portable Code Synthesis

GPU computing architecture for irregular parallelism

Performance Analysis of Join Algorithms on GPUs

Real-time physically cloth simulation with CUDA

Revisit Long Short-Term Memory: An Optimization Perspective

Taming the complexities of the C11 and OpenCL memory models

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Gunrock: A High-Performance Graph Processing Library on the GPU

Reproducible and Accurate Matrix Multiplication for GPU Accelerators

GPU concurrency: Weak behaviours and programming assumptions

A Novel Implementation of QuickHull Algorithm on the GPU

Global finite element matrix construction based on a CPU-GPU implementation

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Most viewed papers (last 30 days)