high performance computing on graphics processing units: hgpu.org

Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi

View

Download (PDF)

Source codes

Tags: Benchmarking, Cloud, Computer science, CUDA, Databases, Machine learning, nVidia, Package, Tesla P100

March 6, 2022 by hgpu

FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours

Shenggan Cheng, Ruidong Wu, Zhongming Yu, Binrui Li, Xiwen Zhang, Jian Peng, Yang You

View

Download (PDF)

Source codes

Tags: Biology, Computer science, CUDA, Machine learning, nVidia, nVidia A100, Package

March 6, 2022 by hgpu

gLBM: A GPU enabled Lattice Boltzmann Method Library

Aaron Bray, Rachel B. Clipp, M. Umar Qureshi, Sorin Mitran, Andinet Enquobahrie

View

Download (PDF)

Source codes

Tags: cfd, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Package

February 20, 2022 by hgpu

Lightning: Scaling the GPU Programming Model Beyond a Single GPU

Stijn Heldens, Pieter Hijma, Ben van Werkhoven, Jason Maassen, Rob V. van Nieuwpoort

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Distributed computing, nVidia, OpenCL, Package, Performance, Tesla P100

February 20, 2022 by hgpu

Heuristic Adaptability to Input Dynamics for SpMM on GPUs

Guohao Dai, Guyue Huang, Shang Yang, Zhongming Yu, Hengrui Zhang, Yufei Ding, Yuan Xie, Huazhong Yang, Yu Wang

View

Download (PDF)

Source codes

Tags: Algorithms, CUDA, Matrix multiplication, Neural networks, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, Package, Sparse matrix, Tesla V100

February 20, 2022 by hgpu

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

Optimizing Performance and Energy Efficiency in Massively Parallel Systems

Persistent Kernels for Iterative Memory-bound GPU Applications

ALPINIST: An Annotation-Aware GPU Program Optimizer

One-shot tuner for deep learning compilers

Advanced Joins on GPUs

HipBone: A performance-portable GPU-accelerated C++ version of the NekBone benchmark

Romou: Rapidly Generate High-Performance Tensor Kernels for Mobile GPUs

FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours

gLBM: A GPU enabled Lattice Boltzmann Method Library

Lightning: Scaling the GPU Programming Model Beyond a Single GPU

Heuristic Adaptability to Input Dynamics for SpMM on GPUs

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)