high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

An Experimental Study of SYCL Task Graph Parallelism for Large-Scale Machine Learning Workloads

Cheng-Hsiang Chiu, Dian-Lun Lin, Tsung-Wei Huang

View

Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 2080, SYCL

September 26, 2021 by hgpu

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research

Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather

View

Tags: Artificial intelligence, Benchmarking, Compilers, Computer science, CUDA, Machine learning, nVidia, Package, Performance

September 26, 2021 by hgpu

A readahead prefetcher for GPU file system layer

Vasilis Dimitsas, Mark Silberstein

View

Tags: Benchmarking, Computer science, CUDA, nVidia, Prefetch, Tesla K40

September 19, 2021 by hgpu

Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability

Vincent R. Pascuzzi, Mehdi Goli

View

Tags: AMD Radeon RX Vega 56, ATI, Computer science, Heterogeneous systems, nVidia, nVidia A100, performance portability, Pseudo-random number generators, SYCL

September 19, 2021 by hgpu

Measurement and Analysis of GPU-accelerated Applications with HPCToolkit

Keren Zhou, Laksono Adhianto, Jonathon Anderson, Aaron Cherian, Dejan Grubisic, Mark Krentel, Yumeng Liu, Xiaozhu Meng, John Mellor-Crummey

View

Tags: AMD Radeon Instinct Mi50, ATI, Code generation, Computer science, HPC, nVidia, OpenCL, Performance, Tesla V100

September 19, 2021 by hgpu

GPU Algorithms for Efficient Exascale Discretizations

Ahmad Abdelfattah, Valeria Barra, Natalie Beams, Ryan Bleile, Jed Brown, Jean-Sylvain Camier, Robert Carson, Noel Chalmers, Veselin Dobrev, Yohann Dudouit, Paul Fischer, Ali Karakus, Stefan Kerkemeier, Tzanio Kolev, Yu-Hsiang Lan, Elia Merzari, Misun Min, Malachi Phillips, Thilina Rathnayake, Robert Rieben, Thomas Stitt, Ananias Tomboulides, Stanimire Tomov, Vladimir Tomov, Arturo Vargas, Tim Warburton, Kenneth Weiss

View

Tags: Algorithms, AMD Radeon Instinct MI100, ATI, Computer science, CUDA, Finite element method, nVidia, OCCA, Tesla V100

September 19, 2021 by hgpu

A Study of Mixed Precision Strategies for GMRES on GPUs

Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam

View

Tags: Algorithms, Computer science, CUDA, Linear Algebra, Mixed precision, nVidia, performance portability, Tesla V100

September 19, 2021 by hgpu

Supporting CUDA for an extended RISC-V GPU architecture

Ruobing Han, Blaise Tine, Jaewon Lee, Jaewoong Sim, Hyesoon Kim

View

Tags: Computer science, CUDA, LLVM, nVidia, OpenCL, Package, Programming Languages

September 5, 2021 by hgpu

Data-Oriented Language Implementation of Lattice-Boltzmann Method for Dense and Sparse Geometries

Tadeusz Tomczak

View

Tags: cfd, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX Titan XP, Package

September 5, 2021 by hgpu

WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU

Tian Lan, Sunil Srinivasa, Stephan Zheng

View

Tags: Computer science, CUDA, Machine learning, nVidia, Package, Python, Tesal V100

September 5, 2021 by hgpu

LocalityGuru: A PTX Analyzer for Extracting Thread Block-level Locality in GPGPUs

Devashree Tripathy, AmirAli Abdolrashidi, Quan Fan, Daniel Wong, Manoranjan Satpathy

View

Tags: Computer science, CUDA, nVidia, PTX

September 5, 2021 by hgpu

High Performance GPU Code Generation for Matrix-Matrix Multiplication using MLIR: Some Early Results

Navdeep Katel, Vivek Khandelwal, Uday Bondhugula

View

Tags: Code generation, Computer science, CUBLAS, CUDA, HPC, Matrix multiplication, nVidia, nVidia GeForce RTX 3090, Package

September 5, 2021 by hgpu

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

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

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

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

* * *

* * *

HGPU group © 2010-2024 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: