high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation

Jianhui Li, Zhennan Qin, Yijie Mei, Jingze Cui, Yunfei Song, Ciyong Chen, Yifei Zhang, Longsheng Du, Xianhang Cheng, Baihui Jin, Jason Ye, Eric Lin, Dan Lavery

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Tags: Code generation, Compilers, Computer science, Deep learning, OpenCL, Package

January 8, 2023 by hgpu

BaCO: A Fast and Portable Bayesian Compiler Optimization Framework

Erik Hellsten, Artur Souza, Johannes Lenfers, Rubens Lacouture, Olivia Hsu, Adel Ejjeh, Fredrik Kjolstad, Michel Steuwer, Kunle Olukotun, Luigi Nardi

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Tags: Bayesian, Compilers, Computer science, FPGA, nVidia, OpenCL, Package, Performance, Programming Languages, Tesla K80

January 8, 2023 by hgpu

Arax: a runtime framework for decoupling applications from heterogeneous accelerators

Manos Pavlidakis, Stelios Mavridis, Antony Chazapis, Giorgos Vasiliadis, Angelos Bilas

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce RTX 2080, OpenCL, Package

January 8, 2023 by hgpu

Understanding the Impact of Input Entropy on FPU, CPU, and GPU Power

Sridutt Bhalachandra, Brian Austin, Samuel Williams, Nicholas J. Wright

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Tags: Computer science, Hardware Architecture, nVidia, nVidia A100, Package, Performance

December 25, 2022 by hgpu

Extending MAGMA Portability with OneAPI

Anna Fortenberry, Stanimire Tomov

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce RTX 3060, oneAPI, Package, performance portability

December 25, 2022 by hgpu

mu-grind: A Framework for Dynamically Instrumenting HLS-Generated RTL

Parmida Vahdatniya, Amirali Sharifian, Reza Hojabr, Arrvindh Shriraman

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, Package, Scala

December 25, 2022 by hgpu

GPU Load Balancing

Muhammad Osama

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, load balancing, Matrix multiplication, nVidia, nVidia A100, Package, Sparse, Thesis

December 25, 2022 by hgpu

Kernel-as-a-Service: A Serverless Interface to GPUs

Nathan Pemberton, Anton Zabreyko, Zhoujie Ding, Randy Katz, Joseph Gonzalez

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Tags: Cloud, Computer science, CUDA, Deep learning, Distributed computing, nVidia, Package, Tesla V100

December 25, 2022 by hgpu

A Framework to Generate High-Performance Time-stepped Agent-based Simulations on Heterogeneous Hardware

Jiajian Xiao

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Tags: Computer science, FPGA, Heterogeneous systems, nVidia GeForce GTX 1060, nVidia GeForce RTX 2080 Ti, OpenCL, Thesis

December 19, 2022 by hgpu

Code Generation from Functional to Imperative: Combining Destination-Passing Style and Views

Zhitao Lin

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Tags: Code generation, Computer science, nVidia, nVidia GeForce GTX 940 M, OpenCL, Thesis

December 19, 2022 by hgpu

Portable C++ Code that can Look and Feel Like Fortran Code with Yet Another Kernel Launcher (YAKL)

Matthew Norman, Isaac Lyngaas, Abhishek Bagusetty, Mark Berrill

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Tags: Computer science, Fortran, nVidia, Package, SYCL, Tesla V100

December 19, 2022 by hgpu

A Study on the Intersection of GPU Utilization and CNN Inference

Jack Kosaian, Amar Phanishayee

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Tags: CNN, Computer science, Deep learning, Neural networks, nVidia, Performance, Tesla V100

December 19, 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

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high performance computing on graphics processing units: hgpu.org

Applications

oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation

BaCO: A Fast and Portable Bayesian Compiler Optimization Framework

Arax: a runtime framework for decoupling applications from heterogeneous accelerators

Understanding the Impact of Input Entropy on FPU, CPU, and GPU Power

Extending MAGMA Portability with OneAPI

mu-grind: A Framework for Dynamically Instrumenting HLS-Generated RTL

GPU Load Balancing

A Framework to Generate High-Performance Time-stepped Agent-based Simulations on Heterogeneous Hardware

Code Generation from Functional to Imperative: Combining Destination-Passing Style and Views

Portable C++ Code that can Look and Feel Like Fortran Code with Yet Another Kernel Launcher (YAKL)

A Study on the Intersection of GPU Utilization and CNN Inference

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

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