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hgpu.org » Optimization

Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers

Anjiang Wei, Allen Nie, Thiago S. F. X. Teixeira, Rohan Yadav, Wonchan Lee, Ke Wang, Alex Aiken

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Tags: Code generation, Computer science, DSL, LLM, Matrix multiplication, nVidia, Optimization, Tesla P100

November 17, 2024 by hgpu

Challenging Portability Paradigms: FPGA Acceleration Using SYCL and OpenCL

Manuel de Castro, Francisco J. andújar, Roberto R. Osorio, Rocío Carratalá-Sáez, Diego R. Llanos

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Tags: Computer science, FPGA, OpenCL, Optimization, performance portability, SYCL

September 22, 2024 by hgpu

DNA sequence alignment: An assignment for OpenMP, MPI, and CUDA/OpenCL

Arturo Gonzalez-Escribano, Diego García-Álvarez, Jesús Cámara

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Tags: Bioinformatics, Biology, CUDA, MPI, nVidia, nVidia A100, nVidia GeForce GTX Titan X, nVidia GeForce RTX 4050, OpenCL, Optimization, Sequence alignment

September 15, 2024 by hgpu

Optimizing the Weather Research and Forecasting Model with OpenMP Offload and Codee

Chayanon (Namo)Wichitrnithed, Woo-Sun-Yang, Yun (Helen)He, Brad Richardson, Koichi Sakaguchi, Manuel Arenaz, William I. Gustafson Jr., Jacob Shpund, Ulises Costi Blanco, Alvaro Goldar Dieste

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Tags: Computer science, CUDA, Fortran, MPI, nVidia, nVidia A100, OpenMP, Optimization, Package, Weather prediction

September 15, 2024 by hgpu

Optimization of Large-Scale Sparse Matrix-Vector Multiplication on Multi-GPU Systems

Jianhua Gao, Weixing Ji, Yizhuo Wang

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Optimization, Sparse matrix, Tesla V100

July 14, 2024 by hgpu

Performance portability analysis of SYCL with a classical CG on CPU, GPU, and FPGA

Julian Franquinet

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Tags: Benchmarking, Computer science, CUDA, FPGA, nVidia, nVidia Quadro GP100, Optimization, Performance, performance portability, SYCL

October 22, 2023 by hgpu

Managing, Profiling, and Optimizing Heterogeneous GPU Workloads

James Gleeson

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Tags: Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce GTX 480, nVidia GeForce RTX 2080 Ti, nVidia Grid K1, Optimization, Package, Performance, Tesla V100, Thesis, Virtualization

July 2, 2023 by hgpu

A Survey on Optimization Techniques for Edge Artificial Intelligence (AI)

Chellammal Surianarayanan, John Jeyasekaran Lawrence, Pethuru Raj Chelliah, Edmond Prakash, Chaminda Hewage

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Tags: Artificial intelligence, Computer science, Energy-efficient computing, Optimization, survey

February 12, 2023 by hgpu

TLP: A Deep Learning-based Cost Model for Tensor Program Tuning

Yi Zhai, Yu Zhang, Shuo Liu, Xiaomeng Chu, Jie Peng, Jianmin Ji, Yanyong Zhang

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Tags: Computer science, CUDA, Deep learning, nVidia, Optimization, Package, Tesla K80, Tesla T4

February 12, 2023 by hgpu

Deep Learning Approaches to Source Code Analysis for Optimization of Heterogeneous Systems: Recent Results, Challenges and Opportunities

Francesco Barchi, Emanuele Parisi, Andrea Bartolini, Andrea Acquaviva

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Tags: AMD Radeon HD 7970, ATI, Computer science, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 970, OpenCL, Optimization, Overview, Security

August 7, 2022 by hgpu

Optimizing the Performance of Parallel and Concurrent Applications Based on Asynchronous Many-Task Runtimes

Weile Wei

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Package, QMC, Tesla V100, Thesis

July 3, 2022 by hgpu

MapReduce for Counting Word Frequencies with MPI and GPUs

Nithin Kavi

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Tags: Algorithms, Computer science, CUDA, Julia, MapReduce, MPI, NLP, nVidia, Optimization, Package, Tesla V100

June 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

Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers

Challenging Portability Paradigms: FPGA Acceleration Using SYCL and OpenCL

DNA sequence alignment: An assignment for OpenMP, MPI, and CUDA/OpenCL

Optimizing the Weather Research and Forecasting Model with OpenMP Offload and Codee

Optimization of Large-Scale Sparse Matrix-Vector Multiplication on Multi-GPU Systems

Performance portability analysis of SYCL with a classical CG on CPU, GPU, and FPGA

Managing, Profiling, and Optimizing Heterogeneous GPU Workloads

A Survey on Optimization Techniques for Edge Artificial Intelligence (AI)

TLP: A Deep Learning-based Cost Model for Tensor Program Tuning

Deep Learning Approaches to Source Code Analysis for Optimization of Heterogeneous Systems: Recent Results, Challenges and Opportunities

Optimizing the Performance of Parallel and Concurrent Applications Based on Asynchronous Many-Task Runtimes

MapReduce for Counting Word Frequencies with MPI and 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

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