high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data

Xinyu Chen, Jiannan Tian, Ian Beaver, Cynthia Freeman, Yan Yan, Jianguo Wang, Dingwen Tao

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Tags: Benchmarking, Compression, Computer science, CUDA, Databases, HPC, nVidia, nVidia RTX 6000 Ada, Package, SYCL

December 24, 2023 by hgpu

Experiences Building an MLIR-based SYCL Compiler

Ettore Tiotto, Víctor Pérez, Whitney Tsang, Lukas Sommer, Julian Oppermann, Victor Lomüller, Mehdi Goli, James Brodman

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Tags: Compilers, Computer science, Heterogeneous systems, Performance, Programming Languages, SYCL

December 24, 2023 by hgpu

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

Xin Jin, Jonathan Larson, Weiwei Yang, Zhiqiang Lin

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Tags: Benchmarking, Computer science, nVidia, nVidia A100, Software Engineering

December 24, 2023 by hgpu

Comparative Performance and Scalability Analysis of GPU-accelerated Database Operations

Carl Andersson, Jonathan Nilsson

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Tags: Benchmarking, Computer science, CUDA, Databases, nVidia, nVidia A10, nVidia M60, Performance, Tesla T4, Thesis

December 24, 2023 by hgpu

Scalable Tuning of (OpenMP) GPU Applications via Kernel Record and Replay

Konstantinos Parasyris, Giorgis Georgakoudis, Esteban Rangel, Ignacio Laguna, Johannes Doerfert

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Tags: AMD Radeon Instinct MI250X, ATI, Auto-Tuning, Computer science, Heterogeneous systems, nVidia, nVidia V100, OpenMP, Package

December 18, 2023 by hgpu

cuSZ-I: High-Fidelity Error-Bounded Lossy Compression for Scientific Data on GPUs

Jinyang Liu, Jiannan Tian, Shixun Wu, Sheng Di, Boyuan Zhang, Yafan Huang, Kai Zhao, Guanpeng Li, Dingwen Tao, Zizhong Chen, Franck Cappello

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Tags: Compression, Computer science, CUDA, nVidia, nVidia A100, nVidia A40

December 18, 2023 by hgpu

Precision and Performance Analysis of C Standard Math Library Functions on GPUs

Anton Rydahl, Joseph Huber, Ethan Luis McDonough, Johannes Doerfert

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Tags: AMD Radeon Instinct MI250X, AMD Radeon Instinct Mi50, ATI, Benchmarking, Compilers, Computer science, CUDA, HIP, Numerical Analysis, OpenMP, Performance, Tesla A100, Tesla V100

December 18, 2023 by hgpu

Application Performance Profiling on Intel GPUs with Oneprof and Onetrace

Mariam Umar, Maxwell Jong

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Tags: Computer science, Intel, Intel Data Center GPU Max 1550, OpenCL, OpenMP, Package, Performance

December 18, 2023 by hgpu

Principles for Automated and Reproducible Benchmarking

Tuomas Koskela, Ilektra Christidi, Mosè Giordano, Emily Dubrovska, Jamie Quinn, Christopher Maynard, Dave Case, Kaan Olgu, Tom Deakin

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Tags: Benchmarking, Computer science, HPC, nVidia, oneAPI, Package, performance portability

December 18, 2023 by hgpu

Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow Posts

Wenhua Yang, Chong Zhang, Minxue Pan

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Tags: Computer science, CUDA, nVidia, OpenCL, Programming Languages, survey

December 10, 2023 by hgpu

Efficiently Processing Large Relational Joins on GPUs

Bowen Wu, Dimitrios Koutsoukos, Gustavo Alonso

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Tags: Benchmarking, Computer science, CUDA, Databases, nVidia, nVidia A100, nVidia GeForce RTX 3090, Package

December 10, 2023 by hgpu

Edge AI for Internet of Energy: Challenges and Perspectives

Yassine Himeur, Aya Nabil Sayed, Abdullah Alsalemi, Faycal Bensaali, Abbes Amira

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Tags: Artificial intelligence, Computer science, Energy-efficient computing, Review

December 10, 2023 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

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high performance computing on graphics processing units: hgpu.org

Applications

FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data

Experiences Building an MLIR-based SYCL Compiler

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

Comparative Performance and Scalability Analysis of GPU-accelerated Database Operations

Scalable Tuning of (OpenMP) GPU Applications via Kernel Record and Replay

cuSZ-I: High-Fidelity Error-Bounded Lossy Compression for Scientific Data on GPUs

Precision and Performance Analysis of C Standard Math Library Functions on GPUs

Application Performance Profiling on Intel GPUs with Oneprof and Onetrace

Principles for Automated and Reproducible Benchmarking

Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow Posts

Efficiently Processing Large Relational Joins on GPUs

Edge AI for Internet of Energy: Challenges and Perspectives

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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