Optimization Techniques for GPU Programming
54
TL;DR: In this article , a survey discusses various optimization techniques found in 450 articles published in the last 14 years and analyzes the optimizations from different perspectives which shows that the various optimizations are highly interrelated, explaining the need for techniques such as auto-tuning.
read more
Abstract: In the past decade, Graphics Processing Units have played an important role in the field of high-performance computing and they still advance new fields such as IoT, autonomous vehicles, and exascale computing. It is therefore important to understand how to extract performance from these processors, something that is not trivial. This survey discusses various optimization techniques found in 450 articles published in the last 14 years. We analyze the optimizations from different perspectives which shows that the various optimizations are highly interrelated, explaining the need for techniques such as auto-tuning.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Unleashing the potential: AI empowered advanced metasurface research
Yunlai Fu,Xuxi Zhou,Yiwan Yu,Jiawang Chen,Shuming Wang,Shining Zhu,Zhenlin Wang +6 more
TL;DR: AI-powered advanced metasurface research explores the intersection of AI and metasurfaces, leveraging AI's computational power to design, analyze, and optimize metasurfaces for various applications.
GPU acceleration of Levenshtein distance computation between long strings
TL;DR: In this paper , a GPU implementation of the WFA algorithm and a new optimization that can halve the elements to be computed, providing additional performance gains, are presented, which is the best ever reported.
7
Progress and Opportunities of Foundation Models in Bioinformatics
Qing Li,Zhihang Hu,Yixuan Wang,Lei Li,Yimin Fan,Irwin King,Le Song,Yu Li +7 more
TL;DR: A systematic investigation and summary of FMs in bioinformatics, tracing their evolution, current research status, and the methodologies employed, aiming to guide the research community in choosing appropriate FMs for their research needs.
6
Sustainable Optimizing Performance and Energy Efficiency in Proof of Work Blockchain: A Multilinear Regression Approach
Meennapa Rukhiran,Songwut Boonsong,Paniti Netinant +2 more
TL;DR: The results reveal that strategically adjusting GPU hardware, software, and configuration can preserve substantial energy while preserving computational efficiency, and offer practical recommendations for optimizing the feature configurations of GPUs to reduce energy consumption, mitigate the environmental impacts of blockchain operations, and contribute to the current research on performance in PoW blockchain applications.
6
References
Memory-Efficient Parallelization of 3D Lattice Boltzmann Flow Solver on a GPU
Nhat-Phuong Tran,Myungho Lee,Dong Hoon Choi +2 more
- 16 Dec 2015
TL;DR: This paper parallelize the LBM on a GPU by incorporating memory-efficient techniques such as the tiling optimization with the data layout changes and the data update scheme so called a pull scheme, and developed optimization techniquessuch as removing branch divergences, reducing the register uses, and reducing the number of double precision floating-point instructions.
21
Optimizing memory access on GPUs using morton order indexing
Anthony E. Nocentino,Philip J. Rhodes +1 more
- 15 Apr 2010
TL;DR: This paper describes an optimization of memory access methods on GPUs using Morton order indexing, sometimes referred to as Z-order index.
21
Automatic Tuning of Sparse Matrix-Vector Multiplication for CRS Format on GPUs
Hiroki Yoshizawa,Daisuke Takahashi +1 more
- 05 Dec 2012
TL;DR: It is shown that the performance achieved using kernel SpMV on GPUs for the compressed row storage (CRS) format depends greatly on optimal selection of a parameter, and an efficient algorithm is proposed for the automatic selection of the optimal parameter.
20
A GPU Implementation of Dynamic Programming for the Optimal Polygon Triangulation
Yasuaki Ito,Koji Nakano +1 more
TL;DR: The implementation using two new ideas to accelerate the dynamic programming solves the optimal polygon triangulation problem for a convex 8192-gon in 5.57 seconds on the NVIDIA GeForce GTX 680, while a conventional CPU implementation runs in 1939.
Performance modeling and optimization of sparse matrix-vector multiplication on NVIDIA CUDA platform
Shiming Xu,Wei Xue,Hai Xiang Lin +2 more
TL;DR: This article proposes optimization of Sparse Matrix-Vector Multiplication based on ELLPACK from two aspects:enhanced performance for the dense vector by reducing cache misses, and reduce accessed matrix data by index reduction.