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
A study of Persistent Threads style GPU programming for GPGPU workloads
Kshitij Gupta,Jeff A. Stuart,John D. Owens +2 more
- 13 May 2012
TL;DR: Through micro-kernel benchmarks, it is shown the PT approach can achieve up to an order-of-magnitude speedup over nonPT kernels, but can also result in performance loss in many cases.
Debunking the 100X GPU vs. CPU myth
W LeeVictor,KimChangkyu,ChhuganiJatin,DeisherMichael,KimDaehyun,D NguyenAnthony,SatishNadathur,SmelyanskiyMikhail,ChennupatySrinivas,HammarlundPer,SinghalRonak,DubeyPradeep +11 more
TL;DR: This research presents a novel and scalable approach to throughput computing that combines reinforcement learning, artificial intelligence, and reinforcement learning to solve the challenge of integrating NoSQL data stores to manage massive amounts of data.
264
Medusa: Simplified Graph Processing on GPUs
Jianlong Zhong,Bingsheng He +1 more
TL;DR: This work proposes a programming framework called Medusa which enables developers to leverage the capabilities of GPUs by writing sequential C/C++ code and develops a series of graph-centric optimizations based on the architecture features of GPUs for efficiency.
258
An effective GPU implementation of breadth-first search
Lijuan Luo,Martin D. F. Wong,Wen-mei W. Hwu +2 more
- 13 Jun 2010
TL;DR: A new GPU implementation of BFS that uses a hierarchical queue management technique and a three-layer kernel arrangement strategy that guarantees the same computational complexity as the fastest sequential version and can achieve up to 10 times speedup.
A Unified Sparse Matrix Data Format for Efficient General Sparse Matrix-Vector Multiplication on Modern Processors with Wide SIMD Units
TL;DR: This work suggests SELL-$C$-$\sigma, a variant of Sliced ELLPACK, as a SIMD-friendly data format which combines long-standing ideas from general-purpose graphics processing units and vector computer programming and shows its suitability on a variety of hardware platforms.