Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Numerical Analysis,Theoretical Computer Science,Software
Reference43 articles.
1. Alcides F, Bruno C (2013) miniumGPU: An Intelligent Framework for GPU Programming, Facing the Multicore-Challenge III, Volume 7686 of the series Lecture Notes in Computer Science, pp 96–107
2. Ashwin MA, Mayank D, Wu CF (2016) CampProf: A Visual Performance Analysis Tool for Memory Bound GPU Kernels, in https://vtechworks.lib.vt.edu/bitstream/handle/10919/19729/CampProf-TechReport.pdf?sequence=3&isAllowed=y . Accessed on 10 July 2016
3. Bacigalupo DA, Jarvis SA, He L, Spooner DP, Dillenberger DN, Nudd GR (2005) An investigation into the application of different performance prediction methods to distributed enterprise applications. J Supercomput 34:2
4. Barnes BJ, Rountree B, Lowenthal DK, Reeves J, de Supinski B, Schulz M (2008) A regression-based approach to scalability prediction. In: 22nd annual international conference on supercomputing
5. Benedict S, Rejitha RS, Phillip G, Prodan R, Fahringer T (2015) Energy prediction of OpenMP applications using random forest modeling approach. In: iWAPT2015 @ IPDPS, pp 1251–1260. doi: 10.1109/IPDPSW.2015.12
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Penalty-Enabled Serverless Architecture for Cloud-based Startup Solutions;2023 International Conference on Inventive Computation Technologies (ICICT);2023-04-26
2. Forecasting the energy intensity of industrial sector in China based on FCM-RS-SVM model;Environmental Science and Pollution Research;2023-02-01
3. Machine Learning for CUDA+MPI Design Rules;2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW);2022-05
4. Using Empirical Data for Scalability Analysis of Parallel Applications;Communications in Computer and Information Science;2019
5. Machine Learning in Compiler Optimization;Proceedings of the IEEE;2018-11