Performance prediction of GPU-based deep learning applications
Eugenio Gianniti, Li Zhang, et al.
CLOSER 2019
In this paper we develop a general methodology for characterizing the access patterns of Web server requests based on a time‐series analysis of finite collections of observed data from real systems. Our approach is used together with the access logs from the IBM Web site for the Olympic Games to demonstrate some of its advantages over previous methods and to construct a particular class of benchmarks for large‐scale heavily‐accessed Web server environments. We then apply an instance of this class of benchmarks to analyze aspects of large‐scale Web server performance, demonstrating some additional problems with methods commonly used to evaluate Web server performance at different request traffic intensities.
Eugenio Gianniti, Li Zhang, et al.
CLOSER 2019
Jian Tan, Parijat Dube, et al.
ICDCS 2011
Soumyadip Ghosh, Mark S. Squillante
WSC 2022
Xingbo Wu, Li Zhang, et al.
EuroSys 2016