2018/03/20 by Ronny Brendel, Bert Wesarg, Brendel, Ronny +9 · 1 voice
Computer Science · #Cloud Computing and Resource Management #FOS: Computer and information sciences #Parallel Computing and Optimization Techniques #Software Engineering (cs.SE) #Software System Performance and Reliability #cs.SE
paper · pdf · doi:10.48550/arxiv.1803.07495
openalex publication_date 2018/03/20 · arxiv published 2018/03/20 · arxiv updated 2018/03/20 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
As applications grow in capability, they also grow in complexity. This complexity in turn gets pushed into modules and libraries. In addition, hardware configurations become increasingly elaborate, too. These two trends make understanding, debugging and analyzing the performance of applications more and more difficult. To enable detailed insight into library usage of applications, we present an approach and implementation in Score-P that supports intuitive and robust creation of wrappers for arbitrary C/C++ libraries. Runtime analysis then uses these wrappers to keep track of how applications interact with libraries, how they interact with each other, and record the exact timing of their functions.