Work

Optimizing Frameworks’ Performance Using C++ Modules Aware ROOT

Year: 2019

Type: conference-paper

Abstract: ROOT is a data analysis framework broadly used in and outside of High Energy Physics (HEP). Since HEP software frameworks always strive for performance improvements, ROOT was extended with experimental support of runtime C++ Modules. C++ Modules are designed to improve the performance of C++ code parsing. C++ Modules offers a promising way to improve ROOT’s runtime performance by saving the C++ header parsing time which happens during ROOT runtime. This paper presents the results and challenges of integrating C++ Modules into ROOT.

Source: EPJ Web of Conferences

DOI: 10.1051/epjconf/201921402011

Authors: Yuka Takahashi, Vassil Vassilev, Oksana Shadura, Raphael Isemann

Institutions: Princeton University, European Organization for Nuclear Research, Chalmers University of Technology

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: National Science Foundation, U.S. Department of Energy, Office of Science

Awards: U.S. CMS Operations at the LHC, Collaborative Research: SI2-SSI: Data-Intensive Analysis for High Energy Physics (DIANA/HEP)