C++ and Data

Abstract

High performance computing with a large code base and C++ has proved to be a good combination. But when it comes to storing data, C++ is a problematic choice: it offers no support for serialization, type definitions are amazingly complex to parse, and the dependency analysis (what does object A need to be stored?) is incredibly difficult. Nevertheless, the LHC data consists of C++ objects that are serialized with help from ROOT's reflection database and interpreter CINT. The fact that we can do it on that scale, and the performance with which we do it makes this approach unique and stirs interest even outside HEP. I will show how CINT collects and stores information about C++ types, what the current major challenges are (dictionary size!), and what CINT and ROOT have done and plan to do about it.

The Role of Interpreters in High Performance Computing

“…It is paramount for serialization of C++ objects and for interpreter access to compiled code. Another contribution discusses many of its details [8]; here we only introduce the properties most relevant for interpreters.…”