FRC: A High-Performance Concurrent Parallel Deferred Reference Counter for C++
We present FRC, a high-performance concurrent parallel reference counter for unmanaged languages. It is well known that high-performance garbage collectors help developers write memory-safe, highly concurrent systems and data structures. While C++, C, and other unmanaged languages are used in high-performance applications, adding concurrent memory management to these languages has proven to be difficult. Unmanaged languages like C++ use pointers instead of references, and have uncooperative mutators which do not pause easily at a safe point. Thus, scanning mutator stack root references is challenging.
FRC only defers decrements and does not require mutator threads to pause during collection. By deferring only decrements, FRC avoids much of the synchronization overhead of a fully-deferred implementation. Root references are scanned without interrupting the mutator by publishing these references to a thread-local array. FRC's performance can exceed that of the C++ standard library's shared pointer by orders of magnitude. FRC's thread-safety guarantees and low synchronization overhead enable significant throughput gains for concurrently-readable shared data structures.
We describe the components of FRC, including our static tree router data structure: a novel barrier which improves the scalability of parallel collection workers. FRC's performance is evaluated on several concurrent data structures. We release FRC and our tests as open-source code and expect FRC will be useful for many concurrent C++ software systems.
Mon 18 JunDisplayed time zone: Eastern Time (US & Canada) change
10:45 - 12:15 | Reference Counting and Techniques for C-family LanguagesISMM 2018 at Discovery AB Chair(s): Emery D. Berger University of Massachusetts, Amherst | ||
10:45 30mTalk | Detailed Heap Profiling ISMM 2018 | ||
11:15 30mTalk | FRC: A High-Performance Concurrent Parallel Deferred Reference Counter for C++ ISMM 2018 Charles Tripp Terrain Data, USA, David Hyde Stanford University, USA, Benjamin Grossman-Ponemon Terrain Data, USA | ||
11:45 30mTalk | Distributed Garbage Collection for General Graphs ISMM 2018 Steven R. Brandt Louisiana State University, Hari Krishnan Facebook, n.n., Costas Busch Louisiana State University, USA, Gokarna Sharma Kent State University, USA |