TY - GEN
T1 - Nesting-safe recoverable linearizability
T2 - 37th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing, PODC 2018
AU - Attiya, Hagit
AU - Ben-Baruch, Ohad
AU - Hendler, Danny
N1 - Funding Information:
∗This research was partially supported by the Israel Science Foundation (grant 1749/14) and by the Lynne and William Frankel Center for Computing Science at Ben-Gurion University.
Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/7/23
Y1 - 2018/7/23
N2 - We presents a novel abstract individual-process crash-recovery model for non-volatile memory, which enables modularity, so that complex recoverable objects can be constructed in a modular manner from simpler recoverable base objects. Within the framework of this model, we define nesting-safe recoverable linearizability (NRL) - a novel correctness condition that captures the requirements for nesting recoverable objects. Informally, NRL allows the recovery code to extend the interval of the failed operation until the recovery code succeeds to complete (possibly after multiple failures and recovery attempts). Unlike previous correctness definitions, the NRL condition implies that, following recovery, an implemented (higher-level) recoverable operation is able to complete its invocation of a base-object operation and obtain its response. We present algorithms for nesting-safe recoverable primitives, namely, recoverable versions of widely-used primitive shared-memory operations such as read, write, test-and-set and compare- and-swap, which can be used to implement higher-level recoverable objects. We then exemplify how these recoverable base objects can be used for constructing a recoverable counter object. Finally, we prove an impossibility result on wait-free implementations of recoverable test-and-set (TAS) objects from read, write and TAS operations, thus demonstrating that our model also facilitates rigorous analysis of the limitations of recoverable concurrent objects.
AB - We presents a novel abstract individual-process crash-recovery model for non-volatile memory, which enables modularity, so that complex recoverable objects can be constructed in a modular manner from simpler recoverable base objects. Within the framework of this model, we define nesting-safe recoverable linearizability (NRL) - a novel correctness condition that captures the requirements for nesting recoverable objects. Informally, NRL allows the recovery code to extend the interval of the failed operation until the recovery code succeeds to complete (possibly after multiple failures and recovery attempts). Unlike previous correctness definitions, the NRL condition implies that, following recovery, an implemented (higher-level) recoverable operation is able to complete its invocation of a base-object operation and obtain its response. We present algorithms for nesting-safe recoverable primitives, namely, recoverable versions of widely-used primitive shared-memory operations such as read, write, test-and-set and compare- and-swap, which can be used to implement higher-level recoverable objects. We then exemplify how these recoverable base objects can be used for constructing a recoverable counter object. Finally, we prove an impossibility result on wait-free implementations of recoverable test-and-set (TAS) objects from read, write and TAS operations, thus demonstrating that our model also facilitates rigorous analysis of the limitations of recoverable concurrent objects.
KW - Concurrency
KW - Lock-freedom
KW - Multi-core algorithms
KW - Nonblocking
KW - Shared memory
KW - Wait-freedom
UR - http://www.scopus.com/inward/record.url?scp=85052455623&partnerID=8YFLogxK
U2 - 10.1145/3212734.3212753
DO - 10.1145/3212734.3212753
M3 - Conference contribution
AN - SCOPUS:85052455623
SN - 9781450357951
T3 - Proceedings of the Annual ACM Symposium on Principles of Distributed Computing
SP - 7
EP - 16
BT - PODC 2018 - Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing
PB - Association for Computing Machinery
Y2 - 23 July 2018 through 27 July 2018
ER -