This paper presents a generic approach for deriving detectably recoverable implementations of many widely-used concurrent data structures. Such implementations are appealing for emerging systems featuring byte-addressable non-volatile main memory (NVMM), whose persistence allows to efficiently resurrect failed threads after crashes. Detectable recovery ensures that after a crash, every executed operation is able to recover and return a correct response, and that the state of the data structure is not corrupted.

The emergence of systems with non-volatile main memory (NVM) increases the interest in the design of recoverable concurrent objects that are robust to crash-failures, since their operations are able to recover from such failures by using state retained in NVM. Of particular interest are recoverable algorithms that, in addition to ensuring object consistency, also provide detectability, a correctness condition requiring that the recovery code can infer if the failed operation was linearized or not and, in the former case, obtain its response.

We present the tracking approach for deriving detectable implementations of many widely-used concurrent data structures for systems with non-volatile main memory (NVRAM). Detectable recovery ensures that in the crash-recovery model, every operation executed during a crash, resumes its execution and returns a correct response, and that the state of the data structure is not corrupted.

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.

Mutual exclusion is a fundamental distributed coordination problem. Shared-memory mutual exclusion research focuses on local-spin algorithms and uses the remote memory references (RMRs) metric. To ensure the correctness of concurrent algorithms in general, and mutual exclusion algorithms in particular, it is often required to prohibit certain re-orderings of memory instructions that may compromise correctness, by inserting memory fence (a.k.a. memory barrier) instructions. Memory fences incur non-negligible overhead and may significantly increase time complexity.