Recoverable Data Structures

Wednesday, February 16, 2022
Speaker(s) : prof. Panagiota Fatourou

This talk will present generic approaches for deriving recoverable synchronization algorithms, as well as recoverable implementations of many widely-used concurrent data structures on top of them. Such implementations are appealing for emerging systems featuring byte-addressable non-volatile main memory (NVMM), whose persistence allows to efficiently resurrect failed processes after crashes. 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.
Our experimental analysis reveals the performance power of employing software combining for achieving recoverable synchronization and for designing highly-efficient fundamental recoverable data structures, such as stacks and queues. Another technique we will present addresses more complex data structures, such as linked-lists, and tree-like structures that implement sets. Our experimental analysis introduces a new way of analyzing the cost of persistence instructions, not by simply counting them but by separating them into categories based on the impact they have on the performance. The analysis reveals that understanding the actual persistence cost of an algorithm in machines with real NVMM, is more complicated than previously thought, and requires a thorough evaluation, since the impact of different persistence instructions on performance may greatly vary.

More details here …
marc.shapiro (at)