Performance Analysis and Modelling of Concurrent Multi-access Data Structures
Paper i proceeding, 2022

The major impediment to scaling concurrent data structures is memory contention when accessing shared data structure access-points, leading to thread serialisation, hindering parallelism. Aiming to address this challenge, significant amount of work in the literature has proposed multi-access techniques that improve concurrent data structure parallelism. However, there is little work on analysing and modelling the execution behaviour of concurrent multi-access data structures especially in a shared memory setting. In this paper, we analyse and model the general execution behaviour of concurrent multi-access data structures in the shared memory setting. We study and analyse the behaviour of the two popular random access patterns: shared (Remote) and exclusive (Local) access, and the behaviour of the two most commonly used atomic primitives for designing lock-free data structures: Compare and Swap, and, Fetch and Add. We model the concurrent multi-accesses by splitting the thread execution procedure into five logical sessions: i) side-work, ii) access-point search iii) access-point acquisition, iv) access-point data acquisition and v) access-point data operation. We model the acquisition of an access-point, as a system of closed queuing networks with parallel servers, and data acquisition in terms of where the data is located within the memory system. We evaluate our model on a set of concurrent data structure designs including a counter, a stack and a FIFO queue. The evaluation is carried out on two state of the art multi-core processors: Intel Xeon Phi CPU 7290 with 72 physical cores and Intel Xeon E5-2695 with 14 physical cores. Our model is able to predict the throughput performance of the given concurrent data structures with 80% to 100% accuracy on both architectures.

performance modelling

data structures

concurrency

parallel programming

queuing theorem

multi-access

lock-free

locality

parallelism

multi-core

semantic relaxation

cache

Författare

Adones Rukundo

Chalmers, Data- och informationsteknik, Nätverk och system

Aras Atalar

Chalmers, Data- och informationsteknik, Nätverk och system

Philippas Tsigas

Nätverk och System

Annual ACM Symposium on Parallelism in Algorithms and Architectures

Vol. SPA 22 333-344
9781450391467 (ISBN)

34th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2022
Philadelphia, USA,

Ämneskategorier

Datorteknik

Datavetenskap (datalogi)

Datorsystem

DOI

10.1145/3490148.3538578

Mer information

Senast uppdaterat

2024-03-27