Identifier
etd-06292016-021029
Degree
Doctor of Philosophy (PhD)
Department
Computer Science
Document Type
Dissertation
Abstract
Shared memory multi-core systems bene_x000C_t from transactional memory implementations due to the inherent avoidance of deadlocks and progress guarantees. In this research, we examine how the system performance is a_x000B_ected by transaction fairness in scheduling and by the precision in consistency. We _x000C_rst explore the fairness aspect using a Lazy Snapshot (multi-version) Algorithm. The fairness of transactions scheduling aims to balance the load between read-only and update transactions. We implement a fairness mechanism based on machine learning techniques that improve fairness decisions according to the transaction execution history. Experimental analysis shows that the throughput of the Lazy Snapshot Algorithm is improved with machine learning support. We also explore the impacts on performance of consistency relaxation. In transactional memory, correctness is typically proven with opacity which is a precise consistency property that requires a legal serialization of an execution such that transactions do not overlap (atomicity) and read instructions always return the most recent value (legality). In real systems there are situations where system delays do not allow precise consistency, such as in large scale applications, due to network or other time delays. Thus, we introduce here the notion of approximate consistency in transactional memory. We de_x000C_ne K-opacity as a relaxed consistency property where transactions' read operations may return one of K most recent written values. In multi-version transactional memory, this allows to save a new object version once every K object updates, which has two bene_x000C_ts: (i) it reduces space requirements by a factor of K, and (ii) it reduces the number of aborts, since there is smaller chance for con icts. In fact, we apply the concept of K-opacity on regular read and write, count and queue objects, which are common objects used in typical concurrent programs. We provide formal correctness proofs and we also demonstrate the performance bene_x000C_ts of our approach with experimental analysis. We compare the performance of precise consistent execution (1-opaque) with di_x000B_erent consistency values of K using micro benchmarks. The results show that increased relaxation of opacity gives higher throughput and decreases the aborts rate signi_x000C_cantly.
Date
2016
Document Availability at the Time of Submission
Release the entire work immediately for access worldwide.
Recommended Citation
Assiri, Basem Ibrahim, "Fairness and Approximation in Multi-version Transactional Memory." (2016). LSU Doctoral Dissertations. 104.
https://repository.lsu.edu/gradschool_dissertations/104
Committee Chair
Busch, Konstantin
DOI
10.31390/gradschool_dissertations.104