Title
Staring into the abyss: an evaluation of concurrency control with one thousand cores
Abstract
Computer architectures are moving towards an era dominated by many-core machines with dozens or even hundreds of cores on a single chip. This unprecedented level of on-chip parallelism introduces a new dimension to scalability that current database management systems (DBMSs) were not designed for. In particular, as the number of cores increases, the problem of concurrency control becomes extremely challenging. With hundreds of threads running in parallel, the complexity of coordinating competing accesses to data will likely diminish the gains from increased core counts. To better understand just how unprepared current DBMSs are for future CPU architectures, we performed an evaluation of concurrency control for on-line transaction processing (OLTP) workloads on many-core chips. We implemented seven concurrency control algorithms on a main-memory DBMS and using computer simulations scaled our system to 1024 cores. Our analysis shows that all algorithms fail to scale to this magnitude but for different reasons. In each case, we identify fundamental bottlenecks that are independent of the particular database implementation and argue that even state-of-the-art DBMSs suffer from these limitations. We conclude that rather than pursuing incremental solutions, many-core chips may require a completely redesigned DBMS architecture that is built from ground up and is tightly coupled with the hardware.
Year
DOI
Venue
2014
10.14778/2735508.2735511
PVLDB
Field
DocType
Volume
Transaction processing,Data mining,Computer science,Staring,Distributed computing,Architecture,Concurrency control,Online transaction processing,Parallel computing,Chip,Thread (computing),Database,Scalability
Journal
8
Issue
ISSN
Citations 
3
2150-8097
10
PageRank 
References 
Authors
0.49
28
5
Name
Order
Citations
PageRank
Xiangyao Yu127016.17
George Bezerra2100.83
Andrew Pavlo31614122.03
Srinivas Devadas486061146.30
Michael Stonebraker5124634310.17