Paper Info
Title
Impact of Data Sharing on Co-Running Embedded Applications in Multi-core System
Abstract
This work studies utilization of shared caches by applications running concurrently on different cores of multicore systems. Knowledge about program contention due to shared resources is important for various design problems concerning multicore architectures. It is needed for power estimation, scheduling of parallel applications and design of shared memories. Moreover, deep understanding of programs behavior is especially needed for the development of accurate models that are able to predict misses caused by shared resources in multicore systems. We present a methodology that is able to examine the interaction of applications in shared caches. Our experiments show a positive impact of data sharing by minimizing misses in shared L2 caches over a wide range of L2 cache sizes for applications from the Media bench suite. Up to 25% lower misses in the last level cache can be observed for embedded applications, when data are allowed to be shared among programs running on different cores.
Year
DOI
Venue
2015
10.1109/PDP.2015.88
PDP
Keywords
Field
DocType
multicore processing,benchmark testing,computational modeling,multicore,embedded systems,data models,predictive models,cache memory,mathematical model,data handling
Computer architecture,Suite,Computer science,Cache,CPU cache,Scheduling (computing),Data sharing,Parallel computing,Embedded applications,Multi-core processor,Multicore systems,Distributed computing
Conference
ISSN
Citations 
PageRank 
1066-6192
0
0.34
References 
Authors
11
2
Name
Order
Citations
PageRank
Anna Korotaeva100.34
Wolfgang Nebel248476.22