DocumentCode :
2484969
Title :
Early experiences on accelerating Dijkstra´s algorithm using transactional memory
Author :
Anastopoulos, Nikos ; Nikas, Konstantinos ; Goumas, Georgios ; Koziris, Nectarios
Author_Institution :
Comput. Syst. Lab., Nat. Tech. Univ. of Athens, Athens, Greece
fYear :
2009
fDate :
23-29 May 2009
Firstpage :
1
Lastpage :
8
Abstract :
In this paper we use Dijkstra´s algorithm as a challenging, hard to parallelize paradigm to test the efficacy of several parallelization techniques in a multicore architecture. We consider the application of transactional memory (TM) as a means of concurrent accesses to shared data and compare its performance with straightforward parallel versions of the algorithm based on traditional synchronization primitives. To increase the granularity of parallelism and avoid excessive synchronization, we combine TM with helper threading (HT). Our simulation results demonstrate that the straightforward parallelization of Dijkstra´s algorithm with traditional locks and barriers has, as expected, disappointing performance. On the other hand, TM by itself is able to provide some performance improvement in several cases, while the version based on TM and HT exhibits a significant performance improvement that can reach up to a speedup of 1.46.
Keywords :
graph theory; multi-threading; parallel processing; shared memory systems; transaction processing; Dijkstra algorithm; helper threading; multicore architecture; parallelization technique; shared data; transactional memory; Acceleration; Computer architecture; Concurrent computing; Laboratories; Life estimation; Multicore processing; Parallel processing; System testing; Systems engineering and theory; Yarn;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on
Conference_Location :
Rome
ISSN :
1530-2075
Print_ISBN :
978-1-4244-3751-1
Electronic_ISBN :
1530-2075
Type :
conf
DOI :
10.1109/IPDPS.2009.5161103
Filename :
5161103
Link To Document :
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