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A Review of Lightweight Thread Approaches for High Performance
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A Review of Lightweight Thread Approaches for High Performance ComputingA Review of Lightweight Thread Approaches for High Performance Computing
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A Review of Lightweight Thread Approaches
for High Performance Computing
Adrián Castelló
Rafael Mayo
Enrique S. Quintana-Ortí
Universitat Jaume I de Castelló
(Spain)
Antonio J. Peña
Barcelona Supercomputing
Center (Spain)
Sangmin Seo
Pavan Balaji
Argonne National Lab
(USA)
IEEE Cluster 2016. 13
rd
– 15
th
September. Taipei (Taiwan)
Motivation
A. Castelló
IEEE Cluster 2016
1
• Exascale systems will offer massive concurrent hardware
• On-node parallelism is inevitable
Cores per socket distribution on the Top500 list
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
0%
20%
40%
60%
80%
100%
Year
Percentage (%)
1 2 4 6 8 9-14 16 18-260
Current solution
A. Castelló
IEEE Cluster 2016
2
• Pthreads is the standard to exploit the current on-node parallelism
• Using pthreads library
• Using high-level programing models
• Pros:
• Works well for hardware characteristics
• Cons:
• Falls from the point of view of software requirements
• Context switch and synchronizations are expensive mechanisms
OS
thread
Lightweight Thread Libraries
A. Castelló 3
IEEE Cluster 2016
OS
thread
U
U
U
• Lightweight thread with low context-switch overhead
• To better overlap computation and communication/IO
• To exploit fine-grained task parallelism
U
User-level thread
Lightweight Thread Libraries
A. Castelló 4
IEEE Cluster 2016
Specific OS
Windows Fibers
Solaris Threads
Specific Hardware
Tiny-Threads
High-level
programming model
ConverseThreads
Nanos++
Lightweight Thread
abstraction
Cilk Go Intel TBB
Stackless threads
MassiveThreads Argobots
Qthreads
General purpose
MassiveThreads Argobots
Qthreads
Stackless Python
Protothreads
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