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MPWide: A communication library
for wide area message passing

Derek Groen
Centre for Computational Science
Overview







The networking landscape
Using wide area networks
MPWide
Example applications
Uses for multiscale modelling
Questions
The networking landscape


The networks connecting grid sites and
supercomputers are highly heterogeneous.
−
−
−

Configurations differ at end points.
Shared paths vs. Dedicated paths
Optical interconnects vs. Regular interconnects.

A

C
B
The networking landscape


Fundamental issue: Networks configurations
tend to be node-specific, not path-specific.
−

What do we do when a node has multiple paths?


(most nodes nowadays do)

A

C
B
Using wide area networks (WANs)


Solution 1: Apply a homogeneous configuration
for all paths.
−

Could work for nodes with similar path lengths.


−
−

Not common for WAN communication nodes.

Inefficient for the TCP protocol, where the optimal
config is dependent on the path length.
Requires admin privileges on all end-points.

A

A
A
Using WANs


Solution 2: Adopt a different protocol.
−
−
−
−

May accomodate heterogeneous configs.
New protocol, new list of potential issues.
Interplay between protocols on shared networks.
Time-consuming and politically heavyweight
process.

խ

ե
Ր
Using WANs


Solution 3: User-space tuning through software.
−

Limited space for tuning.


−
−

Some adjustments require admin rights.

Use TCP protocol and existing configurations.
No special privileges required.

X
A Y

Y B Z

X
C
Z
MPWide




MPWide is a communication library which
allows for user-space tuning of individual paths.
For each path it can:
−

Use 1 or multiple tcp streams.


−
−

Good performance obtained with up to 128 streams/path.

Configure different buffer and packet sizes.
Apply software-based packet pacing to reduce load.


Also improves performance on long networks
(Yoshino et al. 2008).
Example: cosmological N-body









One simulation, parallelized
across supercomputers.
Uses the SUSHI code, which
is a cross-site adaptation of
GreeM.
Models dark matter structure
formation over 13.4 billion years.
Algorithm: Tree + Particle-mesh.
Adaptive load-balancing
between sites. →
Example: cosmological N-body


Using 2 to 4 supercomputers simultaneously.
−








Up to 2048 cores total.

MPI within each site.
Custom MPWide
connections between sites.
MPWide Forwarder procs
bypass connectivity
restrictions.
2048 cores, 3 sites,
7% comm. overhead.
10 Gbps lightpath
Example: multiscale bloodflow
Example: multiscale bloodflow



pyNS (1D) coupled to HemeLB (3D).
400.000 time steps, 4000 velocity exchanges
−
−

with 1.2% comm. overhead (512+1 cores, 2298 s),
and 5% comm. overhead (2048+1 cores, 907 s.).
Uses for multiscale modelling


Can be used for performance critical cyclic
coupling over wide area networks.
−








High-performance, simple low-level interface.

Contains an mpw-cp file transfer client to
accelerate file-based couplings.
Supports C, C++, Python.
Trivial to install and intended for users without
administrative privileges.
Is being integrated into MUSCLE 2 to improve
its coupling performance.
Thank you!


MPWide website:
−



More on the multiscale bloodflow application:
−



Groen et al., Interface Focus 3(2), 2013.

More on the cosmological N-body application:
−



http://castle.strw.leidenuniv.nl/software/mpwide.html

Groen et al., INFOCOMP 2011, ArXiv:1109.5559.

Thanks go out to Steven Rieder, Simon
Portegies Zwart, Tomoaki Ishiyama, Keigo
Nitadori, Joris Borgdorff, Rupert Nash and the
MAPPER consortium as a whole.

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MPWide: A light-weight communication library for wide area message passing and code coupling

  • 1. MPWide: A communication library for wide area message passing Derek Groen Centre for Computational Science
  • 2. Overview       The networking landscape Using wide area networks MPWide Example applications Uses for multiscale modelling Questions
  • 3. The networking landscape  The networks connecting grid sites and supercomputers are highly heterogeneous. − − − Configurations differ at end points. Shared paths vs. Dedicated paths Optical interconnects vs. Regular interconnects. A C B
  • 4. The networking landscape  Fundamental issue: Networks configurations tend to be node-specific, not path-specific. − What do we do when a node has multiple paths?  (most nodes nowadays do) A C B
  • 5. Using wide area networks (WANs)  Solution 1: Apply a homogeneous configuration for all paths. − Could work for nodes with similar path lengths.  − − Not common for WAN communication nodes. Inefficient for the TCP protocol, where the optimal config is dependent on the path length. Requires admin privileges on all end-points. A A A
  • 6. Using WANs  Solution 2: Adopt a different protocol. − − − − May accomodate heterogeneous configs. New protocol, new list of potential issues. Interplay between protocols on shared networks. Time-consuming and politically heavyweight process. խ ե Ր
  • 7. Using WANs  Solution 3: User-space tuning through software. − Limited space for tuning.  − − Some adjustments require admin rights. Use TCP protocol and existing configurations. No special privileges required. X A Y Y B Z X C Z
  • 8. MPWide   MPWide is a communication library which allows for user-space tuning of individual paths. For each path it can: − Use 1 or multiple tcp streams.  − − Good performance obtained with up to 128 streams/path. Configure different buffer and packet sizes. Apply software-based packet pacing to reduce load.  Also improves performance on long networks (Yoshino et al. 2008).
  • 9. Example: cosmological N-body      One simulation, parallelized across supercomputers. Uses the SUSHI code, which is a cross-site adaptation of GreeM. Models dark matter structure formation over 13.4 billion years. Algorithm: Tree + Particle-mesh. Adaptive load-balancing between sites. →
  • 10. Example: cosmological N-body  Using 2 to 4 supercomputers simultaneously. −     Up to 2048 cores total. MPI within each site. Custom MPWide connections between sites. MPWide Forwarder procs bypass connectivity restrictions. 2048 cores, 3 sites, 7% comm. overhead. 10 Gbps lightpath
  • 12. Example: multiscale bloodflow   pyNS (1D) coupled to HemeLB (3D). 400.000 time steps, 4000 velocity exchanges − − with 1.2% comm. overhead (512+1 cores, 2298 s), and 5% comm. overhead (2048+1 cores, 907 s.).
  • 13. Uses for multiscale modelling  Can be used for performance critical cyclic coupling over wide area networks. −     High-performance, simple low-level interface. Contains an mpw-cp file transfer client to accelerate file-based couplings. Supports C, C++, Python. Trivial to install and intended for users without administrative privileges. Is being integrated into MUSCLE 2 to improve its coupling performance.
  • 14. Thank you!  MPWide website: −  More on the multiscale bloodflow application: −  Groen et al., Interface Focus 3(2), 2013. More on the cosmological N-body application: −  http://castle.strw.leidenuniv.nl/software/mpwide.html Groen et al., INFOCOMP 2011, ArXiv:1109.5559. Thanks go out to Steven Rieder, Simon Portegies Zwart, Tomoaki Ishiyama, Keigo Nitadori, Joris Borgdorff, Rupert Nash and the MAPPER consortium as a whole.