When Don

1
When Dont I Use MPI?

• Jonathan Berry
• Scalable Algorithms Department
• Sandia National Laboratories
• June 3, 2008

2
Informatics Datasets Are Different

• Informatics The analysis of datasets arising
  from information sources such as the WWW (not
  physical simulation)
• Motivating Applications
• Homeland security
• Computer security (DOE emphasis)
• Biological networks, etc.

From UCSD 08

• One of the interesting ramifications of the fact
  that the PageRank calculation converges rapidly
  is that the web is an expander-like graph
• Page, Brin, Motwani,Winograd 1999

Broder, et al. 00
Primary HPC Implication Any partitioning is bad
3
Informatics Usage Models Can Be Quite Different
4
Multithreaded Architectures Can Boost Performance

• PageRank performs a sequence of matrix-vector
  multiplications
• NICE data are R-MAT graphs with maximum
  degree 1000
• NASTY data are R-MAT graphs with maximum degree
  200k
• The MTA-2 runs are nearly data agnostic and have
  ideal speedup through 20p
• The end of MTA-2 scaling indicates that
  algorithmic work is needed (weve seen and
  overcome behavior like this before)

33M vertices, 268M directed edges
PageRank time
Number of Processors
K. Devine, S. Plimpton, Berry
5
MTA/XMT Programming Use the Compiler

• Here, we sum a quantity over the neighbors of one
  vertex
• The removal of the reduction of sum prevents a
  hot spot
• This output is from canal, an MTA/XMT compiler
  analysis tool

6
We Are Developing The MultiThreaded Graph Library

• Enables multithreaded graph algorithms (XMT, SMP,
  Niagara)
• Builds upon community standard (Boost Graph
  Library)
• Abstracts data structures and other application
  specifics
• Hide some shared memory issues
• Preserves good multithreaded performance

S-T connectivity scaling (MTA-2)
SSSP scaling (MTA-2)
Solve time (sec)
Solve time (sec)
MTGL
C
MTGL
C
MTA-2 Processors
MTA-2 Processors
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Current MTGL Algorithms

• Connected components (psearch, visit_edges,
  visit_adj)
• Strongly-connected components (psearch)
• Maximal independent set (visit_edges)
• Typed subgraph isomorphism (psearch, visit_edges)
• S-t connectivity (bfs)
• Single-source shortest paths (psearch)
• Betweenness centrality (bfs-like)
• Community detection (all kernels)
• Connection subgraphs (bfs, sparse matrix,
  mt-quicksort)
• Find triangles (psearch)
• Find assortativity (psearch)
• Find modularity (psearch)
• PageRank (matvec)
• Network Simplex for MaxFlow
• Under development
• Motif detection
• more

Berkeley Open-Source Licence pending
8
Acknowledgements

• MultiThreading Background
• Simon Kahan (formerly Cray)
• Petr Konecny (Google (formerly Cray))
• MultiThreading/Distributed Memory Comparisons
• Karen Devine (Sandia)
• Steve Plimpton (Sandia)
• MTGL Algorithm Design and Development
• Vitus Leung (Sandia)
• Kamesh Madduri (Georgia Tech.)
• William McLendon (Sandia)
• Cynthia Phillips (Sandia)
• Generic Programming Background
• Andrew Lumsdaine (Indiana U.)
• Doug Gregor (Indiana U.)