Scalable Peer-to-peer Network for Biological Simulations

Shun-Yun Hu

2005/05/26

Outline

Introduction Voronoi-based Overlay Network (VON) Protein Folding Problem Conclusion

A Look at Simulations

Simulations are important tools in scientific research

Larger scale and higher resolution (more accurate and detailed simulations) are constantly sought

However, computational resource can be limited

An Untapped Potential

300 Million PCs on the Internet (2000 est.)

Up to 80% to 90% of CPU is wasted

Large supply of computing resource, growing rapidly

An Example: SETI@Home

Search for Extraterrestrial Intelligence (SETI) UC Berkeley Project launched in May 1999

PC User downloads a screen saver Calculations are done using idle CPU time

2005/03 statistics (in 6 years) 5.3 M world-wide participants 2.2 M years of single-processor CPU 54 teraflop machine (current top 3: 70.72, 51.87, 35.86)

Simulation: Folding@Home

Stanford Project launched in Sept. 2000 Seeks to determine protein’s 3D structure

Screensaver that downloads “work units” 2002 Statistics:

30,000 volunteers 1 M days of single-processor CPU

Published 23 papers in: Science, Nature, Nature Structural Biology, PNAS, JMB, etc.

The Grand Question

Can we build the ultimate simulator for large-scale simulation utilizing millions of computers world-wide?

Potential applications: Nuclear reaction Star clusters Atomic-scale modeling in material science Weather, earthquakes Biology (protein, ecosystem, brain, ...)

Current Limitations

Current methodology: Client-server model (master & slaves) clients request “work unit” to process Communication is minimized Clients do not communicate

Issues: Only suitable for “embarrassingly parallel” simulations Sophisticated server-side algorithm and management required

An alternative: peer-to-peer (P2P) computing

What is Peer-to-Peer (P2P)?

[Stoica et al. 2003] Distributed systems without any centralized control

or hierarchical organization Runs software with equivalent functionality

Examples File-sharing: Napster, Gnutella, eDonkey VoIP: Skype DHT: Chord, CAN, Pastry

Peer-to-Peer Overlay

A P2P overlay network source: [Keller & Simon 2003]

Promise & Challenge of P2P

Promises Growing resource, decentralized

Scalable Commodity hardware Affordable

Challenges Topology maintenance dynamic join/leave Efficient content retrieval no global knowledge

A Simulation Scenario

How can we utilize P2P for simulation-purpose?Answer: depends on what you want to simulate

We observe that many simulations… are spatially-oriented (i.e. based on coordinate systems) run in discrete time-steps require synchronization at each time-step exhibit localized interaction (i.e. short-range interaction)

example: molecular dynamics (MD) simulation

Scenario Defined for P2P

Many simulated entities (nodes) on a 2D plane ( > 1,000) Positions (coordinates) may change at each time-step How to synchronize positions with those in Area of Interest

(AOI)?

Area of Interest

P2P Design Goals

Observation: the contents are information from AOI neighbors P2P content discovery is a neighbor discovery problem

Solve the Neighbor Discovery Problem in a fully-distributed, message-efficient manner.

Specific goals: Scalable Limit & minimize message traffics Fast Direct connection with AOI neighbors

Outline

Introduction Voronoi-based Overlay Network (VON) Protein Folding Problem Conclusion

Voronoi Diagram

2D Plane partitioned into regions by sites, each region contains all the points closest to its site

Can be used to find k-nearest neighbor easily

Neighbors

Site

Region

Design Concepts

Identify enclosing and boundary neighbors Each node constructs a Voronoi of all AOI neighbors Enclosing neighbors are minimally maintained Mutual collaboration in neighbor discovery

Circle Area of Interest (AOI)

White self

Yellow enclosing neighbor (E.N.)

L. Blue boundary neighbor (B.N.)

Pink E.N. & B.N.

Green AOI neighbor

D. Blue unknown neighbor

Use Voronoi to solve the neighbor discovery problem

Procedure (JOIN)

1) Joining node sends coordinates to any existing node

Join request is forwarded to acceptor

2) Acceptor sends back its own neighbor list

joining node connects with other nodes on the list

Acceptor’s region

Joining node

Procedure (MOVE)

1) Positions sent to all neighbors, mark messages to B.N.

B.N. checks for overlaps between mover’s AOI and its E.N.

2) Connect to new nodes upon notification by B.N.

Disconnect any non-overlapped neighbor

Boundary neighbors

New neighbors

Non-overlapped neighbors

Outline

Introduction Voronoi-based Overlay Network (VON) Protein Folding Problem Conclusion

Protein Folding Problem

Find native state (lowest free energy) 3D structure given a 1D sequence of amino acids

Timescale limitation of classical MD methods Secondary structure folds in 0.1 ~ 10 s Small protein folds in tens of s Current record: 1s (villin headpiece) full-atomic simulation of 1 ns takes one CPU day 1,000 ~ 10,000 gap (it might take decades)

Folding@Home Parallelization Dynamics of complex

system involves crossing of free energy barriers

Most time is spent in free energy minimum “waiting”

Possible to simulate using trajectories much shorter than folding time

“ensemble dynamics” (same coords, different velocities)

Outline

Introduction Voronoi-based Overlay Network (VON) Protein Folding Problem Conclusion

Summary

Idle CPU and networks are untapped potential resources for large-scale simulation

Current approaches do not support simulations that require frequent synchronization / updates

A promising solution: Voronoi-based P2P Overlay Leverage knowledge of each peer to maintain topology Properties: scalable, efficient, fully-distributed Enable simulations with frequent localized synchronization

Acknowledgements Dr. Jui-Fa Chen (陳瑞發老師 ) Dr. Wei-Chuan Lin (林偉川老師 ) Members of the Alpha Lab, TKU CS

Guan-Ming Liao (廖冠名 ) Dr. Chin-Kun Hu (胡進錕老師 ) LSCP, Institute of Physics, Academia Sinica

Joaquin Keller (France Telecomm R&D, Solipsis) Bart Whitebook(butterfly.net) Jon Watte (there.com)

Dr. Wen-Bing Horng (洪文斌老師 ) Dr. Jiung-yao Huang (黃俊堯老師 )