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Joint National Integration Center

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Presentation on theme: "Joint National Integration Center"— Presentation transcript:

1 Joint National Integration Center
SPEEDES Dr. Ron Van Iwaarden Metron, Inc. Joint National Integration Center (719)

2 Overview History of JNIC SPEEDES Other users Lessons learned
Future directions JNIC = Joint National Integration Center SPEEDES = Synchronous Parallel Engine for Emulation and Discrete Event Simulation

3 Pre-History of SPEEDES
Originally developed at NASA as outgrowth of Time Warp Operating System Included several advancements Breathing Time Warp (BTW) algorithm Reasonable optimistic algorithm which limits memory use and runaway nodes Events as Objects Gives great flexibility for model design

4 Pre-History of SPEEDES (cont)
Other advancements: Novel event queue design Portable C++ Extensible communications system GOTS Open source

5 Pre-History of SPEEDES (cont)
Jeff Steinman brought SPEEDES to Metron in 1996 Initial development was funded by DMSO Intended as a parallel Naval Simulation System (NSS) Turned into general improvements not specifically related to NSS DMSO = Defense Modeling and Simulation Office

6 MDWAR = Missile Defense Wargaming and Analysis Resource
SPEEDES at MDWAR Chosen as framework for MDWAR in late 1996 Began with version 0.2 from NASA/Metron Extremely primitive, buggy, poorly documented, difficult to use Version 0.3 added new communications infrastructure Version 0.4 added event handlers and Process Model Version 0.5 added the Object Proxy State Manager and several rollbackable container classes Version 0.6 included initial port to Windows NT and initial implementation of Data Distribution Management MDWAR = Missile Defense Wargaming and Analysis Resource

7 SPEEDES at MDWAR (cont)
Early versions of SPEEDES Version 0.7 reorganized the distribution, added a new parser, and implemented a sort of namespace using Sp. Also included initial persistence framework Version 0.8 added full DDM functionality and had the seeds for the unified API in current use. Version 0.9 had the Unified API and removed a great deal of obsolete code

8 SPEEDES at MDWAR (cont)
Modern versions of SPEEDES Version 1.0 Added the SPEEDES User’s Guide Added the API Reference Manual The Unified API was finished. Much of the obsolete code was removed Version 2.0 Added object proxy attribute subscription Added automatic lazy re-evaluation General code optimization (size and speed)

9 SPEEDES at MDWAR (cont)
Modern versions of SPEEDES Version 2.1 Ported to Microsoft Visual Studio Removed novel event queue design Resulted in net performance improvement General code optimization Reduced memory requirements Reduced executable size Fixed numerous Data Declaration Management bugs Added optimized conservative algorithm

10 SPEEDES at MDWAR (cont)
Modern versions of SPEEDES Version 2.2 Due mid July Not being produced at request of JNIC Adding initial implementation of shared memory host router Standard Template Library (STL) containers RB_map, RB_list, RB_vector, RB_multimap All are significantly (4-10x) faster than current rollbackable containers Function with non rollbackable STL algorithms library General performance improvements Minor bug fixes

11 Significant users JNIC Air Force Research Lab (Rome Labs) C2BMC ABL
MDWAR IMDSE Conservative only Windows NT SPEEDES just works and lets them model Air Force Research Lab (Rome Labs) Rome Labs funded iterator improvement, incorporated in Version 2 Distributed Information Enterprise Modeling and Simulation (DIEMS) Phase II SBIR: Parallel course of action evaluation Synthetic Force Structure Simulation (SFSS) C2BMC ABL NASA

12 Lessons learned SPEEDES has been extraordinarily resilient
Almost all performance problems have been due to improper modeling Framework bugs are now rare Significantly impacted development in the early (< v 0.8) years Proxy mechanism is solid but tightly couples models Use of proxy updates has decreased significantly Proxies use often indicates incorrect modeling Not communicating through message sets Unnecessary or excessive notifications Attribute subscription carries a small penalty Often used to simply unsubscribe totally to proxy updates

13 Lessons learned (cont)
Performance tuning requires analysis tools Real time performance does not come for free Built up suite of analysis tools SPEEDES instrumentation has been extensive and varied MDWAR has many tools to analyze the instrumentation files Rules of thumb learned about modeling New APIs added to improve parallelism SPEEDES overhead is minimal (usually 10s of micro-seconds/event) Recent tests using MDWAR 5.0 (SPEEDES 2.1) on 1 node (optimistic) shows a ~15% framework overhead. BTW is within 20% of sequential on SPEEDES 2.1, should be 10-15% with 2.2 I/O is a killer. Data collection has a minor impact Biggest problem is making sure we collect enough

14 Future Directions: Clustering
Clustering can lead to high performance federations Retains ability for easy debugging modes Can link up through shared memory or TCP/IP Design allows for MDWAR Standard Gateway (MSG) connections Elements could hook together in variety of fashions Optimistic: Full optimistic time management with rollbacks Includes the option of connecting through shared memory on the same machine or TCP/IP for those that are not on the same machine. Conservative: Linked through MSGs Playback: A element could be replaced by an MSG Playback for standalone testing/debugging Any combination of the above

15 Basic Clustering Design
ABL MDWAR Ghost Elements write their own simulations All interactions/data to other elements go through ghosts High Fidelity Threat MDWAR Ghost MDWAR ABL Ghost Hi-Fi Threat Ghost C2BMC MDWAR Ghost C2BMC Ghost

16 Basic Clustering Design (cont)
ABL MDWAR Ghost Testing and early integration can be done with MDWAR Standard Gateway (MSG) All simulations link up conservatively High Fidelity Threat MDWAR Ghost MSG MSG MDWAR ABL Ghost Hi-Fi Threat Ghost C2BMC MDWAR Ghost MSG C2BMC Ghost

17 Basic Clustering Design (cont)
ABL MDWAR Ghost Later exercises could use mix of MSG and high performance clustering Conservative MSG Cluster 2 Massive HPC High Fidelity Threat MDWAR Ghost Cluster 1 MDWAR ABL Ghost Hi-Fi Threat Ghost Optimistic Cluster 3 C2BMC MDWAR Ghost C2BMC Ghost

18 Basic Clustering Design (cont)
ABL MDWAR Ghost Cluster 4 Other exercises could run as one large optimistic cluster using a mix of shared memory and TCP/IP SPEEDES Server All optimistic High Fidelity Threat MDWAR Ghost Cluster 2 Massive HPC Cluster 1 MDWAR ABL Ghost Hi-Fi Threat Ghost C2BMC MDWAR Ghost Cluster 3 C2BMC Ghost

19 Other Future Developments
Continued changes for usability Continued reduction in memory and CPU footprint Main focus is and will be on stability, and reliability Performance has already been proven. AFRL funded parallel course of action simulation (due 2006)


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