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CoDeR-MP SSF meeting, May 3, 2011, Uppsala Agenda

CoDeR-MP SSF meeting, May 3, 2011, Uppsala Agenda. 10.15-10.45 Overview (Coffee will be served) Introduction, Olof Lindgren CoDeR-MP: Goals, progress and vision, Wang Yi Discussion 10.45-11.00 Hard safety-critical real-time applications

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CoDeR-MP SSF meeting, May 3, 2011, Uppsala Agenda

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  1. CoDeR-MP SSF meeting, May 3, 2011, Uppsala Agenda • 10.15-10.45 Overview (Coffee will be served) • Introduction, Olof Lindgren • CoDeR-MP: Goals, progress and vision, Wang Yi • Discussion • 10.45-11.00 Hard safety-critical real-time applications • CoDeR-MP solved the 37-year open problem! Guan Nan • Coloring the cache to isolate multiple applications, Wang Yi • 11.00-11.10 Break • 11.10-11.35 Soft high-performance real-time applications • Performance profiling and modeling, David Eklöv & Erik Hagersten • The multi-core locking problem, Pan Xiaoyue & Bengt Jonsson • 11.35-12.00 Industrial applications: real-time signal processing • Real-time model-based estimation, Alexander Medvedev, UU • SAAB’s perspective on multi-core, Mats Ekman & Björn Holmberg, SAAB • 12.00 -13.00 Lunch & Discussion

  2. CoDeR-MPComputationally Demanding Real-Time Applications on Multicore Platforms • OUTLINE • Why CoDeR-MP • Project Plan • Structure • Goals • Progress • Main achievements • Demos • Vision

  3. Year 1999-2007 The free lunch is over & Multicores are coming !

  4. CPU CPU CPU CPU L1 L1 L1 L1 L1 L1 L1 L1 CPU CPU CPU CPU Typical Multicore Architecture L2 Cache Off-chip memory

  5. Theoretically with multicore, you may get: • Higher Performance • Increasing the cores -- unlimited computing power  ! • Lower Power Consumption • Increasing the cores, decreasing the clock frequency  Keep the “same performance” using ¼ of the energy This sounds great for embedded & real-time applications!

  6. CPU CPU CPU CPU L1 L1 L1 L1 L1 L1 L1 L1 CPU CPU CPU CPU Real-Time Applications on Multicores? Bandwidth L2 Cache Problems: -- Cache contention -- Bus interference -- Multiprocessor scheduling -- Spinlocks/Queuing -- Cheap/expensive Synchronization Shared Resources Off-chip memory

  7. CoDeR-MPaddressing the challenges: • Migrating legacy software to multicore • Sequential code  parallelization • Performance issues – memory problems • Synchronization/locking problem • Developing new real-time software on multicore • High-performance applications: “fast” – real-time applications • Predictable real-time applications with guarantees: “correct” and “deterministic” Driven by Industrial Applications

  8. Real-Time Tracking with parallel particle filter – SAAB

  9. Real-Time Control – ABB Robotics • IRC5 robot controller Precise moves Welding program A B C D Commands High-level instructions Requests Mixed Hard and Soft Real-Time Tasks 20% hard real-time tasks Main concerns: Isolation between hard & soft tasks: “fire walls” Real-time guarantee for the 20% “super” RT tasks Migration to multicore?

  10. Goals of CoDeR-MP New techniques for • High-performance Real-Time applications & • PredictableReal Time applications on multi-core processors Mixed applications on the same multi-core chip 20% Others 60% Soft RT 20% Hard RT

  11. Project Plan • Task 1 (Demonstrators) • Migration of IRC5 robot controller onto multicore platform (guidelines and tools for performance and real-time guarantees) • Multicore implementation of parallel alg. for ground target tracking • Task 2 (Application diagnostics for migration) • Methods and tools for modeling, adaptation, integration and evaluation of design alternatives • Task 3 (Application parallelization) • Parallel algorithms for control and signal processing • Task 4 (Resource allocation for real-time/”predictable”) • Multicore scheduling (processor cores and caches) • Task 5 (Resource allocation for performance/”fast”) • Resource modeling and management

  12. Consortium/Senior Members • SAAB • SAAB Systems, Mats Ekman • (SAAB Combitech, Björn Holmberg) • ABB • Corporate Research, Jan Höglund • ABB Robotics, Peter Ericsson/Roger Kulläng • Uppsala University • Automated Control, Alexander Medvedev • Computer Architectures, Erik Hagersten & David Black-Schaffer • Software Technology, Bengt Jonsson • Embedded Systems, Wang Yi, Project leader

  13. Current Ph.D. Students • David Eklöv • Guan Nan • Pan Xiaoyue • Andreas Sandberg • Andreas Sembrant • Olov Rosen • Jonatan Liden • Zhang Yi • David Black-Schaffer (now assistant professor) Previous Post Doc Fellow

  14. CoDeR-MP: Project Structure • Techniques/tools for real-time guarantees • Wang et al • Techniques/tools for performance guarantees • Erik, Bengt et al • Industrial Applications: real-time signal processing • Alexander and Mats

  15. Main achievements • Industrial applications • SAAB shows great interests in using the parallel signal processing algorithms developed within CoDeR-MP for real-time tracking • ABB robotics shows great interests of using the CoDeR-MP performance modeling/profiling tools • Academic research • 20 (peer-reviewed) papers on good/top conferences • 2 best paper awards: IEEE RTSS 2009 and HiPEAC 2011 • 5 best paper nominations (IEEE RTSS09, IEEE RTSS10, IEEE RTAS10, IEEE RTAS11 & HiPEAC11) • Solved a 37-year open problem for multiprocessor scheduling • Successful FP 7 collaboration, 4 proposals! • Wang, CERTAINTY (Mixed embedded applications on multicores), likely to be funded • Erik (passed the threshold, cliff-hanger) • Wang, Encore (passed the threshold) • Bengt (passed the threshold)

  16. Demonstrators (in progress) • Real-Time Tracking • Running on “recorded data” • Migration of legacy code • Prototype tools for performance analysis • Cache coloring on LINUX for real-time guarantee

  17. VISION

  18. Robot Contriller Hard 20% Real-Time Soft Real-Time Non Real-Time: House Keeping • We must allocate “resources”: cores, caches • We must isolate the different applications

  19. Application Hard real-time, Software real-time, Others ? Platform Hardware Resources: Cores, Caches, Memmory Bandwidth …

  20. Application Hard real-time, Software real-time, Others Hard 20% Real-Time Soft Real-Time Non Real-Time: House Keeping Resource Reservation Resource Virtualization Platform Hardware Resources: Cores, Caches, Memmory Bandwidth …

  21. Application Hard real-time, Software real-time, Others Hard 20% Real-Time Soft Real-Time Non Real-Time: House Keeping Application Mapping Server 1 … … Server N Resource Partition Platform Hardware Resources: Cores, Caches, Memmory Bandwidth …

  22. Application Hard real-time, Software real-time, Others Hard 20% Real-Time Soft Real-Time Non Real-Time: House Keeping Application Mapping CoDeR-MP tools Server 1 … … Server N Resource Partition CoDeR-MP tools Platform Hardware Resources: Cores, Caches, Memmory Bandwidth …

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