Uwe Brinkschulte, Jürgen Becker University of Karlsruhe, Germany Theo Ungerer

1. CARUSO – an Approach Towards a Network of Low Power Autonomic Systems on Chips for Embedded Real-time Applications Uwe Brinkschulte, Jürgen Becker University of Karlsruhe, Germany Theo Ungerer University of Augsburg, Germany WPDRTS 04, Santa Fe, April 2004

2. Outline of the Presentation • Motivation • CARUSO Principle Goals • State of the Art • Research Objectives • CARUSO System Architecture • CARUSO Roadmap • Conclusions 2

3. 1. Motivation • Systems on Chip (SoC): • state of the art to build embedded computing systems with limitations in space and power consumption In contrast to microcontroller solutions, the entire system is integrated on a single chip

4. 1. Motivation • SoC can be used to build complex distributed embedded systems, e.g. • Distributed Robot Control • Robot Swarms • Complex Image Processing • ... • Designed in conventional style, these systems require a lot of effort for configuration, optimization, maintenance, ...

5. 2. CARUSO Principle Goals • CARUSO • Connective Autonomic Real-time Ultra-Low-Power System on • Chip • is a new SoC project • is work-in-progress • is a “joint venture” of several research groups/topics • aims to simplify the development and operation of complex embedded systems. • integrates hardware and software for high performance embedded computing with respect to other requirements:

6. 2. CARUSO Principle Goals • Autonomic Computingself-Organization, self-Configuration, self-Optimization,self-Protection, self-Healing=> robust, flexible, adaptive embedded systems minimum human interaction • Connectivityto form dynamic ad-hoc networks=> cooperation of multiple small computing components self-healing, self-optimization • Real-timesoft-, firm- and hard real-time => is a key feature for many embedded applications

7. 2. CARUSO Principle Goals • Ultra Low Poweroptimization of overall and single node power consumption=> increase battery life time, adapt to a changing environment (e.g. the distribution of available solar energy in a distributed network is location dependant and might change) • Cost and Spacereduction of development and operational costs, reduction of required space=> fit the upcoming ubiquitous applications • Performanceuse the latest processor techniques (multithreading, reconfigurable hardware, power-aware architectures)=> get a good performance / power consumption trade-off

8. 2. CARUSO Principle Goals Basic idea: do not treat each requirement isolated, but try to explore (and exploit) the relationship and interactions between them Example: Optimizing the overall energy consumption of the distributed system including hardware, software and middleware => increase of the optimization space (compared to optimizing a single node) additional global knowledge about task distribution, real- time constraints and execution history can be used

9. 2. CARUSO Principle Goals • Main project focus: • to realize a hardware and software architecture for CARUSO • Covered research topics: • multithreaded processor architectures • reconfigurable SoC • energy efficient hardware and software design • helper threads • real-time systems and middleware • autonomic computing

10. 2. CARUSO Principle Goals • A sketch of our solutions (more details later) • a multithreaded processor core • real-time thread scheduling in hardware • a reconfigurable unit with reconfigurable multi-grain data paths • helper threads for local system monitoring and autonomic management • middleware for global service distribution, system monitoring and autonomic management • energy management based on real-time scheduling, service distribution and the local and global system monitoring • a demo application: an optical tracking system

11. 3. State of the Art • Multithreaded Processor Architectures • support the execution of multithreaded programs by special hardware • multiple register sets, multiple program counters, special pipeline design (thread tag) • classes of hardware multithreading • cycle-by-cycle interleaving • block interleaving • simultaneous multithreading • main purpose: latency hiding • newly introduced to several high-end processors (e.g. Pentium 4), signal processors and microcontrollers (e.g. TriCore 2)

12. 3. State of the Art • Multithreaded Processor Architectures • the Komodo project explored hardware multithreading for real-time applications • multithreaded Java microcontroller, 6 threads, block interleaving, 0-cycle context switch • real-time scheduling in hardware (FPP, EDF, LLF, GP) • GP: Guaranteed Percentage Scheduling, assigns each thread a guaranteed percentage of the processor power in an interval of 100 clock cycles • offers a strict timing isolation of the threads

13. 3. State of the Art • still unexplored: combining a multithreaded processor core with reconfigurable hardware on a SoC Multithreaded Processor Architectures GP Scheduling

14. 3. State of the Art • Reconfigurable SoC • contains a processor core and a reconfigurable part • the reconfigurable part increases the performance and adapts the SoC to a specific task

15. 3. State of the Art • Reconfigurable SoC • classes of reconfiguration • static (once) • dynamic (during run-time) • fine grain (gates) • coarse grain (function blocks) • multi grain (data paths between function blocks) • example: HoneyComb, multi grain dynamic reconfiguration on a SoC

16. 3. State of the Art • to be explored: the relationship between dynamic reconfiguration, a multithreaded processor core, autonomic computing and energy consumption Reconfigurable SoC HoneyComb Architecture start node routing node occupied paths adaptivly routed connection of distance i

17. 3. State of the Art • Energy Efficient Design • electrical level • frequency and voltage scaling • pipeline gating • microarchitectural level • reducing external bus transfers • dynamic power management • architectural level • increasing the code density • static power management

18. 3. State of the Art • Energy Efficient Design • for multithreaded processors • not much research done yet • main approach: avoid energy consuming speculation misses • for real-time applications • exploit the time constraints to save energy • many approaches exploit the deadlines in EDF • in the Komodo project: exploit the • worst-case/real-case gap in EDF • requested percentages in GP

19. 3. State of the Art • to be explored: benefits by combining known techniques with new approaches triggered by hardware reconfiguration, hardware multithreading and middleware Energy Efficient Design Energy saving in GP

20. 3. State of the Art • Helper Threads • threads which are separated from the normal control flow • support system management on a multithreaded processor core: • branch prediction • trap handling • cache preloading • real-time garbage collection • real-time debugging, … • to be explored: are helper threads a suitable way to handle self-management and self-organization in autonomic computing?

21. 3. State of the Art • Real-time Middleware • middleware for distributed real-time and embedded systems is state of the art (RT-CORBA, MinimumCORBA, OSA+, …) • new challenges: • reconfigurable SoC • a component might be realized in software or hardware • middleware has to manage, reconfigure or migrate such components in real-time

22. 3. State of the Art • Real-time Middleware • new challenges (cont.): • autonomic computing • middleware will be a key component • responsible for self-x in a distributed system • energy saving • find an energy-optimal distribution for the current situation • reduce the resource needs

23. 3. State of the Art • Autonomic Computing • introduced by IBM to simplify the management of IT systems • computing systems should behave like organic entities • self-x properties (self-organizing, self-configuring, self-healing, self-protecting, self-optimizing, …) • looks like a promising idea to support tomorrows embedded and distributed systems (complexity, dependability, …) • applying this to SoC needs further exploration

24. 4. Research Objectives • Main CARUSO research focus: • exploit the synergy between the different requirements and attributes • Basic research questions:

25. 4. Research Objectives • Autonomic Computing • Which interrelationships exist between self-optimization, self-protecting, self-healing and self-reconfiguration? • How can this be supported by constructing dynamic networks of SoCs? • What is the influence of the Autonomic Computing principles on the real-time properties of the system? • What are the advantages of the dynamic hardware reconfiguration feature available in the SoC for Autonomic Computing? • What is the influence of the multithreaded processor core?

26. 4. Research Objectives • Energy Consumption • Does the overall optimization of the distributed system consisting of hardware, software, middleware and configware lead to better results than the optimization of the single components? • Can known time constraints in distributed systems be used as additional information source for resource usage and an energy-optimal distribution? • Is the possibility of software- and hardware-reconfiguration usable to reduce the energy consumption? • And again, what is the influence of the multithreaded processor core?

27. 4. Research Objectives • Connectivity • What are the necessary features of the middleware in such a system? • How can middleware support energy saving and Autonomic Computing? • How the middleware is affected by the dynamic hardware reconfiguration feature of the processing nodes? • What kind of communication links are necessary for an optimal system performance?

28. 4. Research Objectives • Real-time • What is the impact of hard-real-time requirement on the architecture of the reconfigurable SoC and its multithreaded processor core? • How the real-time behavior is affected by dynamic hardware reconfiguration, Autonomic Computing and energy saving? • Can the real-time constraints deliver any additional information to support the requirements mentioned above? • How real-time scheduling is influenced? • A lot of questions to be answered!

29. 5. CARUSO System Architecture Example Applications: Optical Tracking System, Robot Swarms Global Autonomic Manager Global Resource Manager Authentification Global Monitoring API Real-time Middleware Core Local Autonomic Manager Local Resource Manager Local Monitoring Communication Security Manager HW Power-Management Reconfigurable Peripherals Reconfigurable Coprocessor Multithreaded Processor Core CARUSO Node CARUSO Node CARUSO Node

30. 5. CARUSO System Architecture • Autonomic Principles (self-X): • closed control loop: • Monitoring Autonomic Mgmt Resource Mgmt • local level: autonomic management on chip • global level: distributed autonomic management • monitoring affects the chip, the system software, the middleware and the application

31. 5. CARUSO System Architecture CARUSO Chip: Dynamic Adaptive Datapaths Multithreaded Processor Core (SMT) Memory Real-time Thread Scheduler EventUnit IntelligentDatapathCoupling ExecutionUnits ExtensionHardwareController VirtualMemoryManager EventCoupling Standard Input/Output Peripheral On-DemandHardware

32. 5. CARUSO System Architecture • The integration of a multithreaded processor core in a • reconfigurable SoC is a key idea of this project: • It enables the main project goals: • autonomic computing supported by helper threads => local and global autonomic manager => Self-X properties • energy consumption monitored by helper threads => local and global power management, load balancing, deactivation

33. 5. CARUSO System Architecture • real-time constraints monitored by helper threads => system reconfiguration, power management • real-time scheduling supported by multithreaded hardware=> fast context switch, isolation, power aware scheduling • high performance/low power by hardware multithreading and hardware reconfiguration=> latencies caused by reconfiguration or other events are bridged by switching to another thread,=> avoids speculation

34. 5. CARUSO System Architecture • Application Optical Tracking System • augmented reality => tracking of camera position and angle • can be done by detection of characteristics in key frames • problems: real-time, precision, energy efficiency

35. 5. CARUSO System Architecture • Solution: network of autonomic SoC Selection of characteristics Buffer Backward tracking Correspondance analysis Keyframe selection Projective reconstruction Measure ofQualtity Self-calibration Video signal Translation,Rotation Calibration-matrix Measure ofQualtity

36. 5. CARUSO System Architecture • Application: robot swarm • (e.g. cleaning the floor) • cooperation • real-time requirements • limited energy resources • highly dynamic • failures of single robots • … • => autonomic behavior

37. 6. CARUSO Roadmap • Planned project duration: 3 years • First year • basic HW design (multithreaded processor core, reconfigurable datapaths) in SystemC • basic helper threads • basic RT middleware • Second year • hardware prototype in FPGA • basic local autonomic functions • basic global autonomic functions • Third year • hardware optimization, ASIC synthesis • extended local and global autonomic functions • sample application integration • evaluation

38. 7. Conclusions • we propose a new SoC approach • general ideas • emphase connectivity, autonomic computing principles (self-X), real-time and low-power • explore and exploit the relationship between the different requirements • hardware ideas • combine reconfigurable hardware with a multithreaded processor core to support: • autonomic management (HW reconfiguration, helper threads) • power management (power aware scheduling in HW, multithreading instead of speculation, latency bridging) • real-time (RT scheduling in HW, isolation)

39. 7. Conclusions • software ideas • local autonomic management is done by a closed control loop using the helper threads • global, distributed autonomic management is done by a closed control loop using middleware • the middleware is responsible for • connectivity • handling the global autonomic principles (self-x) • global reconfiguration in HW and SW • optimization of the global energy consumption • global real-time properties • the work has just begun!