Digital On-Demand Computing Organism DodOrg SPP OC Kolloquium DFG SPP 1183 Organic Computing München, Oktober 7/8, 2010

Transcription

1 Digital On-Demand Computing Organism DodOrg SPP OC Kolloquium DFG SPP 113 Organic Computing München, Oktober 7/, 2010 KIT The cooperation of Forschungszentrum Karlsruhe GmbH and Universität Karlsruhe (TH)

2 Talk Overview Project Motivation and Overview Current Work: Organic Hardware Organic Middleware Organic Low Power Management Organic Middleware Demonstrator Platform Overview Scenarios Conclusion SPP 113 OC Kolloquim München, 7.-. Oktober 2010

3 DodOrg Motivation Classic Scenario: DodOrg Scenario: Only those scenarios can be handled that were considered in advance, where the cause can be detected, where the corresponding reaction had been explicitly programmed. Lack of adaptation leads to insufficient reactions (e.g. shutdown ) Demonstrator platform System reaction based on indications (higher level of abstraction) e.g. CRC/bit error rate, network bottleneck, environmental change or change on application level Proper reaction possible even if Scenario was not considered in advance. Cause was not detected, Reaction was not explicitly programmed. Flexible response to changed environmental situation Scenario detection: recognize that something is different Adapt to changed requirements either by known path or gradual process of rearrangement (optimization, healing) Plasticity: Stabilization but not petrification SPP 113 OC Kolloquim München, 7.-. Oktober 2010

4 Phase III: Project Objectives Stability The ability of the system to provide the required service while reacting upon external and internal events. Robustness Extending the stable system property towards more serious system changes. + Oscillation avoidance + Normal operating conditions - Faulty components - Malicious attacks + Attack resistance + Fault resistance + Increased tolerance - Increased overhead SPP 113 OC Kolloquim München, 7.-. Oktober 2010

5 Cell Level Organ Level Biological Considerations (Brändle) Organic Monitoring System (Karl) Proactive Intelligent Data Analysis Brain Level DodOrg: Refined Layer Model Nervous System Self-Adaptation Self-Optimization Self-Healing Application Testbed (all groups) Application Monitoring Application API Heart Stable Hormone Interaction Organic Middleware (Brinkschulte) Middleware Monitoring, Feedback Hormone Level Computation Thermal-aware Energy distribution Distributed Low Power Management (Henkel) Temperature, Local Traffic Myocardial Cell Extension Dynamic Power Management Real-time considerations Organic Processing Cells (Becker) Hardware Monitoring Stabiltiy Aspects SPP 113 OC Kolloquim München, 7.-. Oktober 2010

6 Organic Processing Cells (s): Chip To Chip Communication (Prof. Becker) Goals Seamless and transparent expansion of the on chip communication services (artnoc) Dynamic resource pool physical growth of DodOrg organism Challenges Physical Connection # I/O Pins Bandwidth Latency Hot Plug /Unplug Control Flow Overhead µproc Cell FPGA Cell IO Cell IO Cell Dynamic Address Space Transparent µproc Cell System 1 System 2 IO Cell Extension IO Cell IO Cell IO Cell Broadcast Real-time Adaptive routing SPP 113 OC Kolloquim München, 7.-. Oktober 2010

7 Organic Processing Cells (s): Chip To Chip Communication (Prof. Becker) Off-Chip- (OCI) Parallel Serial Asynchronous Transmission artnoc Handshake Signals artnoc Flit-Data 3 Phase Operation Link Negotiation Backchannel Detection # Virtual Channels (VCs) # Real-Time Channels Data Transmission Link Cutback Terminate open artnoc VCs Chip Chip R R R R 3 2 R R R R R R R R R R R R R R R R 3 2 Off-Chip R R SPP 113 OC Kolloquim München, 7.-. Oktober 2010

8 link efficiency % Organic Processing Cells (s): Chip To Chip Communication (Prof. Becker) Data Transmission: Adaptive Control Router_a Flow Protocol Goal: Increase Serial Link Efficiency port_out_a Differential Control Flow Transmission 1 VC used: P(C ch ) < 0,1 > 1 VC used: P(C ch ) > 0,5 data(7:0) vc_id(1:0) valid Amount of Control Flow mainly depends full(3:0) on VC usage 2 Protocol Modes Differential Mode Auto Sequence Mode rtc_ready(2:0) data(7:0) bc_grant port_in_a vc_id(1:0) valid full(3:0) rtc_ready(2:0) Diff Mode bc_grant Auto Mode OCI_a 1 1 OCI_b Router_b port_in_b data(7:0) vc_id(1:0) valid full(3:0) rtc_ready(2:0) bc_grant port_out_b data(7:0) vc_id(1:0) valid full(3:0) rtc_ready(2:0) bc_grant VC 2 VC's 50/50 3 VC's 50/20/30 virtual channel usage 2 VC's 10/ SPP 113 OC Kolloquim München, 7.-. Oktober 2010

9 Proactive Intelligent Data Analysis Organic Monitoring: State Classification and Evaluation (Prof. Karl) Objectives Classification of the system state with regard to environmental conditions Identification of bottlenecks Determine the outcome of an optimization cycle Providing these information to Organic Middleware and Thermal Management Biological Considerations (Brändle) Self-Adaptation Self-Optimization Self-Healing Stable Hormone Interaction Stable Energy Distribution Interaction, Metrics Application Testbed (all groups) Application API Organic Middleware (Brinkschulte) Hormone Level Computation Dynamic Power Management Real-time considerations Application Monitoring Middleware Monitoring, Feedback Distributed Low Power Temperature, Management (Henkel) Local Traffic Application Requirements Organic Processing Cells Hardware (Becker) Monitoring Status Plasticity Aspects Organic Monitoring System (Karl) Monitoring Hardware Status Flexible, rule-based Approach Based on the data gathered by our low-level monitoring-infrastructure Evaluation rules are defined at runtime in a dedicated learning phase Rules can be updated at runtime to adapt to new environmental conditions Configuration Feedback Data Raw & Cooked Middleware Thermal Management SPP 113 OC Kolloquim München, 7.-. Oktober 2010

10 Organic Monitoring: State Classification and Evaluation (Prof. Karl) Rule Layout rule = (t, v, p1, p2, p3) One Rule for each event type Rule Creation Determine the normalized occurence ratio for each event type at a predefined time Creation of a histogram Determination of the points p1, p2, p3 Evaluation Using a simple transfer function (TF) TF converts the ratio into an evaluation score System State is classified using a weighted arithmetic mean of all evaluation scores SPP 113 OC Kolloquim München, 7.-. Oktober 2010

11 Organic Monitoring: State Classification and Evaluation (Prof. Karl) Rule Layout rule = (t, v, p1, p2, p3) One Rule for each event type Rule Creation Determine the normalized occurence ratio for each event type at a predefined time Creation of a histogram Determination of the points p1, p2, p3 Evaluation Using a simple transfer function (TF) TF converts the ratio into an evaluation score System State is classified using a weighted arithmetic mean of all evaluation scores SPP 113 OC Kolloquim München, 7.-. Oktober 2010v

12 Organic Monitoring: Outlook (Prof. Karl) Phase/ Trend Detection and Prediction Prediction of future system states Identification of potentially harmful system states in advance Avoiding Bad System States through Proactivity Initiating proper system changes to avoid bad or harmful system states (e.g. high temperature or performance bottleneck) Introducing a feedback-loop for on-line evaluation of the system changes Proactive self-healing and self-optimization Avoid this state Past System States Current System State Predicted System States SPP 113 OC Kolloquim München, 7.-. Oktober 2010

13 Peers (in neighbored s) Organic Low Power Management: Managing Energy-Distribution (Prof. Henkel) Trade & Negotiate Legend: data / information actions Power source Energy Input Energy Budget Fill Influencing Hormone Expression Energy level Consume Organic Middleware Low energy consumption Cost Function Each has a Local Energy Budget Future energy level Actual energy level Actual power state RT criteria Determines the local available Power energy / RT Global Power Source Policy P 1 Efficiency Temperature Local traffic Energy Fade P Budget Local Energy Power 2 States PAgent Budget 3 controlling Local Energy Budget P 4 Receives temperature data each pulse Scheduled Voltage / frequency setting Energy Distribution: goals Assigned Tasks Avoidance of local thermal hot-spots Energy Distribution: main concept Tasks Organic Monitoring Assigns energy budgets to s (pulse-based) Negotiates & Trades energy budget with neighboring s Influences Power policies SPP 113 OC Kolloquim München, 7.-. Oktober 2010

14 Organic Low Power Management:Thermal Management (Prof. Henkel) Agent negotiation based on simple economic principles Energy budget made up of Energy Units Trading based on supply & demand Temperature incorporated as a negotiation penalty Agents only trade with their direct neighbors One Energy Unit per pulse Energy Units propagate across the chip over time Thermal simulation of energy distribution Agent Agent Agent Thermal-aware power negotiation SPP 113 OC Kolloquim München, 7.-. Oktober 2010

15 Temperature ( C) Organic Low Power Management: Outlook (Prof. Henkel) Current approach succeeds in keeping temperature below a threshold, however the effectiveness of agent trading can still be improved Temperature below threshold Time Interval (ms) Improvement of negotiation process using economic learning Organic state classification as input Trading multiple energy units at a time will decrease propagation time Considerable improvement for large chips (hundreds of cores) Better trading between different thermal domains (i.e. physically separated chips) SPP 113 OC Kolloquim München, 7.-. Oktober 2010

16 Organic Middleware: Re-Intruduction of the Artificial Hormone System (Prof. Brinkschulte) Task Mapping Providing Self-X Properties: Self-Configuration Self-Healing Self-Optimization Good mapping regarding Requirements of each task Relationships of the tasks Condition of each cell and it s neighborhood Reacting and Adapting to changes (plasticity) e.g. increased bit-rate errors Reaching stable mapping conditions Oscillation avoidance SPP 113 OC Kolloquim München, 7.-. Oktober 2010

17 Organic Middleware: Implementation of the AHS for µcs (Prof. Brinkschulte) Pure ANSI C for deployment in environments from small µcs to large PCs Distributed Application AHS 7729 Total Physical Source Lines of Code (SLOC) AHS Hormone Communication AHS Task Management AHS Message Communication Simple exchange of underlying OS due to the AHS Basic OS Support abstraction layer AHS Log Management AHS Basic OS Support AHS Error Management AHS List Management AHS Basic Communication Support Network protocol easily interchangeable due to AHS Basic Communication Support interface Operating System Communication System SPP 113 OC Kolloquim München, 7.-. Oktober 2010

18 Network- Organic Middleware: Outlook (Prof. Brinkschulte) Prototype implementation: Analyzing the effects on system stability with the influences of: Power Monitoring MicroBlaze µc Config- Setting boundaries for the control influences Conflict avoidance through proactivity Immune System for the AHS: AHS - Middle ware Power- Monitor Immune mechanisms for advanced Self-Healing and Self-Protecting Aspects to increase Robustness (together with the Organic Processing Cell Capabilities and the Organic Monitoring) Robustness against mal-behaving internal/external components (comparable to illness in a biological system) Being able to react to ill s Counter-measures against malicious attacks SPP 113 OC Kolloquim München, 7.-. Oktober 2010

19 Prototype: Interaction of HW, Mon, MW and TM HW-s: Networking via HW- Energy Budget from power management System Status and Estimations of Future Changes from monitor clk_dp data path MicroBlaze-µC with Middleware Ring Oscilator Temperature Sensor Config- Power- Monitor clk_net Network- artnoc- Router artnoc- Router Network- Config- Power- Monitor clk_dp data path MicroBlaze-µC with Middleware Ring Oscilator Temperature Sensor Develop Protocols: Infos Ranges Packet Formats etc clk_dp data path MicroBlaze-µC with Middleware Ring Oscilator Temperature Sensor clk_dp clk_net data path Monitor MicroBlaze-µC with Middleware Config- Network- artnoc- Router Power- Network- Config- Power- Network- artnoc- Router Config- Monitor clk_dp data path MicroBlaze-µC with Middleware Oscilator Temperature Sensor artnoc- Router Network- artnoc- Router Ring Config- clk_dp data path MicroBlaze-µC with Middleware clk_dp clk_dp data path MicroBlaze-µC with Middleware Ring Oscilator Temperature Sensor Ring Oscilator Temperature Sensor Monitor Power- Monitor Network- artnoc- Router Power- Config- Power- Network- artnoc- Router Config- Monitor data path MicroBlaze-µC with Middleware Ring Oscilator Temperature Sensor Power- Monitor Ring Oscilator Temperature Sensor SPP 113 OC Kolloquim München, 7.-. Oktober 2010

20 Demonstrator Hardware Floorplan clk_net clk_dp data path MicroBlaze-µC with Middleware Config- Network- Empty- Network- Config- clk_dp data path MicroBlaze-µC with Middleware Power- Power- Microblaze Ring Oscilator Temperature Sensor Monitor artnoc- Router artnoc- Router Monitor Ring Oscilator Temperature Sensor clk_dp clk_dp data path MicroBlaze-µC with Middleware Config- Network- artnoc- Router Network- artnoc- Router I/O- Config- data path MicroBlaze-µC with Middleware Power- Power- Ring Oscilator Temperature Sensor Monitor Monitor Ring Oscilator Temperature Sensor SPP 113 OC Kolloquim München, 7.-. Oktober 2010

21 DodOrg Demonstrator Scenarios Providing Self-X Properties: Self-Configuration Self-Healing Self-Optimization SPP 113 OC Kolloquim München, 7.-. Oktober 2010

22 DodOrg Demonstrator Scenarios Providing Self-X Properties: Self-Configuration Self-Healing Self-Optimization SPP 113 OC Kolloquim München, 7.-. Oktober 2010

23 DodOrg Demonstrator Scenarios Providing Self-X Properties: Self-Configuration Self-Healing Self-Optimization SPP 113 OC Kolloquim München, 7.-. Oktober 2010

24 DodOrg Demonstrator Scenarios Providing Self-X Properties: Self-Configuration Self-Healing Self-Optimization SPP 113 OC Kolloquim München, 7.-. Oktober 2010

25 Visualisation Show all that is happening inside Working demonstrator only shows the result, not the interior of what is happening while the system is running Visualisation of the : Activity Monitoring Info Temp and Energy Budget Running Tasks Cycles Bandwidth MW sends infos via serial interface to an PC where the data is visualized SPP 113 OC Kolloquim München, 7.-. Oktober 2010

26 Conclusion Concepts individually tested and applicability proven Monitoring: hormone-inspired associative event coding and use of associative counters Middleware: reaching stable hormone and mapping situations while still being able to react to changes Low-Power-Processing: thermal-aware local agent-based energy budget distribution Processing Cells: Growth of the OC-hardware platform through adaptive chip to chip communication interface Incorporation of the DodOrg subsystems into demonstrator platform SPP 113 OC Kolloquim München, 7.-. Oktober 2010

27 Organic Monitoring System (Karl) Thank you for your attention! Application Testbed (all groups) Questions? Organic Middleware (Brinkschulte) Organic Low Power Management (Henkel) Organic Processing Cells (Becker) SPP 113 OC Kolloquim Augsburg, September 2009

28 List of Publications: D. Kramer, R. Buchty, and W. Karl, A Scalable and Decentral Approach to Sustained System Monitoring, ACACES,2009 R. Buchty and W. Karl, Design Aspects for Self-Organizing Heterogeneous Multi-Core Architectures, IT - Information Technology Journal 5/0, 200 R. Buchty, D. Kramer, and W. Karl, An Organic Computing Approach to Sustained Real-time Monitoring, BICC0, 200 R. Buchty, O. Mattes, and W. Karl, Self-aware Memory: Managing Distributed Memory in an Autonomous Multi-master Environment, ARCS, 200 R. Buchty and W. Karl, A Monitoring) Infrastructure for the Digital on-demand Computing Organism (DodOrg), IWSOS, 2006 Hans-Peter Löb, Rainer Buchty, Wolfgang Karl, A Network Agent for Diagnosis and Analysis of Real-time Ethernet Networks, CASES, 2006 U. Brinkschulte and A. von Renteln, Analyzing the Behavior of an Artificial Hormone System for Task Allocation, ICATC, 2009 U. Brinkschulte, A. von Renteln, and M. Weiss, Examining Task Distribution by an artificial hormone system based middleware, ISORC, 200 U. Brinkschulte, M. Pacher and A. von Renteln, An Artificial Hormone System for Self-Organizing Real-Time Task Allocation, in Organic Computing, 2007 U. Brinkschulte, A. von Renteln, and M. Pacher, Reliability of an Artificial Hormone System with Self-X Properties, PDCS, 2007 T. Ebi, M. A. Al Faruque, and J. Henkel, TAPE: Thermal-aware Agent-based Power Economy for Multi/Many-Core Architectures, ICCAD 2009 M. Shafique, L. Bauer, and J. Henkel, REMiS: Run-time Energy Minimization Scheme in a Reconfigurable Processor with Dynamic Power-Gated Instruction Set, ICCAD 2009 M. A. Al Faruque, R. Krist, J. Henkel: ADAM: Run-time Agent-based Distributed Application Mapping for on-chip Communication", DAC 200 C. Schuck, B. Haetzer, and J. Becker, An for a Decentralized 2d-Reconfiguration on Xilinx Virtex-FPGAs for Organic Computing, ReCoSoC, 200 C. Schuck, M. Kuehnle, M. Huebner, and J. Becker, A framework for dynamic 2D placement on FPGAs, IPDPS, 200 C. Schuck, S. Lamparth, J. and Becker, artnoc - A Novel Multi-Functional Router Architecture for Organic Computing, FPL, SPP 113 OC Kolloquim Augsburg, September 2009