1. Instituto de Plasmas e Fusão Nuclear Instituto Superior Técnico Lisbon, Portugal http://www.ipfn.ist.utl.pt B. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition ITER CODAC Bruno Soares Gonçalves bruno@ipfn.ist.utl.pt http://ipfn.ist.utl.pt/EU-PhD/

2. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 2 CODAC CO ntrol, D ata A ccess and C ommunication system

3. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 3 Large-scale experiments: control and data aquisition challenges The next generation of physics experiments will –be highly complex –raise new challenges in the field of control and automation systems –demand well integrated, interoperable set of tools with a high degree of automation –deliver and process data at a rate of up to hundred GBytes/s. –deploy and integrate systems with different degrees of complexity and provenience

4. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 4 New projects prominently feature –solutions adopted from other laboratories, –hardware and software standards –industrial solutions. Are they any different from commercial systems ? –Although sharing a large degree of architectural commonality, given their unique requirements, traditionally, such systems have been purpose built. significantly greater amount of I/O capability required between computational elements unique and disparate I/O requirements imposed on their interfaces Large-scale experiments: control and data aquisition systems

5. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 5 Commercial technology will likely meet the basic requirements on which physics experiments can leverage for building future control systems Large-scale experiments: R&D on control and data aquisition R&D activities target –Self-triggered front-end electronics with adequate output bandwidth and data processing –MIMO controllers with efficient resource sharing between control tasks on the same unit –Massive parallel computing capabilities.

6. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 6 However… future systems are envisioned to be more than an order of magnitude larger than those of today More challenging will be… providing a robust, fault tolerant, reliable, maintainable, secure and operable control systems Large-scale experiments: control and data aquisition (more) challenges

7. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 7 Is ITER any different? ITER CODAC is a challenging endeavour ITER will generate a huge quantity of experimental data –150 plant systems –1 000 000 diagnostic channels –300 000 slow control channels – 5 000 fast control channels –40 CODAC systems –5 Gb/s data –3Pb/year data ( e.g. 12 IR cameras in a 10 minutes discharge: 1.728 Tbytes ) In addition... ITER will require a far higher level of availability and reliability than previous/existing tokamaks.

8. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 8 ITER Challenges: Scientific Exploitation ITER will generate huge quantities of experimental data – PBytes per year (but still less than LHC) (e.g. 12 IR cameras data resulting from a 10 minutes shot: 1.728 TBytes) ITER will provide tools for continuously accessing and analysing data during a pulse - Requires data indexing by events ITER will have a very strong flexible set of diagnostics and tools for optimising the performance during a pulse - Adequate tools and methodologies need to be developed ITER will have a limited number of pulse cycles and an unlimited number of ideas to be tested – Will schedule and reschedule many activities during a pulse ITER will evolve both equipment and ideas over 20 years – A lifetime of 30 years including procurement – evolution must be built into CODAC

9. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 9 ITER Challenges: Inherent Constraints ITER site will be a Nuclear Registered site ITER environment between JET and a Nuclear power station in terms of quality, audit trails,..... etc. To accomplish the scientific objectives will need control system architecture with freedom but within the licensing constraints Requires tools to guarantee safety, protection of investment (and a unique facility) and guaranteed operation Hostile environment for measurements, networks, electronics – human access will be restricted ITER will require a far higher level of availability and reliability than previous/existing tokamaks IT security will be a major issue Security with transparency is required. What does this mean for Remote participation?

10. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 10 ITER Challenges: Inherent Constraints ITER is assumed to be totally legacy-free for hardware and software Methodologies will have to be tested and proved on existing fusion devices before implementation on ITER It will be necessary to take informed decisions based on technology progress Maintenance will be an issue and proliferation of technologies must be avoided ITER is an international project In-kind procurement world-wide Integration of Plant Systems from all participants The implications of in-kind delivery of subsystems need to be recognised Powerful remote access networks Remote access security

11. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 11 ITER CODAC CODAC provides the COntrol, Data Access and Communication functions for ITER, allowing integrated operation. This includes: continuously monitoring the Plant Systems; displaying their status to operators including alarms; preparing and automating scheduled operations (including plasma pulses); recovering data from Plant Systems; storing and making all the data available. CODAC uses multiple logical and physical networks to segregate these disparate functions.

12. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 12 ITER: as seen by CODAC CODAC integrates ALL ITER Plant Systems Many networks: operation, interlocks, safety CODAC functions are like present tokamaks

13. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 13 ITER: Instrumentation and Control I&C is in 3 clear tiers –Safety: protects personnel, population and environment –Interlock: protects ITER investment –CODAC: operates ITER I&C is in 2 layers –Plant Systems: local responsibility –Networks when responsibility lies across Plant Systems ITER operation will be complex The investment needs to be reliable The licensing has to be simple

14. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 14 CODAC CODAC shall provide: Supervisory control functions as a project wide and interface specifications between CODAC and Plant Systems. Central data management functions i.e. data archiving, data monitoring and visualization functions. PSH functional profile and data exchange software for the asynchronous communication interface between CODAC and Plant System. Mini CODAC as a tool to carry out FAT (Factory Acceptance Test) Specifications for the Network Interface Units with their interface specifications. Self-description schema and tool for Plant System I&C designers. Functional mimic diagrams for Plant System data monitoring, trends, plasma discharge preparation, sequencing, and data display. Functions for global and plant operating states management, plasma control, data recording with time stamp, data marshalling, data archiving etc. Capability to log all commands and state transitions along with all the associated data with time stamping.

15. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 15 CODAC and Plant Systems I&C architecture CODAC Systems Provides supervisory functions of ITER plant operation, plasma experiment, overall ITER plant operating status monitoring, data archiving and alarm handling, HMI interface and remote experiment handling functions. Modular design with Dual Redundancy required

16. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 16 CODAC components The principal CODAC System is the Supervisory Control System The Supervisory Control System: dynamically allocates any required resources to an ITER operation Task. manages a dynamically evolving set of concurrent activities, each of which is driven by an Operation Schedule. The Operation Schedule is prepared by Schedule Preparation and each Operation Schedule requires Schedule Validation before becoming executable. is executed by Schedule Execution once the resources are made available by SCS. There is a strong interface between scheduling and ITER operation planning

17. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 17 CODAC components The status of ITER is obtained from Plant Monitoring, which also generates a data stream for Data Logging. Maximum refresh frequency proposed is 3 Hz, corresponding to a human reaction. Minimum rate is 0.1 Hz to ensure a continuous record and continuous functionality checking. Monitoring data are available in the Experiment Sites to enhance contact with operation. The functionality is typical of an industrial SCADA (Supervisory Control And Data Acquisition) displays on mimic diagrams, trending, warning and alarm handling, manual triggering of commands or changes to set-points.

18. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 18 Central data management functions CODAC shall provide data logging, data monitoring, data archiving and data visualisation functions within the Main Control Room. Data provided from the Plant System I&C in a format compatible with the CODAC specifications Data are generated by different parts of the ITER plant at different sampling rates according to the information itself and according to the operational state of ITER. The notion of pulse archive also disappears, replaced by the data in a particular pulse being and identifiable time interval in a continuous data retrieval stream. Storage strategies required for efficient recovery of data taken at different sampling rate (0.1 Hz to 1 MHz). Separating the total data flow into suitable streams to optimize the retrieval of archived information.

19. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 19 Issues: Operation Software IssuesActions Operation for longer periods or even continuous the operation should be considered continuous and the ageing ‘shot’ paradigm shall be replaced Event-driven support where data is acquired or actions performed only when relevant events occur –data indexing using events and time- stamps with synchronism of all digitizer and generator endpoints (absolute time) Provide tools for continuously accessing and analysing data during a pulse

20. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 20 CODAC and Plant Systems I&C architecture CODAC Networks Provide ITER wide physical and logical interconnections between CODAC and the Plant Systems. The roles and functions of networks are defined according to their performance requirements.

21. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 21 CODAC Networks The CODAC architecture is based on distributed systems connected over a set of complementary asynchronous and synchronous networks Each Plant System and CODAC Systems can communicate over one or more networks Asynchronous general purpose Plant Operation Network (PON) provides the backbone of CODAC communication for most CODAC data traffic. General ITER Networks (GIN) used to connect between the Plant Operation Zone and external Experiment and Analysis Sites. Networks used will depend on the required functionality, volume of data, bandwidth and latency.

22. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 22 High Performance Networks Some functions of CODAC require deterministic, hard real- time communication and synchronization between distributed nodes. These requirements are addressed by the CODAC High Performance Networks Synchronous DataBus Network (SDN) Time Communication Network (TCN) Event Distribution Network (EDN) Audio Video Network (AVN)

23. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 23 Issues: Timing, Synchronization, events and Synchronous data Transport Networks IssuesActions Distribution of timing signals from central unit to sub-system timing decoder cards where timing signals are subsequently connected to digitizers and control processors Include timing, synchronization and event decoder directly on digitizers and control processors –Higher reliability –Improve commissioning and maintenance efforts –Possibility of performing the timing and synchronization of control processes over the synchronous network (IEEE 1588) Absolute time conceptCODAC shall provide absolute time broadcast; triggers are timing events; clocks are recovered from the synchronous data (optical) links used for events transport. –Autonomous local absolute time clock units on the digitizers synchronized through a fast network New diagnostics and plasma controllers may require an updated real-time control and monitoring hardware infrastructure Specify a new synchronous network infrastructure –Lower latency distribution of plasma variables and events (< 2 us)

24. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 24 CODAC and Plant Systems I&C architecture Plant Systems provide data acquisition, operation & control, status/alarm monitoring, and data communication functions with the CODAC systems. Also have local autonomous operation control independent from the CODAC. Plant Systems communicates only through CODAC.

25. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 25 CODAC and Plant Systems I&C architecture Plant System Host standard image of Plant System to the CODAC. It is a single point entry for the asynchronous communication with CODAC (data exchange) Controls data flow, interprets all the commands and passes them to the Subsystem Controller for necessary actions.

26. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 26 Plant System supplier’s responsibility Plant System suppliers shall: –Provide self-description data of their Plant System I&C and shall receive interface requirements from the CODAC. –Provide and implement applications for their Plant System monitoring, data acquisition, autonomous operation and control functions. –Provide Plant System simulators/Plant subsystem simulators. – Carry out Factory Acceptance Tests using mini-CODAC as a testing tool. Also Plant System is responsible to carry out installation, commissioning and SAT at the IO site.

27. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 27 Mini-CODAC Development of a mini-CODAC mandatory It is required to test all CODAC concepts prior to full development and also to provide a development and test tool for Plant System designers Mini-CODAC is a CODAC emulator for development of Plant Systems Tool for carrying out functional testing of the Plant System to certify Plant System functional integration. Scalable functionality to achieve limited performance testing of the Plant System interfaces with CODAC. Used to carry out Provisional Acceptance Tests (and for repeating the FAT if needed) to prove and verify that all plant cabling and connections have been terminated correctly and that the input and output schedule is as required by the design. Does not define the technical functionality and test processes of Plant Systems but defines and provides environment with limited performance to facilitate integration testing of Plant Systems with CODAC.

28. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 28 Plant System Simulator Used to test the behaviour of Plant Systems during different phases of integration (Factory Acceptance Tests, Commissioning and Site Acceptance Tests and also during plant operation). Plant System/Sub-system simulator should be based on self description data from Individual Plant System/sub-system supplier.

29. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 29 CODAC and Plant Systems I&C architecture Equipment May not communicate in a project-wide standardised form. Configured hierarchically according to the individual Plant System design. Not procured for direct interface with CODAC but subject to an integration procurement arrangement to deliver as a Plant System component. (sensors, actuators, instrumentation, electronics, modules, racks, cabling, wiring,…)

30. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 30 Sub-systems and equipments Control System Interface Definition  Optics alignment controller interfaces  Laser alignment unit interfaces  Lasers controller interfaces  Detection system controller interfaces  Windows monitoring unit interfaces  Inner wall monitoring unit interfaces  Control and monitoring software specification  Local controller hardware specification 30 LIDAR CONTROL AND DATA ACQUISITION as example Diagnostic systems will have local controllers and data acquisition which may have to be developed to meet the requirements

31. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 31 Issues: Data Acquisition IssuesActions The size of the data collected in each shot is increasing (ITER will generate huge quantities of data. e.g 12 IR cameras data resulting from a 10 minutes shot: 1.728 TBytes) Implement faster data transport to comply with cycle-time Higher-speed real-time pulse processing both during and after shot High sampling rates and data bandwidth Data reduction techniques directly in the sub- system, preferably on the digitizer modules –Increment the transient recorder time window –Solve local bandwidth bottlenecks –improve the CODAC performance since data reduction tasks will be parallelized, lessening data management burden on CODAC infrastructure thus helping meeting the operation delay constrains

32. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 32 Issues: Instrumentation IssuesActions Multitude of different hardware platforms to maintain ‘generic’ sub-system able to perform one or more of the (fast) local control operations, feedback and data acquisition tasks Develop for easy deployment and maintenance Higher processing power requirements for local data reduction techniques, fast real-time local control or other specialized algorithms on the digitizers Use of processors with parallel processing capabilities (multicore, FPGAs,…), interconnected through a (multiple-) full-mesh topology low-latency high bandwidth network for transport of variables and data streams Ease the programming of local real- time processing algorithms by non- specialized users Development of a set of helper tools for easier programming, simulation and deployment of code on reconfigurable devices (Field Programmable Gate Array - FPGA) and multi-core processors

33. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 33 Issues: Instrumentation (cont.) IssuesActions Improve systems reliabilityStandards based instrumentation with inherent redundancy and mechanical/ thermal characteristics (e.g. Advanced Telecommunications Computer Architecture - ATCA) Local and global management of hardware operation is required to improve maintainability Implementation of a standards based improved hardware management interface (e.g. Intelligent Platform Management Interface (IPMI), Shelf (crate) management (ShM)

34. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 34 Issues: Instrumentation (Cont.) IssuesActions Easier installation/replacement of hardware modules Hardware interface designed for ‘Plug-and-Play’, and ‘Hot-swap’ e.g. ITER will evolve both equipment and ideas over 20 years therefore evolution must be built into CODAC Improve the speediness of sub-system commissioning and integration on global CODAC Design the local sub-system control and data acquisition software for autonomous operation Preliminary test operations during development can be performed autonomously Scalability

35. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 35 CODAC components Plasma Control is implemented as a specific Operation Schedule to maximise reuse of automation and plasma control tools. General feedback control, including Plasma Control, uses a Synchronous DataBus to communicate data converted to physics units, including an estimate of the error on each signal and its status. Evaluation of plasma diagnostic information is local in the diagnostic Plant System if this is straightforward. Information is collected over the Synchronous DataBus for analysing data from multiple Plant Systems and finally transmitted over the Synchronous DataBus to the actuators.

36. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 36 High Maintenance Proliferation of interfaces Should converge on modern instrumentation, computer, etc. standards Lack of commonality and functionality between different devices RTMC systems e.g. JET PPCC not simply exportable to other devices and vice-versa Lack of flexibility Integration of new equipment and physics into the existing infrastructure is time-consuming. Lack of good transport and integrated models and tools Integrated development environment and interchange formats Future developments should acknowledge these issues Limitations of existing Control Systems: JET as an example

37. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 37 Issues: Control Systems IssuesActions Higher algorithm complexity and higher number of input signals for plasma control Use of MIMO plasma controllers Higher real-time processing power Lower loop delays for time- critical real-time control Faster, lower latency real-time local synchronous network for variable sharing among processors Faster design cycle of RT control systems Develop an improved integrated framework for code development, simulation and deployment

38. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 38 JET has a wide range of Plasma Control Systems Aim of Control Systems in fusion: JET as an example To reach and reproduce scenarios which cannot be programmed Quasi-Steady State Experiments Magnetic and Kinetic Profile & ITB Experiments Mode Conversion Experiments Radiation and Impurity Experiments MHD Experiments To protect Plasma and Machine NB Shinethrough (WALLS, PEWS and NBLM) LHCD Launcher (Monitor Iron and Radiation) Avoid Disruptions Mimize waste (Neutrons, Tritium)

39. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 39 Control and data acquisition in fusion: JET Vertical Stabilization as example Elongated plasmas are vertically unstable –If no corrective action is taken the plasma column moves vertically until it reaches the vessel protecting tiles. –The plasma then rapidly shrinks and eventually disrupts discharging all its energy to the machine structures imparting large impulsive forces. Forces of hundreds of tons were measured at JET VS system designed to make the plasma vertically stable so that the Shape Controller can successfully control the plasma position and shape.

40. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 40 Control and data acquisition in fusion: ITER Vertical Position Control Loss of vertical plasma position control in ITER will cause thermal loads on Plasma Facing Components of 30-60 MJ/m 2 for ~0.1s. –PFCs cannot be designed to sustain (repetitive) thermal loads like those quoted above. VDE also generates the highest electromagnetic loads –A phenomenological extrapolation of horizontal forces from worst JET cases implies horizontal loads ~45MN on ITER vacuum vessel. –MHD wetted kink model developed to simulate the horizontal loads predicts ~20MN. –Vertical loads ~90MN Plasma vertical position in ITER must be robust & reliable to ensure a vertical plasma position control loss is a very unlikely event

41. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 41 JET Vertical Stabilization: Specifications of the MIMO architecture Reduction of –loop delay on the signal acquisition/generation endpoints (down to 10 µs) –on the data interconnect links from and to the processing unit –on the analogue signal path (analogue filters); High processing power –on the acquisition/generator endpoints –on the system controller; –improvement of MIMO algorithm performance Synchronization of all digitizer/generator endpoints; Architecture designed for maintainability, upgradeability and scalability; Low cost per channel; Low risk of implementation and testing.

42. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 42 JET Vertical Stabilisation Vertical Stabilization Controller (input signals >190): x86-based ATCA controller Up to 12 DGP cards (PCIe links through the ATCA full mesh backplane) Each board has 32 18 bit ADC channels, each separately isolated Parallel execution on FPGAs for MIMO signal processing (Control loop delay < 50  s, aim < 10  s) Freeware operating system RTAI The Aurora and PCI Express communication protocols allow for data transport, between modules, with expected latencies below 2 µs.

43. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 43 ATCA @ JET Vertical Stabilization Front viewRear view 192 input signals

44. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 44 ITER relevant technology: ATCA ATCA is the most promising architecture to substantially enhance the performance and capability of existing standard systems It is designed to handle tasks such as –event building, –feature extraction –high level trigger processing. –TeraOPS of processing power in a single sub-rack. First commercial open standard designed for –high throughput –High availability High interest to data acquisition physics and attractive for experiments requiring a very high up-time

45. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 45 Why ATCA? ATCA platform is gaining traction in the physics community because of Advanced communication bus architecture (serial gigabit replacing parallel buses) very high data throughput options and its suitability for real-time applications Agnostic backplane that accepts several serial switch network protocols Scalable shelf capacity to 2.5Tb/s Scalable system availability to 99.999% Robust power infrastructure (distributed 48V power system) and large cooling capacity (cooling for 200W per board) High levels of modularity and configurability Ease of integration of multiple functions and new features The ability to host large pools of DSPs, NPs, processors and storage The ability to host multiple controllers and storage on a shelf High security and regulatory conformance Reliable, full redundancy support Reliable mechanics (serviceability, shock and vibration) Hardware management interface

46. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 46 ATCA @ JET Vertical Stabilization: “the star of the show” IPFN’s ATCA-MIMO-ISOL

47. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 47 Does it work? VS controller in action - Vertical kicks experiment

48. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 48 CODAC milestones First plasma assumed to be 2018 All functionality available – end 2014 Control room and site distribution operational – end 2012 First integration – end 2012 Mini-CODAC operational – end 2010 Plant System Host –end 2009 These dates may be revised (and certainly not for earlier)

49. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 49 Summary ITER CODAC is a challenging endeavour

50. Author’s name | Place, Month xx, 2007 | EventB. Gonçalves | Lisbon, February 20, 2009 | Diagnostics & Data Acquisition 50 A professor is only as good as the questions he raises in his pupils minds... Not just PhD EU PhD