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Designing a CODAC for Compass

Designing a CODAC for Compass. Presented by: André Sancho Duarte. Outline. Introduction to the CODAC concept Compass Tokamak CODAC in modern fusion experiments Issues Needs Solutions CODAC implementations Firesignal Other examples Application to Compass. CODAC System.

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Designing a CODAC for Compass

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  1. Designing a CODAC for Compass Presented by: André Sancho Duarte

  2. 9 October 2008, European Doctorate on Fusion Science and Engineering Outline • Introduction to the CODAC concept • Compass Tokamak • CODAC in modern fusion experiments • Issues • Needs • Solutions • CODAC implementations • Firesignal • Other examples • Application to Compass

  3. 9 October 2008, European Doctorate on Fusion Science and Engineering CODAC System Control, Data Access and Communications System for: • Control • Experiment configuration • Support systems configuration • Data Acquisition and Retrieval • Communications • Remote Participation

  4. 9 October 2008, European Doctorate on Fusion Science and Engineering CODAC Diagram for ITER

  5. 9 October 2008, European Doctorate on Fusion Science and Engineering Compass Tokamak • Major radius 0.56 m • Minor radius 0.18 – 0.23 m • Plasma current < 350 kA • Magnetic field 1.2 or 2.1 T • Triangularity ~ 0.5 - 0.7 • Elongation ~ 1.8 • Pulse length < 1 s • PLH, 1.3 GHz < 0.4 MW • PNBI 2 × 0.3 MW

  6. 9 October 2008, European Doctorate on Fusion Science and Engineering CODAC for Compass • The development of a control and data acquisition system for Compass represents an opportunity to test ITER relevant solutions • The following areas are planned to test in Compass • Remote maintenance/upgrade of the control software and re-programmable hardware. • Automatic/interactive installation and deployment of instrumentation hardware. • Formal self-description of plant systems, including diagnostic systems, using the XML set of technologies. • Fast, real-time multivariable (MIMO) plasma controllers. • Online data reduction as an option or in parallel to raw data storage on large memories.

  7. 9 October 2008, European Doctorate on Fusion Science and Engineering Modern Fusion Experiments • Pulse duration over 1 second • Expectation of human intervention • Around 50 diagnostics, some very complex • Over 100 MB/s of data per diagnostic • Example: Rogowsky coils in Compass can produce 256 MB/s (32 channels of 4 bytes @ 2 Msamples/s) • Small number of pulses during a campaign • Constant monitoring of the machine and its envolving

  8. 9 October 2008, European Doctorate on Fusion Science and Engineering Typical Experiment Flow Chart

  9. 9 October 2008, European Doctorate on Fusion Science and Engineering Desired Experimental Chart

  10. 9 October 2008, European Doctorate on Fusion Science and Engineering Issues- Collected Data (1/3) • The size of the data collected can cause data transport and storage issues and increment of the operation cycle-time beyond the machine constrains • Implement faster data transport to comply with machine cycle-time (use of new generation faster data transport networks) • Higher-speed real-time pulse processing both during and after shot? • Implement event-driven data acquisition operation • Data is acquired or actions performed (e.g. change acquisition rate) only when relevant events occur • Provide data compression capability into the diagnostics (less data to store and faster data transfer)

  11. 9 October 2008, European Doctorate on Fusion Science and Engineering Issues- Collected Data (2/3) • Some diagnostics require high sampling frequencies; current technical capabilities may be exceeded when operating for large periods • Use of standards-based fast data transfer on the data paths (e.g. PCIe) • Use of local fast memory with sizes of several GB and bandwidth of GB/s • Use of data compression when bandwidth bottlenecks still remain

  12. 9 October 2008, European Doctorate on Fusion Science and Engineering Issues- Collected Data (3/3) Data reduction techniques: • Data Compression: • Lossless algorithms • Keep all the data • Fast compression and decompression available • Typical data can be highly compressed • Loss algorithms can provide extra compression • Can provide extra compression for specific data • Variable acquisition rates • Good for events localized in time • Data loss for unexpected events

  13. 9 October 2008, European Doctorate on Fusion Science and Engineering Issues – RT Data Processing (1/2) • Higher RTC processing power required for local data compression or reduction, monitoring of diagnostic output and generation of plasma control variables • Use of processors with parallel processing capabilities, high-throughput and low latency (multi-core CPUs, FPGAs, DSP …) • hardware processors included on the digitizers can process and manage RTC high throughput data flow and perform preliminary basic algorithms or data compression/reduction • Use of data processing units where various boards are interconnected through a full-mesh topology network having low-latency and high bandwidth

  14. 9 October 2008, European Doctorate on Fusion Science and Engineering Issues – RT Data Processing (2/2) • New diagnostics and plasma controllers may require an updated real-time control and monitoring infrastructure. • Higher algorithm complexity and higher number of input signals • Lower loop delays for time-critical real-time control and distribution of plasma variables and events (sometimes under 10 µs) • Better timing, synchronization and RT messages networks.

  15. 9 October 2008, European Doctorate on Fusion Science and Engineering Issues – Digital Instrumentation

  16. 9 October 2008, European Doctorate on Fusion Science and Engineering Innovation on Instrumentation • The referred requirements reveal the importance of a platform capable of providing: • High-throughput real-time hardware signal processors at the acquisition level • Low-latency serial gigabit full-mesh interconnection between cards • Integrated RTC event-based acquisition, operation and storage • Integrated synchronism of all digitizer • Presently the ATCA based instrumentation is a good candidate • ATCA systems are expected to become the backbone of the CODAC in Compass

  17. 9 October 2008, European Doctorate on Fusion Science and Engineering Existing CODACs for Long Pulses (1/2) • LHD (Japan) • Based on PC cluster • Communication through TCP/IP • VXI based systems • Data Streaming (10 s slices) • Lossless data compression (ZLIB and JPEG-LS) • Two stage backup • Web interface for data analysis

  18. 9 October 2008, European Doctorate on Fusion Science and Engineering Existing CODACs for Long Pulses (2/2) • EAST (China) • Distributed data system • Communications via TCP/IP network • CAMAC and PCI based systems • Data streaming (5 s slices) • Data compression with LZO • Windows software for data analysis

  19. 9 October 2008, European Doctorate on Fusion Science and Engineering The Firesignal System • Modular client/server approach with XML plant description/ systems integration. • Standalone operation or interfaced with other CODACs. • Event-driven/Steady State Operation on absolute time. • User friendly interface with remote management and participation = control room spread over campus/web. • Easy and universal integration (Matlab, IDL, SciLab, C, Java, Python...)‏. • Modules connected through CORBA run in various OS. • Plug&Play and HotSwap of hardware

  20. 9 October 2008, European Doctorate on Fusion Science and Engineering Conclusions • Modern fusion experiments share common needs and issues regarding control and data acquisition • Technological developments in hardware and software allow us to address them efficiently • Existing CODACs have implemented with success many of these technologies • Compass provides an excellent platform for deploying and testing the ideas here presented. • It is desirable for the new CODAC to be flexible, in order to accommodate new developments

  21. 9 October 2008, European Doctorate on Fusion Science and Engineering Improvements on Firesignal

  22. 9 October 2008, European Doctorate on Fusion Science and Engineering Support Slides

  23. 9 October 2008, European Doctorate on Fusion Science and Engineering Data Compression JET’s Fast Camera. Results provided by Jesús Vega (CIEMAT/ES)‏ L.Ying, L. Jiarong, L. Guiming, Z. Yingfei, L. Shia, The EAST Distributed Data System, Fusion Eng. Des. 82 (2007) 339 - 343

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