S. N. Simrock, A. Aallekar, L. Abadie, L. Bertalot, M. Cheon, C

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Scientific computing for real time data processing and archiving for ITER Operation S.N. Simrock, A. Aallekar, L. Abadie, L. Bertalot, M. Cheon, C. Hansalia, G. Jablonski, D. Joonekindt, Y. Kawano , W.-D. Klotz, T. Kondoh, P. Makijarvi, D. Makowski, A. Manojkumar, V. Martin, A. Mielczarek , A. Napieralski, M. Orlikowski, M. Park, P. Perek,S. Petrov, R. Reichle, I. Semenov, D. Shelukhin, F. Tomi, V.S. Udintsev, G. Vayakis, A. Wallander, M. Walsh, A. Winter, Wu, S. Q. Yang, I. Yonekawa, K. Zagar ITER International Organization, 13108, St. Paul-lez-Durance, Cedex, France. And Domestic Agencies Representatives . 24th IAEA Fusion Energy Conference (FEC 2012) IAEA CN-97, 08 October 2012 to 13 October 2012 USA Figure-1 : PARAMETERS OF DATA SOURCES AND DATA RATES FOR ARCHIVING Introduction Data Acquisition Needs for Diagnostics ITER Instrumentation and Control Solution Figure – 2: I&C ARCHITECTURE In order to control and evaluate the plasmas produced in magnetic fusion devices it is necessary to measure the value of the key plasma parameters (density, temperature, impurities, internal magnetic fields etc.) using specially developed measurement systems termed ‘Diagnostic Systems’ Diagnostics measurement systems have stringent requirements in terms of high performance data acquisition, data processing and real-time data streaming from distributed sources to the plasma control system as well as large amounts of raw data streaming to scientific archiving. There are about 50 different parameters to be measured [1]) The technologies used range from magnetics, microwave and optical imaging systems, spectroscopy, neutron and gamma dosimetry, fusion product analyzers etc. The plant I&C systems must support the operational needs for : Machine Protection, Plasma Operation and Physics Exploitation Sampling rates : 1,10,100, and 1000 MS/s (2 GS/s are implemented using oscilloscope sampling heads ) Bit resolution : 16, 14, and 12 CameraLink or GbE will be required for optical and fusion product (spectrometers) diagnostics. Refer Figure - 1 Algorithms and Real-Time Data Processing Needs In the case of high data rates (ADC sampling rate 100-1000 MS/s or cameras) it is desirable to implement the real-time algorithms in the FPGA which controls also the data acquisition. ( Refer TABLE-III) High Data Rates e.g.: Pulse analysis, Phase reconstruction, Filtering in frequency domain, Integral transformation, Data compression, Geometry mapping, Event detection. Real Time Data Processing e.g.: Filtering, Scaling, Decimation, Fast-Fourier transform, Cross- and auto-correlation, Calibration High Data Rates Systems e.g. : Dosimetry, Microwave reflectometry, Imaging, Optical systems Criteria for estimate of the Data Rates for Archiving : • Number of signals and variables • Measurement update rate and signal sampling rate • Need for archiving of raw data, Data rates dominated by a few diagnostics • Identified dominating data sources and estimated remaining sources Figure – 3: FAST CONTROLLER FORM FACTOR Requirements for High Performance Scientific Computing Table-III: Estimation of computational needs for vis/IR image processing tasks The computational needs of some diagnostics can reach 1 Teraflop/s depending on the selected algorithms and the required accuracy (number of data points processed). Scientific archiving needs will be of the order of 2 GB/s continuous (10 GB/s on demand for 3 seconds) for first plasma and 50 GB/s continuous (300 GB/s on demand) for full physics exploitation. (Refer TABLE-I.) Data Streaming to Archiving Algorithm Function Complexity Time Constraint Image compression Data reduction ~1Gflop <1ms Maxima extraction Machine Protection 1 Mflop < 1ms Hot spot detection Plasma Control ~ 1Gflop < 100 ms Particle trajectory reconstruction Physics Studies ~100 Tflop >1h The estimate (TABLE-II)depends on the demand of raw data to be archived, the possibilities of data compression (especially important for imaging diagnostics and spectroscopy) and the duty cycle of diagnostics with very high sample rates TABLE-I: DATA MANAGEMENT REQUIREMENTS TABLE-II: REQUIREMENTS FOR DATA ARCHIVING Streaming mode Scenario-> First Plasma Physics Exploitation Continuous streaming (plasma pulse) 2 GB/sec 50 GB/sec On demand streaming(3 seconds) 10 GB/sec 300 GB/sec Solution Diagnostics Type Data Acquisition ADC / Camera Data Rate for Archiving Signal Processing complexity/reso urce Algorithms Magnetics (0.1 – 1) MS/s Moderate Moderate, FPGA, CPU Integrators, Magnetic reconstruction Neutronics 100 Ms/s Medium Medium, distributed, FPGA, CPU Pulse analysis Optical 1 GS/s High (peak) Medium, FPGA, CPU Optical Spectrometers 1 Mpixel (50 Hz) High Spectral analysis Microwave systems High, FPGA, CPU, GPU Complex filtering, Bottollier-Curtet Imaging systems 1 Mpixel (1 kHz) compression, reflection removal, event detection Figure-4: HIGH PERFORMANCE SCIENTIFIC COMPUTING ARCHITECTURE The ITER I&C standards : Plant Control Design Handbook (PCDH) [2] and Computational resources including FPGAs, GPUs and multi-core CPUs.[3] Figure – 2 provides overall ITER I&C Architecture ; Figure - 3 explains ITER solution for Real Time Data Processing needs and Data Streaming to Archiving requirements. Figure - 4 provides further detail solution for Data Streaming to Archiving Needs. Assumptions: First Plasma data are dominated by 4 cameras and raw data from ~2000 channels of raw data from magnetics Data from VIS/IR cameras can be compressed without loss / 5 [not for 1st plasma] Raw data from cameras from imaging spectroscopy is reduced by factor of ~10 Raw data from fast sampling ADCs (>100 MS/s) is available only on demand for limited time Total data from on demand archiving does not exceed data from continuous archiving Data rate between pulses is much smaller (/100) than during pulse Most data comes from few sources ( 80/20 rule) CONCLUSIONS ITER CODAC has identified commercially available standard fast controllers with different performance grades which fulfil these needs. Currently several representative diagnostics use cases are implemented to verify the choices. REFERENCES [1] Costley, A., IT/P6-21, Measurement Requirements and the Diagnostic System on ITER, IAEA 2008. [2] CODAC Plant Control Design Handbook, http://www.iter.org/org/team/chd/cid/codac/plantcontrolhandbook [3] JY. Journeaux, Instrumentation and control standardization in the ITER project, SOFT 2010 Legends 08 October -20 October 2010 Presented by S. Simrock Title: Integration of ITER Diagnostic Plant Systems with CODAC Requirements Solution