A. Higashijima

A. Sugiyama

H. "Nakanishi

K. Ida

K. Nakamura

M. Emoto

M. Hasegawa

M. Kojima

M. Nonomura

M. Ohsuna

M. Yoshikawa

S. Imazu

T. Yamamoto

Y. Ito

Y. Nagayama

Y. Nakamura

Y." Washo

National Institute for Fusion Science (NIFS-Repository)

        The computer for the plasma control acquires various types of data such as plasma current, magnetic signals, and visible light. This also calculates various control signals such as coil currents, RF power, and piezo valves, and controls them. These acquired and control signals are not independent from each other but have a relationship with each other. Thus, the plasma control system (WS) is desirable in nature to be a centralized controls system which acquires all kinds of data and control all subsystems. However, this sometimes becomes over loaded with the WS. In actual, the WS of QUEST acquires various data and controls various subsystems with calculating plasma equilibrium and processing the plasma image using 1.73 GHz Intel Core i7-820 quad core CPU. All of these tasks use almost full CPU resource, and make it impossible to impose another control term any more.  In order to resolve these technical issues, a distributed control system is developed, which is composed of several control system and enables the implementation of more versatile controls. Each control system is connected to each other via reflective memories with optical fiber cables. The advantage is to provide the electrical isolation spontaneously. With the centralized control system, all the input and output signals are transferred via the electrical isolation amplifier to avoid mixed reference potentials. However, in the distributed system, there is no need to prepare the expensive broadband isolation amplifiers.  Figure 1 shows the current status of the CPU usage with the centralized control system. A thread L_AIO_1 enclosed with a dashed line in Fig. 1 denotes the data transfer with DMA FIFO between the control module and 4 FPGA (Field Programmable Gate Array) modules. Each FPGA module has 8 analog and 8 input channels. A thread L_AIO_2 is also the data transfer of 4 FPGA modules with 100 kHz numerical integration of magnetic signals. These threads are executed in 4 kHz (250 usec). The bars in Fig. 1 denote CPU occupation of 4 cores. The latter thread takes more time than the former because numerical integrated data have to be transferred in addition. (Notes: The numerical integration is executed on FPGA and does not put a load on CPU.) With these two threads, almost two cores are occupied, and the main thread, the equilibrium calculation thread, and the plasma image processing use other cores. Thus, almost full cores are used, and the additional other control terms cannot be imposed to the WS in the present status.  The GE cPCI-5565PIORC of National Instruments Corp. is used as the reflective memory, which has 256 Mbytes on board SDRAM and can transfer 170 Mbytes/sec according to manufacturer catalog. In many cases, the data type to share between systems may be 8 byte double precision real data. Figure 2 shows the time to read and write the reflective memory with double precision real data measured on the WS. There is no difference between read and write time, and the time have relationship of offset linear on the amount of data. Especially, data amount of 1000 to 2000 can be shared with 4 kHz which is the operating frequency of the WS, and is sufficient, though the 64 double precision real data which contain 32 magnetic signals and 32 its numeral integrated data is to share for the mean time. This transfer rate is about 50 Mbytes/sec less than 170 Mbytes/sec of catalog. This may depends on data size to share or the data types.  In future, the fundamental data such as shot number, control status, and time will be shared between systems. And, many variety control terms will be implemented with the increased available capacity by using reflective memory.  Fig. 1. Usage monitoring of control system’s Quad Core CPU.  10100100010 100 1000writereadProcessing Time (usec)Number of  variablesperiod of 4kHz Fig. 2. Time to read and write a reflective memory The LHD data acquisition and archiving system, namely “LABCOM system”, has been applied for the QUEST experiment at Kyushu University and also for the GAMMA10 at University of Tsukuba since 2008. It has been developed as the common data sharing platform for the “Fusion Virtual Laboratory (FVL)” project 1), of which remote access is constructed on the fusion-research dedicated virtual private network “SNET” 2). It is virtually set up on the Japanese academic network backbone SINET4 operated by National Institute of Informatics (NII). Fig. 1 shows the schematic structure of FVL on SNET. At the QUEST experiment, seven data acquisition (DAQ) nodes are running which are always operated and monitored remotely by NIFS LABCOM group. As for the GAMMA10 experiment, three DAQ nodes are running with the same manner and the rest of raw data acquired by legacy local systems are also transferred and registered to the LABCOM data system once a year after the end of GAMMA10 annual campaign. The whole data amount accumulated in LABCOM archive has gone up about 0.7 Peta-bytes. QUEST data occupy double of 2.6 TB between shot #1 and #25876, and GAMMA10 does double of 1.4 TB from shot #207771 to #229544, respectively. The acquired raw data amount for each shot has kept growing at QUEST since 90 MB/shot in 2008, 300 MB in 2009, 350 MB in 2010, 620–800 MB in 2011– 2012, and finally up to 1.2 GB/shot in 2013 FY. In addition, the new ‘raw2ana-quest’ service has been started since 2013 QUEST campaign, which enables the automatic data analyses synchronously triggered by the first appearance of diagnostic raw data. It can considerably help the physics analysts to be free from the human interactive data post-processing for each plasma shot. As well as other fusion experimental sites, above mentioned both labs have needed a cost reasonable isolation amplifier for a long time. Easily obtainable commercial products are usually more expensive due to the requirement mismatch for the plasma diagnostics. Due to the significant requests to develop and distribute a homemade one to the Japanese fusion community, we have been examining the optimized isolation circuit design for some years. We first challenged to apply the light energy conversion, directly to obtain the primary-side DC voltage, by using LED and solar cells. However, the output power is not enough to drive the photo coupler at the primary-side circuit. Therefore, we secondly tested an isolated DC-DC converter module, from which we could not eliminate the switching noises not suitable for analog amplifier circuit. Consequently, we finally decided to use the regulator circuit with a toroidal transformer that is expected to provide somewhat better isolation than usual EI-formed ones. Inside view of our homemade prototype of 8-channel isolation amplifiers can be seen in Fig. 2 in which a toroidal transformer and the power supply is independently installed for each channel. We have installed it on GAMMA10 experiment and verified the noise levels on the site. 1) H. Nakanishi, et al.: Fusion Eng. Des. 87 (2012) 2189. 2) T. Yamamoto, et al.: Fusion Eng. Des. 85 (2010) 637. Fig. 1 Schematic network diagram of “Fusion Virtual Laboratory” participating sites and SNET:LHD, QUEST, and GAMMA10 are equivalently connected to each other through the SNET on SINET4.Fig. 2 Front and inside photos of the new 8-channel isolation amplifier: Primary-side power supply isindependently implemented for each channel,whereas the secondary-side one is shared with acommon (chassis) ground.573§74. Progress of the Remote Data Acquisition and Sharing in “Fusion Virtual Laboratory (FVL)” Based on 10 Gbps SINET4Nakanishi, H., Ohsuna, M., Kojima, M., Ito, Y., Imazu, S., Nonomura, M., Yamamoto, T., Emoto, M., Nagayama, Y., Nakamura, Y., Ida, K.,  Hasegawa, M., Higashijima, A., Nakamura, K.  (RIAM, Kyushu Univ.),  Yoshikawa, M., Sugiyama, A., Washo, Y. (PRC, Univ. Tsukuba)

Progress of the Remote Data Acquisition and Sharing in “Fusion Virtual Laboratory (FVL)” Based on 10 Gbps SINET4

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Progress of the Remote Data Acquisition and Sharing in “Fusion Virtual Laboratory (FVL)” Based on 10 Gbps SINET4

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