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83 results on '"Cheng, Yaodong"'

1. The Construction and Application of Data System of LHAASO Project

Author

Cao, Zhen, Yao, Zhiguo, Gu, Minhao, Cheng, Yaodong, Chinese Academy of Sciences, Ministry of Education of the PRC, Ministry of Science and Technology of the PRC, China Association for Science and Technology, Chinese Academy of Social Sciences, Chinese Academy of Engineering, National Natural Science Foundation of China, and Chinese Academy of Agricultural Sciences

Published
2024
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2. ParticleNet for Jet Tagging in Particle Physics on FPGA

Author

Zhang, Yutao, Cheng, Yaodong, Gao, Yu, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Cruz, Christophe, editor, Zhang, Yanchun, editor, and Gao, Wanling, editor

Published
2024
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4. A High-Speed Asynchronous Data I/O Method for HEPS

Author

Fu Shiyuan, Wang Lu, Cheng Yaodong, Hu Yu, Liu Rui, Wang Lei, Wang Shuang, Liu Jianli, Sun Haokai, and Qi Fazhi

Subjects
Physics, QC1-999
Abstract

The High Energy Photon Source (HEPS) is expected to produce a substantial volume of data, lead to immense data I/O pressure during computing. Inefficient data I/O can significantly impact computing performance. To address this challenge, firstly, we have developed a data I/O framework for HEPS. This framework consists of three layers: data channel layer, distributed memory management layer, and I/O interface layer. It mask the underlying data differences in formats and sources, while implementing efficient I/O methods. Additionally, it supports both stream computing and batch computing. Secondly, we have designed a data processing pipeline scheme aimed at reducing I/O latency and optimizing I/O bandwidth utilization during the processing of high-throughput data. This involves breaking down the computing task into several stages, including data loading, data pre-processing, data processing, and data writing, which are executed asynchronously and in parallel. Finally, we introduce the design of stream data I/O process. The primary objective of stream data I/O is to enable real-time online processing of raw data, avoiding I/O bottlenecks caused by disk storage. This approach ensures the stability of data transmission and integrates distributed memory management to guarantee data integrity in memory.

Published
2024
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5. XkitS：A computational storage framework for high energy physics based on EOS storage system

Author

Cheng Yaosong, Bi Yujiang, Cheng Yaodong, Li Haibo, Gao Yu, and Zhang Minxing

Subjects
Physics, QC1-999
Abstract

Large-scale high-energy physics experiments generate scientific data at the scale of petabytes or even exabytes, requiring high-performance data IO for processing. However, in large computing centers, computing and storage devices are typically separated. Large-scale data transfer has become a bottleneck for some data-intensive computing tasks, such as data encoding and decoding, compression, sorting, etc. The time spent on data transfer can account for 50% of the entire computing task. The larger the amount of data accessed, the more significant this cost becomes. One attractive solution to address this problem is to offload a portion of data processing to the storage layer. However, modifying traditional storage systems to support computation offloading is often cumbersome and requires a broad understanding of their internal principles. Therefore, we have designed a flexible software framework called XkitS, which builds a computable storage system by extending the existing storage system EOS. This framework is deployed on the EOS FTS storage server and offloads computational tasks by invoking the computing capabilities (CPU, FPGA, etc.) on FTS. Currently, it has been tested and applied in the data processing of the Large High Altitude Air Shower Observatory (LHAASO), and the results show that the time spent on data decoding using the computable storage technology is half of that using the original method.

Published
2024
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6. Using Hadoop for High Energy Physics Data Analysis

Author

Huang, Qiulan, Wei, Zhanchen, Sun, Gongxing, Cheng, Yaodong, Cheng, Zhenjing, Hu, Qingbao, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Li, Jianhui, editor, Meng, Xiaofeng, editor, Zhang, Ying, editor, Cui, Wenjuan, editor, and Du, Zhihui, editor

Published
2019
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7. Cross-Domain Data Access System for Distributed Sites in HEP

Author

Xu, Qi, Cheng, Zhenjing, Cheng, Yaodong, Chen, Gang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Li, Jianhui, editor, Meng, Xiaofeng, editor, Zhang, Ying, editor, Cui, Wenjuan, editor, and Du, Zhihui, editor

Published
2019
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8. Automated and Intelligent Data Migration Strategy in High Energy Physical Storage Systems

Author

Cheng, Zhenjing, Cheng, Yaodong, Wang, Lu, Hu, Qingbao, Li, Haibo, Xu, Qi, Chen, Gang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Li, Jianhui, editor, Meng, Xiaofeng, editor, Zhang, Ying, editor, Cui, Wenjuan, editor, and Du, Zhihui, editor

Published
2019
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9. Scientific Data Management and Application in High Energy Physics

Author

Chen, Gang, Cheng, Yaodong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Li, Jianhui, editor, Meng, Xiaofeng, editor, Zhang, Ying, editor, Cui, Wenjuan, editor, and Du, Zhihui, editor

Published
2019
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14. Porting the EOS from X86 (Intel) to aarch64 (ARM) architecture

Author

Cheng Yaosong, Bi Yujiang, Cheng Yaodong, Li Haibo, Lu Wang, and Zhang Minxing

Subjects
Physics, QC1-999
Abstract

With the advancement of many large HEP experiments, the amount of data that needs to be processed and stored has increased significantly, so we must upgrade computing resources and improve the performance of storage software. This article discusses porting the EOS software from the x86_64 architecture to the aarch64 architecture, with the aim of finding a more cost-effective storage solution. In the process of porting, the biggest challenge is that many dependent packages do not have aarch64 version and need to be compiled by ourselves, and the assembly part of the software code also needs to be adjusted accordingly. Despite these challenges, we have successfully ported the EOS code to the aarch64. This article discusses the current status and plans for the software port as well as performance testing after porting.

Published
2021
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15. Intelligent compression for synchrotron radiation source image

Author

Fu Shiyuan, Wang Lu, Cheng Yaodong, and Chen Gang

Subjects
Physics, QC1-999
Abstract

Synchrotron radiation sources (SRS) produce a huge amount of image data. This scientific data, which needs to be stored and transferred losslessly, will bring great pressure on storage and bandwidth. The SRS images have the characteristics of high frame rate and high resolution, and traditional image lossless compression methods can only save up to 30% in size. Focus on this problem, we propose a lossless compression method for SRS images based on deep learning. First, we use the difference algorithm to reduce the linear correlation within the image sequence. Then we propose a reversible truncated mapping method to reduce the range of the pixel value distribution. Thirdly, we train a deep learning model to learn the nonlinear relationship within the image sequence. Finally, we use the probability distribution predicted by the deep leaning model combined with arithmetic coding to fulfil lossless compression. Test result based on SRS images shows that our method can further decrease 20% of the data size compared to PNG, JPEG2000 and FLIF.

Published
2021
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16. Evolution of the LHAASO Distributed Computing System based Cloud

Author

Huang Qiulan, Li Haibo, Cheng Yaodong, Shi Jingyan, Zheng Wei, and Hu Qingbao

Subjects
Physics, QC1-999
Abstract

In this paper we will describe the LHAASO distributed computing system based on virtualization and cloud computing technologies. Particularly, we discuss the key points of integrating distributed resources. A solution of integrating cross-domain resources is proposed, which adopt the Openstack+HTCondor to make the distributed resources work as a whole resource pool. A flexible resource scheduling strategy and a job scheduling policy are presented to realize the resource expansion on demand and the efficient job scheduling to remote sites transparently, so as to improve the overall resource utilization. We will also introduce the deployment of the computing system located in Daocheng, the LHAASO observation base using cloud-based architecture, which greatly helps to reduce the operation and maintenance cost as well as to make sure the system availability and stability. Finally, we will show running status of the system.

Published
2020
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17. CDFS: A high-efficiency Data Access System for Storage Federations

Author

Fu Shiyuan, Xu Qi, Cheng Yaodong, and Chen Gang

Subjects
Physics, QC1-999
Abstract

High energy physics (HEP) experiments, such as LHAASO, produce a large amount of data, which is usually stored and processed on distributed sites. Nowadays, the distributed data management system faces some challenges such as global file namespace, efficient data access and storage. Focusing on those problems, this paper proposed a cross-domain data access file system (CDFS), applying data deduplication and compression as the storage-optimized engine, aiming at dynamically building an aggregate view of multiple distributed storages and accessing data in a fast and efficient way. The test based on the raw data of LHAASO experiment showed that the CDFS could present a unique repository based on distributed sites in LHAASO. And the storage-optimized engine reduces the storage consumption of the raw data by more than 50%.

Published
2020
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18. Heat Prediction of High Energy Physical Data Based on LSTM Recurrent Neural Network

Author

Cheng Zhenjing, Wang Lu, Cheng Yaodong, and Chen Gang

Subjects
Physics, QC1-999
Abstract

High-energy physics computing is a typical data-intensive calculation. Each year, petabytes of data needs to be analyzed, and data access performance is increasingly demanding. The tiered storage system scheme for building a unified namespace has been widely adopted. Generally, data is stored on storage devices with different performances and different prices according to different access frequency. When the heat of the data changes, the data is then migrated to the appropriate storage tier. At present, heuristic algorithms based on artificial experience are widely used in data heat prediction. Due to the differences in computing models of different users, the accuracy of prediction is low. A method for predicting future access popularity based on file access characteristics with the help of LSTM deep learning algorithm is proposed as the basis for data migration in hierarchical storage. This paper uses the real data of high-energy physics experiment LHAASO as an example for comparative testing. The results show that under the same test conditions, the model has higher prediction accuracy and stronger applicability than existing prediction models.

Published
2020
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19. The enhanced x-ray timing and polarimetry mission: eXTP: an update on its scientific cases, mission profile and development status

Author

Zhang, Shuang Nan, Santangelo, Andrea, Xu, Yupeng, Feroci, Marco, Hernanz, Margarita, Lu, Fangjun, Chen, Yong, Feng, Hua, Nandra, Kirpal, Jiang, Weichun, Svoboda, Jiri, Brandt, Søren, Schanne, Stéphane, Zand, Jean, Michalska, Malgorzata, Bozzo, Enrico, Kalemci, Emrah, Agudo, Ivan, Ahangarianabhari, Mahdi, Aitink-Kroes, Gabby, Ambrosi, Giovanni, Ambrosino, Filippo, An, Zhenghua, Perez Torres, Miguel Angel, Antonelli, Matias, Argan, Andrea, Babinec, Viktor, Baldini, Luca, Barbera, Marco, van Baren, Coen, Baudin, David, Bayer, Jörg, Bellazzini, Ronaldo, Bellutti, Pierluigi, Bertucci, Bruna, Bertuccio, Giuseppe, Bi, Xingzi, Boezio, Mirko, Bonvicini, Valter, Bonvicini, Walter, Bordas, Pol, Borghese, Alice, Borghi, Giacomo, Bouyjou, Florent, Bozkurt, Ayhan, Brez, Alessandro, Brienza, Daniele, Cadoux, Franck, Campana, Riccardo, Cao, Jiewei, Cao, Xuelei, Casares, Jorge, Cavazzuti, Elisabetta, Ceraudo, Francesco, Chen, Tianxiang, Chen, Wen, Chen, Can, Chen, Yupeng, Chen, Xin, Chen, Yehai, Chenevez, Jerome, Cheng, Yaodong, Cirrincione, Daniela, Civitani, Marta, Cong, Min, Zelati, Francesco Coti, Cui, Weiwei, Cui, Tao, Cui, Wei, Dai, Boyu, Dauser, Thomas, De Angelis, Nicolas, De Marco, Barbara, De Rosa, Alessandra, Monte, Ettore Del, Cosimo, Sergio Di, Diebold, Sebastian, Dilillo, Giuseppe, Ding, Fei, Dohnal, Roman, Dong, Zefang, Donnarumma, Immacolata, Dovciak, Michal, Du, Yuanyuan, Ducci, Lorenzo, Evangelista, Yuri, Fan, Qingmei, Favre, Yannick, Ferrés, Patrícia, Fiandrini, Emanuele, Ficorella, Francesco, Fuschino, Fabio, Gálvez, José Luis, Gao, Na, Gao, Min, Ge, Yuqiang, Ge, Mingyu, Gevin, Olivier, Grassi, Marco, Gu, Yudong, Gu, Quanying, Guan, Ju, Guedel, Manuel, Han, Xingbo, Han, Dawei, He, Huilin, He, Junwang, Hedderman, Paul, den Herder, Jan Willem, Hong, Bin, Hormaetxe, Ander, Hou, Dongjie, Hu, Zexun, Hu, Hao, Hu, Qingbao, Hu, Yu, Huang, Yue, Huang, Jiangjiang, Huang, Qiushi, Huo, Jia, Hynek, Richard, Iwasawa, Kazumi, Izzo, Lucca, Ji, Long, Jia, Shumei, Jiang, Bowen, Jiang, Wei, Jiang, Jiechen, Jiang, Xiaowei, Jiao, Yang, Jin, Ge, Jin, Fan, Jose, Jordi, Karas, Vladimir, Kennedy, Thomas, Kirsch, Christian, Kole, Merlin, Komarek, Martin, Kreykenbohm, Ingo, Kuiper, Lucien, Kuvvetli, Irfan, Labanti, Claudio, Latronico, Luca, Laubert, Phillip, Li, Tao, Li, Longhui, Li, Hong, Li, Duo, Li, Wei, Li, Maoshun, Li, Gang, Li, Xiaobo, Li, Chengkui, Li, Bing, Li, Haibo, Liang, Hong, Liao, Qiuyan, Liao, Jinyuan, Limousin, Olivier, Lin, Yanjian, Linares, Manuel, Liu, Rui, Liu, Yichen, Liu, Zhihao, Liu, Hongwei, Liu, Xiaojing, Liu, Xiaohua, Cicero, Ugo Lo, Loehring, Jens, Lombardi, Giovanni, Lorenz, Maximilian, Lu, Bing, Lucchesi, Leonardo, Luo, Tao, Luo, Laidan, Ma, Jia, Ma, Xiang, Macera, Daniele, Malcovati, Piero, Manfreda, Alberto, Paredes, Josep Maria, Marinucci, Andrea, Martindale, Adrian, Meidinger, Norbert, Mele, Filippo, Mendes, Vasco, Meng, Bin, Merkl, Martin, Meuris, Aline, Miniutti, Giovanni, Minuti, Massimo, Morbidini, Alfredo, Morgante, Gianluca, Muleri, Fabio, Munini, Riccardo, Mussolin, Lorenzo, Negri, Barbara, Nie, Jianyin, Novák, Petr, Nowosielski, Witold, Nuti, Alessio, Onat, Ahmet, Orleanski, Piotr, Orsini, Leonardo, Ottensamer, Roland, Ou, Ge, Pacciani, Luigi, Paltani, Stephane, Pan, Teng, Pan, Kai, Pareschi, Giovanni, Patruno, Alessandro, Pepponi, Giancarlo, Perinati, Emanuele, Piazzolla, Raffaele, Picciotto, Antonino, Piemonte, Claudio, Pinchera, Michele, Pliego, Samuel, Poutanen, Juri, Qi, Liqiang, Qi, Fazhi, Qiang, Pengfei, Qiao, Fangjian, Qiao, Zheng, Qiu, Xiangbiao, Qiu, Chengbo, Qu, Jinlu, Rachevski, Alexandre, Rashevskaia, Irina, Rea, Nanda, Ribo, Marc, de la Rie, Rob, Rodriguez, Jerome, Gil, Pablo Rodríguez, Sala, Gloria, Schanz, Thomas, Serafinelli, Roberto, Sgro, Carmelo, Shen, Zhengxiang, Sheng, Lizhi, Shi, Jingyan, Sironi, Giorgia, Skup, Konrad, Song, Liming, Song, Zeyu, Song, Jiangbo, Spandre, Gloria, Spiga, Daniele, Su, Yongquan, Sun, Liang, Sungur, Müberra, Svéda, Libor, Tagliaferri, Gianpiero, Tan, Ying, Tao, Lian, Tcherniak, Denis, Tenzer, Chris, Todaro, Michela, Tolos, Laura, Torok, Gabriel, Torres, Diego F., Trois, Alessio, Turhan, Onur, Uttley, Phil, Vacchi, Andrea, Virgilli, Enrico, Vogel, Channah, Walton, Dave, Wang, Jian, Wang, Xianqi, Wang, Bo, Wang, Langping, Wang, Xiaofeng, Wang, Dianlong, Wang, Yusa, Wang, Juan, Wang, Hao, Wang, Ruijie, Wang, Ping, Wang, Lingjun, Wang, Wenshuai, Wang, Tian, Wang, Haoyu, Wang, Zhanshan, Watts, Anna L., Wen, Xiangyang, Wilms, Jörn, Winter, Berend, Wu, Xin, Wu, Chao, Wu, Zhenyu, Wu, Qiong, Wu, Kaiji, Xiong, Hao, Xiong, Shaolin, Xu, Wei, Xu, Zhao, Xu, Jingjing, Xu, Xiongwei, Xue, Jiadai, Yan, Yongqing, Yan, Xingtao, Yang, Xianghui, Yang, Yanji, Yang, Xiongtao, Yang, Sheng, Yang, Jiawei, Yang, Yingquan, Yi, Shuxu, Yu, Yonggao, Yu, Ke, Zampa, Ganluigi, Zampa, Nicola, Zane, Silvia, Zdziarski, Andrzej A., Zhang, Long, Zhang, Shu, Zhang, Wenda, Zhang, Xiaoli, Zhang, Zhen, Zhang, Jiawei, Zhang, Fan, Zhang, Ziliang, Zhang, Dali, Zhang, Honglin, Zhang, Aimei, Zhang, Tong, Zhang, Hongmei, Zhang, Juan, Zhang, Liang, Zhang, Yueting, Zhao, Li, Zhao, Baosheng, Zhao, Zijian, Zhao, Xiaofan, Zhao, Haisheng, Zhao, Xiaoyun, Zheng, Shijie, Zhou, Yupeng, Zhou, Xiaohong, Zhu, Jiahuan, Zhu, Yuxuan, Zhu, Cheng, Zhu, Zhencai, Zorzi, Nicola, Zwart, Frans, den Herder, Jan-Willem A., Nikzad, Shouleh, Nakazawa, Kazuhiro, Chinese Academy of Sciences, Agenzia Spaziale Italiana, Ministerio de Ciencia e Innovación (España), Federal Ministry of Economics and Technology (Germany), and Foundation for Polish Science

Subjects
Equation of state, Extreme gravity, Black hole, X-ray timing, X-ray polarimetry, Neutron star, Extreme magnetism, Extreme density
Abstract

Space Telescopes and Instrumentation 2022: Ultraviolet to Gamma Ray (2022), Montreal, Jul 17-22, 2022.--Proceedings of SPIE - The International Society for Optical Engineering vol. 12181 Article number 121811W.-- Full list of authors: Zhang, Shuang-Nan; Santangelo, Andrea; Xu, Yupeng; Feroci, Marco; Hernanz, Margarita; Lu, Fangjun; Chen, Yong; Feng, Hua; Nandra, Kirpal; Jiang, Weichun; Svoboda, Jiri; Brandt, Soren; Schanne, Stephane; in't Zand, Jean; Michalska, Malgorzata; Bozzo, Enrico; Kalemci, Emrah; Agudo, Ivan; Ahangarianabhari, Mahdi; Aitink-Kroes, Gabby; Ambrosi, Giovanni; Ambrosino, Filippo; An, Zhenghua; Perez Torres, Miguel Angel; Antonelli, Matias; Argan, Andrea; Babinec, Viktor; Baldini, Luca; Barbera, Marco; van Baren, Coen; Baudin, David; Bayer, Joerg; Bellazzini, Ronaldo; Bellutti, Pierluigi; Bertucci, Bruna; Bertuccio, Giuseppe; Bi, Xingzi; Boezio, Mirko; Bonvicini, Valter; Bonvicini, Walter; Bordas, Pol; Borghese, Alice; Borghi, Giacomo; Bouyjou, Florent; Bozkurt, Ayhan; Brez, Alessandro; Brienza, Daniele; Cadoux, Franck; Campana, Riccardo; Cao, Jiewei; Cao, Xuelei; Casares, Jorge; Cavazzuti, Elisabetta; Ceraudo, Francesco; Chen, Tianxiang; Chen, Wen; Chen, Can; Chen, Yupeng; Chen, Xin; Chen, Yehai; Chenevez, Jerome; Cheng, Yaodong; Cirrincione, Daniela; Civitani, Marta; Cong, Min; Coti Zelati, Francesco; Cui, Weiwei; Cui, Tao; Cui, Wei; Dai, Boyu; Dauser, Thomas; De Angelis, Nicolas; De Marco, Barbara; De Rosa, Alessandra; Del Monte, Ettore; Di Cosimo, Sergio; Diebold, Sebastian; Dilillo, Giuseppe; Ding, Fei; Dohnal, Roman; Dong, Zefang; Donnarumma, Immacolata; Dovciak, Michal; Du, Yuanyuan; Ducci, Lorenzo; Evangelista, Yuri; Fan, Qingmei; Favre, Yannick; Ferres, Patricia; Fiandrini, Emanuele; Ficorella, Francesco; Fuschino, Fabio; Luis Galvez, Jose; Gao, Na; Gao, Min; Ge, Yuqiang; Ge, Mingyu; Gevin, Olivier; Grassi, Marco; Gu, Yudong; Gu, Quanying; Guan, Ju; Guedel, Manuel; Han, Xingbo; Han, Dawei; He, Huilin; He, Junwang; Hedderman, Paul; den Herder, Jan-Willem; Hong, Bin; Hormaetxe, Ander; Hou, Dongjie; Hu, Zexun; Hu, Hao; Hu, Qingbao; Hu, Yu; Huang, Yue; Huang, Jiangjiang; Huang, Qiushi; Huo, Jia; Hynek, Richard; Iwasawa, Kazumi; Izzo, Lucca; Ji, Long; Jia, Shumei; Jiang, Bowen; Jiang, Wei; Jiang, Jiechen; Jiang, Xiaowei; Jiao, Yang; Jin, Ge; Jin, Fan; Jose, Jordi; Karas, Vladimir; Kennedy, Thomas; Kirsch, Christian; Kole, Merlin; Komarek, Martin; Kreykenbohm, Ingo; Kuiper, Lucien; Kuvvetli, Irfan; Labanti, Claudio; Latronico, Luca; Laubert, Phillip; Li, Tao; Li, Longhui; Li, Hong; Li, Duo; Li, Wei; Li, Maoshun; Li, Gang; Li, Xiaobo; Li, Chengkui; Li, Bing; Li, Haibo; Liang, Hong; Liao, Qiuyan; Liao, Jinyuan; Limousin, Olivier; Lin, Yanjian; Linares, Manuel; Liu, Rui; Liu, Yichen; Liu, Zhihao; Liu, Hongwei; Liu, Xiaojing; Liu, Xiaohua; Lo Cicero, Ugo; Loehring, Jens; Lombardi, Giovanni; Lorenz, Maximilian; Lu, Bing; Lucchesi, Leonardo; Luo, Tao; Luo, Laidan; Ma, Jia; Ma, Xiang; Macera, Daniele; Malcovati, Piero; Manfreda, Alberto; Maria Paredes, Josep; Marinucci, Andrea; Martindale, Adrian; Meidinger, Norbert; Mele, Filippo; Mendes, Vasco; Meng, Bin; Merkl, Martin; Meuris, Aline; Miniutti, Giovanni; Minuti, Massimo; Morbidini, Alfredo; Morgante, Gianluca; Muleri, Fabio; Munini, Riccardo; Mussolin, Lorenzo; Negri, Barbara; Nie, Jianyin; Novak, Petr; Nowosielski, Witold; Nuti, Alessio; Onat, Ahmet; Orleanski, Piotr; Orsini, Leonardo; Ottensamer, Roland; Ou, Ge; Pacciani, Luigi; Paltani, Stephane; Pan, Teng; Pan, Kai; Pareschi, Giovanni; Patruno, Alessandro; Pepponi, Giancarlo; Perinati, Emanuele; Piazzolla, Raffaele; Picciotto, Antonino; Piemonte, Claudio; Pinchera, Michele; Pliego, Samuel; Poutanen, Juri; Qi, Liqiang; Qi, Fazhi; Qiang, Pengfei; Qiao, Fangjian; Qiao, Zheng; Qiu, Xiangbiao; Qiu, Chengbo; Qu, Jinlu; Rachevski, Alexandre; Rashevskaia, Irina; Rea, Nanda; Ribo, Marc; de la Rie, Rob; Rodriguez, Jerome; Rodriguez Gil, Pablo; Sala, Gloria; Schanz, Thomas; Serafinelli, Roberto; Sgro, Carmelo; Shen, Zhengxiang; Sheng, Lizhi; Shi, Jingyan; Sironi, Giorgia; Skup, Konrad; Song, Liming; Song, Zeyu; Song, Jiangbo; Spandre, Gloria; Spiga, Daniele; Su, Yongquan; Sun, Liang; Sungur, Muberra; Sveda, Libor; Tagliaferri, Gianpiero; Tan, Ying; Tao, Lian; Tcherniak, Denis; Tenzer, Chris; Todaro, Michela; Tolos, Laura; Torok, Gabriel; Torres, Diego F.; Trois, Alessio; Turhan, Onur; Uttley, Phil; Vacchi, Andrea; Virgilli, Enrico; Vogel, Channah; Walton, Dave; Wang, Jian; Wang, Xianqi; Wang, Bo; Wang, Langping; Wang, Xiaofeng; Wang, Dianlong; Wang, Yusa; Wang, Juan; Wang, Hao; Wang, Ruijie; Wang, Ping; Wang, Lingjun; Wang, Wenshuai; Wang, Tian; Wang, Haoyu; Wang, Zhanshan; Watts, Anna L.; Wen, Xiangyang; Wilms, Joern; Winter, Berend; Wu, Xin; Wu, Chao; Wu, Zhenyu; Wu, Qiong; Wu, Kaiji; Xiong, Hao; Xiong, Shaolin; Xu, Wei; Xu, Zhao; Xu, Jingjing; Xu, Xiongwei; Xue, Jiadai; Yan, Yongqing; Yan, Xingtao; Yang, Xianghui; Yang, Yanji; Yang, Xiongtao; Yang, Sheng; Yang, Jiawei; Yang, Yingquan; Yi, Shuxu; Yu, Yonggao; Yu, Ke; Zampa, Ganluigi; Zampa, Nicola; Zane, Silvia; Zdziarski, Andrzej A.; Zhang, Long; Zhang, Shu; Zhang, Wenda; Zhang, Xiaoli; Zhang, Zhen; Zhang, Jiawei; Zhang, Fan; Zhang, Ziliang; Zhang, Dali; Zhang, Honglin; Zhang, Aimei; Zhang, Tong; Zhang, Hongmei; Zhang, Juan; Zhang, Liang; Zhang, Yueting; Zhao, Li; Zhao, Baosheng; Zhao, Zijian; Zhao, Xiaofan; Zhao, Haisheng; Zhao, Xiaoyun; Zheng, Shijie; Zhou, Yupeng; Zhou, Xiaohong; Zhu, Jiahuan; Zhu, Yuxuan; Zhu, Cheng; Zhu, Zhencai; Zorzi, Nicola; Zwart, Frans, The enhanced X-ray Timing and Polarimetry mission (eXTP) is a flagship observatory for X-ray timing, spectroscopy and polarimetry developed by an International Consortium. Thanks to its very large collecting area, good spectral resolution and unprecedented polarimetry capabilities, eXTP will explore the properties of matter and the propagation of light in the most extreme conditions found in the Universe. eXTP will, in addition, be a powerful X-ray observatory. The mission will continuously monitor the X-ray sky, and will enable multiwavelength and multi-messenger studies. The mission is currently in phase B, which will be completed in the middle of 2022. © 2022 SPIE. All rights reserved., The Chinese team acknowledges support by the Chinese Academy of Sciences through the Strategic Priority Research Program, Grant No. XDA15020100. The Italian authors acknowledge funding support by the Italian Space Agency (under agreement n. 2020-3-HH.0 and ASI-INAF n.2017-14-H.O) and INFN (project XRO -X-ray Observatories). The Spanish authors acknowledge funding support from the MICIN/AEI grant PID2019-108709GB-I00. The German team acknowledges support from the Bundesministerium fur Wirtschaft und Technologie through the Deutsches Zentrum fur Luft-und Raumfahrt e.V. (DLR) under the grant number FKZ 50 OO 1902. The Polish team acknowledges FNP grant POIR.04.04.00-00-5C65/17. The Czech team acknowledges support from the GACR project 21-06825X. The Turkish team acknowledges support from the Turkish Space Agency., With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709

Published
2022
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22. EventDB: an event-based indexer and caching system for BESIII experiment

Author

Cheng Yaodong, Li Haibo, Xu Qi, Cheng Zhenjing, and Huang Qiulan

Subjects
Physics, QC1-999
Abstract

Beijing Spectrometer (BESIII) experiment has produced hundreds of billions of events. The traditional event-wise accessing of BESIII Offline Software System is not effective for the selective accessing with low rate during a physics analysis. In this paper, an event-based data management system (EventDB) is introduced, which can effectively alleviate the problems of low efficiency of data processing and low utilization of resources. Firstly, an indexing system based on NoSQL database is designed. By extracting specified attributes of events, the events interested to the physicists are selected and stored into the database, whilst the real data of event is still stored in ROOT files. For those hot events, the real event data can also be cached into EventDB to improve the access performance. The data analysis workflow of HEP experiments is needed to change if the EventDB system is applied. The analysis program queries the corresponding event index from database, then get event data from database if the event is cached, or get data from ROOT files if it is not cached. Finally, the test on more than one hundred billion physics events shows the query speed was greatly improved over traditional file-based data management systems.

Published
2019
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23. The enhanced X-ray Timing and Polarimetry mission – eXTP:an update on its scientific cases, mission profile and development status

Author

den Herder, Jan-Willem A., Nikzad, Shouleh, Nakazawa, Kazuhiro, Zhang, Shuang Nan, Santangelo, Andrea, Xu, Yupeng, Feroci, Marco, Hernanz, Margarita, Lu, Fangjun, Chen, Yong, Feng, Hua, Nandra, Kirpal, Jiang, Weichun, Svoboda, Jiri, Brandt, Søren, Schanne, Stéphane, Zand, Jean, Michalska, Malgorzata, Bozzo, Enrico, Kalemci, Emrah, Agudo, Ivan, Ahangarianabhari, Mahdi, Aitink-Kroes, Gabby, Ambrosi, Giovanni, Ambrosino, Filippo, An, Zhenghua, Perez Torres, Miguel Angel, Antonelli, Matias, Argan, Andrea, Babinec, Viktor, Baldini, Luca, Barbera, Marco, van Baren, Coen, Baudin, David, Bayer, Jörg, Bellazzini, Ronaldo, Bellutti, Pierluigi, Bertucci, Bruna, Bertuccio, Giuseppe, Bi, Xingzi, Boezio, Mirko, Bonvicini, Valter, Bonvicini, Walter, Bordas, Pol, Borghese, Alice, Borghi, Giacomo, Bouyjou, Florent, Bozkurt, Ayhan, Brez, Alessandro, Brienza, Daniele, Cadoux, Franck, Campana, Riccardo, Cao, Jiewei, Cao, Xuelei, Casares, Jorge, Cavazzuti, Elisabetta, Ceraudo, Francesco, Chen, Tianxiang, Chen, Wen, Chen, Can, Chen, Yupeng, Chen, Xin, Chen, Yehai, Chenevez, Jerome, Cheng, Yaodong, Cirrincione, Daniela, Civitani, Marta, Cong, Min, Zelati, Francesco Coti, Cui, Weiwei, Cui, Tao, Cui, Wei, Dai, Boyu, Dauser, Thomas, De Angelis, Nicolas, De Marco, Barbara, De Rosa, Alessandra, Monte, Ettore Del, Cosimo, Sergio Di, Diebold, Sebastian, Dilillo, Giuseppe, Ding, Fei, Dohnal, Roman, Dong, Zefang, Donnarumma, Immacolata, Dovciak, Michal, Du, Yuanyuan, Ducci, Lorenzo, Evangelista, Yuri, Fan, Qingmei, Favre, Yannick, Ferrés, Patrícia, Fiandrini, Emanuele, Ficorella, Francesco, Fuschino, Fabio, Gálvez, José Luis, Gao, Na, Gao, Min, Ge, Yuqiang, Ge, Mingyu, Gevin, Olivier, Grassi, Marco, Gu, Yudong, Gu, Quanying, Guan, Ju, Guedel, Manuel, Han, Xingbo, Han, Dawei, He, Huilin, He, Junwang, Hedderman, Paul, den Herder, Jan Willem, Hong, Bin, Hormaetxe, Ander, Hou, Dongjie, Hu, Zexun, Hu, Hao, Hu, Qingbao, Hu, Yu, Huang, Yue, Huang, Jiangjiang, Huang, Qiushi, Huo, Jia, Hynek, Richard, Iwasawa, Kazumi, Izzo, Lucca, Ji, Long, Jia, Shumei, Jiang, Bowen, Jiang, Wei, Jiang, Jiechen, Jiang, Xiaowei, Jiao, Yang, Jin, Ge, Jin, Fan, Jose, Jordi, Karas, Vladimir, Kennedy, Thomas, Kirsch, Christian, Kole, Merlin, Komarek, Martin, Kreykenbohm, Ingo, Kuiper, Lucien, Kuvvetli, Irfan, Labanti, Claudio, Latronico, Luca, Laubert, Phillip, Li, Tao, Li, Longhui, Li, Hong, Li, Duo, Li, Wei, Li, Maoshun, Li, Gang, Li, Xiaobo, Li, Chengkui, Li, Bing, Li, Haibo, Liang, Hong, Liao, Qiuyan, Liao, Jinyuan, Limousin, Olivier, Lin, Yanjian, Linares, Manuel, Liu, Rui, Liu, Yichen, Liu, Zhihao, Liu, Hongwei, Liu, Xiaojing, Liu, Xiaohua, Cicero, Ugo Lo, Loehring, Jens, Lombardi, Giovanni, Lorenz, Maximilian, Lu, Bing, Lucchesi, Leonardo, Luo, Tao, Luo, Laidan, Ma, Jia, Ma, Xiang, Macera, Daniele, Malcovati, Piero, Manfreda, Alberto, Paredes, Josep Maria, Marinucci, Andrea, Martindale, Adrian, Meidinger, Norbert, Mele, Filippo, Mendes, Vasco, Meng, Bin, Merkl, Martin, Meuris, Aline, Miniutti, Giovanni, Minuti, Massimo, Morbidini, Alfredo, Morgante, Gianluca, Muleri, Fabio, Munini, Riccardo, Mussolin, Lorenzo, Negri, Barbara, Nie, Jianyin, Novák, Petr, Nowosielski, Witold, Nuti, Alessio, Onat, Ahmet, Orleanski, Piotr, Orsini, Leonardo, Ottensamer, Roland, Ou, Ge, Pacciani, Luigi, Paltani, Stephane, Pan, Teng, Pan, Kai, Pareschi, Giovanni, Patruno, Alessandro, Pepponi, Giancarlo, Perinati, Emanuele, Piazzolla, Raffaele, Picciotto, Antonino, Piemonte, Claudio, Pinchera, Michele, Pliego, Samuel, Poutanen, Juri, Qi, Liqiang, Qi, Fazhi, Qiang, Pengfei, Qiao, Fangjian, Qiao, Zheng, Qiu, Xiangbiao, Qiu, Chengbo, Qu, Jinlu, Rachevski, Alexandre, Rashevskaia, Irina, Rea, Nanda, Ribo, Marc, de la Rie, Rob, Rodriguez, Jerome, Gil, Pablo Rodríguez, Sala, Gloria, Schanz, Thomas, Serafinelli, Roberto, Sgro, Carmelo, Shen, Zhengxiang, Sheng, Lizhi, Shi, Jingyan, Sironi, Giorgia, Skup, Konrad, Song, Liming, Song, Zeyu, Song, Jiangbo, Spandre, Gloria, Spiga, Daniele, Su, Yongquan, Sun, Liang, Sungur, Müberra, Svéda, Libor, Tagliaferri, Gianpiero, Tan, Ying, Tao, Lian, Tcherniak, Denis, Tenzer, Chris, Todaro, Michela, Tolos, Laura, Torok, Gabriel, Torres, Diego F., Trois, Alessio, Turhan, Onur, Uttley, Phil, Vacchi, Andrea, Virgilli, Enrico, Vogel, Channah, Walton, Dave, Wang, Jian, Wang, Xianqi, Wang, Bo, Wang, Langping, Wang, Xiaofeng, Wang, Dianlong, Wang, Yusa, Wang, Juan, Wang, Hao, Wang, Ruijie, Wang, Ping, Wang, Lingjun, Wang, Wenshuai, Wang, Tian, Wang, Haoyu, Wang, Zhanshan, Watts, Anna L., Wen, Xiangyang, Wilms, Jörn, Winter, Berend, Wu, Xin, Wu, Chao, Wu, Zhenyu, Wu, Qiong, Wu, Kaiji, Xiong, Hao, Xiong, Shaolin, Xu, Wei, Xu, Zhao, Xu, Jingjing, Xu, Xiongwei, Xue, Jiadai, Yan, Yongqing, Yan, Xingtao, Yang, Xianghui, Yang, Yanji, Yang, Xiongtao, Yang, Sheng, Yang, Jiawei, Yang, Yingquan, Yi, Shuxu, Yu, Yonggao, Yu, Ke, Zampa, Ganluigi, Zampa, Nicola, Zane, Silvia, Zdziarski, Andrzej A., Zhang, Long, Zhang, Shu, Zhang, Wenda, Zhang, Xiaoli, Zhang, Zhen, Zhang, Jiawei, Zhang, Fan, Zhang, Ziliang, Zhang, Dali, Zhang, Honglin, Zhang, Aimei, Zhang, Tong, Zhang, Hongmei, Zhang, Juan, Zhang, Liang, Zhang, Yueting, Zhao, Li, Zhao, Baosheng, Zhao, Zijian, Zhao, Xiaofan, Zhao, Haisheng, Zhao, Xiaoyun, Zheng, Shijie, Zhou, Yupeng, Zhou, Xiaohong, Zhu, Jiahuan, Zhu, Yuxuan, Zhu, Cheng, Zhu, Zhencai, Zorzi, Nicola, Zwart, Frans, den Herder, Jan-Willem A., Nikzad, Shouleh, Nakazawa, Kazuhiro, Zhang, Shuang Nan, Santangelo, Andrea, Xu, Yupeng, Feroci, Marco, Hernanz, Margarita, Lu, Fangjun, Chen, Yong, Feng, Hua, Nandra, Kirpal, Jiang, Weichun, Svoboda, Jiri, Brandt, Søren, Schanne, Stéphane, Zand, Jean, Michalska, Malgorzata, Bozzo, Enrico, Kalemci, Emrah, Agudo, Ivan, Ahangarianabhari, Mahdi, Aitink-Kroes, Gabby, Ambrosi, Giovanni, Ambrosino, Filippo, An, Zhenghua, Perez Torres, Miguel Angel, Antonelli, Matias, Argan, Andrea, Babinec, Viktor, Baldini, Luca, Barbera, Marco, van Baren, Coen, Baudin, David, Bayer, Jörg, Bellazzini, Ronaldo, Bellutti, Pierluigi, Bertucci, Bruna, Bertuccio, Giuseppe, Bi, Xingzi, Boezio, Mirko, Bonvicini, Valter, Bonvicini, Walter, Bordas, Pol, Borghese, Alice, Borghi, Giacomo, Bouyjou, Florent, Bozkurt, Ayhan, Brez, Alessandro, Brienza, Daniele, Cadoux, Franck, Campana, Riccardo, Cao, Jiewei, Cao, Xuelei, Casares, Jorge, Cavazzuti, Elisabetta, Ceraudo, Francesco, Chen, Tianxiang, Chen, Wen, Chen, Can, Chen, Yupeng, Chen, Xin, Chen, Yehai, Chenevez, Jerome, Cheng, Yaodong, Cirrincione, Daniela, Civitani, Marta, Cong, Min, Zelati, Francesco Coti, Cui, Weiwei, Cui, Tao, Cui, Wei, Dai, Boyu, Dauser, Thomas, De Angelis, Nicolas, De Marco, Barbara, De Rosa, Alessandra, Monte, Ettore Del, Cosimo, Sergio Di, Diebold, Sebastian, Dilillo, Giuseppe, Ding, Fei, Dohnal, Roman, Dong, Zefang, Donnarumma, Immacolata, Dovciak, Michal, Du, Yuanyuan, Ducci, Lorenzo, Evangelista, Yuri, Fan, Qingmei, Favre, Yannick, Ferrés, Patrícia, Fiandrini, Emanuele, Ficorella, Francesco, Fuschino, Fabio, Gálvez, José Luis, Gao, Na, Gao, Min, Ge, Yuqiang, Ge, Mingyu, Gevin, Olivier, Grassi, Marco, Gu, Yudong, Gu, Quanying, Guan, Ju, Guedel, Manuel, Han, Xingbo, Han, Dawei, He, Huilin, He, Junwang, Hedderman, Paul, den Herder, Jan Willem, Hong, Bin, Hormaetxe, Ander, Hou, Dongjie, Hu, Zexun, Hu, Hao, Hu, Qingbao, Hu, Yu, Huang, Yue, Huang, Jiangjiang, Huang, Qiushi, Huo, Jia, Hynek, Richard, Iwasawa, Kazumi, Izzo, Lucca, Ji, Long, Jia, Shumei, Jiang, Bowen, Jiang, Wei, Jiang, Jiechen, Jiang, Xiaowei, Jiao, Yang, Jin, Ge, Jin, Fan, Jose, Jordi, Karas, Vladimir, Kennedy, Thomas, Kirsch, Christian, Kole, Merlin, Komarek, Martin, Kreykenbohm, Ingo, Kuiper, Lucien, Kuvvetli, Irfan, Labanti, Claudio, Latronico, Luca, Laubert, Phillip, Li, Tao, Li, Longhui, Li, Hong, Li, Duo, Li, Wei, Li, Maoshun, Li, Gang, Li, Xiaobo, Li, Chengkui, Li, Bing, Li, Haibo, Liang, Hong, Liao, Qiuyan, Liao, Jinyuan, Limousin, Olivier, Lin, Yanjian, Linares, Manuel, Liu, Rui, Liu, Yichen, Liu, Zhihao, Liu, Hongwei, Liu, Xiaojing, Liu, Xiaohua, Cicero, Ugo Lo, Loehring, Jens, Lombardi, Giovanni, Lorenz, Maximilian, Lu, Bing, Lucchesi, Leonardo, Luo, Tao, Luo, Laidan, Ma, Jia, Ma, Xiang, Macera, Daniele, Malcovati, Piero, Manfreda, Alberto, Paredes, Josep Maria, Marinucci, Andrea, Martindale, Adrian, Meidinger, Norbert, Mele, Filippo, Mendes, Vasco, Meng, Bin, Merkl, Martin, Meuris, Aline, Miniutti, Giovanni, Minuti, Massimo, Morbidini, Alfredo, Morgante, Gianluca, Muleri, Fabio, Munini, Riccardo, Mussolin, Lorenzo, Negri, Barbara, Nie, Jianyin, Novák, Petr, Nowosielski, Witold, Nuti, Alessio, Onat, Ahmet, Orleanski, Piotr, Orsini, Leonardo, Ottensamer, Roland, Ou, Ge, Pacciani, Luigi, Paltani, Stephane, Pan, Teng, Pan, Kai, Pareschi, Giovanni, Patruno, Alessandro, Pepponi, Giancarlo, Perinati, Emanuele, Piazzolla, Raffaele, Picciotto, Antonino, Piemonte, Claudio, Pinchera, Michele, Pliego, Samuel, Poutanen, Juri, Qi, Liqiang, Qi, Fazhi, Qiang, Pengfei, Qiao, Fangjian, Qiao, Zheng, Qiu, Xiangbiao, Qiu, Chengbo, Qu, Jinlu, Rachevski, Alexandre, Rashevskaia, Irina, Rea, Nanda, Ribo, Marc, de la Rie, Rob, Rodriguez, Jerome, Gil, Pablo Rodríguez, Sala, Gloria, Schanz, Thomas, Serafinelli, Roberto, Sgro, Carmelo, Shen, Zhengxiang, Sheng, Lizhi, Shi, Jingyan, Sironi, Giorgia, Skup, Konrad, Song, Liming, Song, Zeyu, Song, Jiangbo, Spandre, Gloria, Spiga, Daniele, Su, Yongquan, Sun, Liang, Sungur, Müberra, Svéda, Libor, Tagliaferri, Gianpiero, Tan, Ying, Tao, Lian, Tcherniak, Denis, Tenzer, Chris, Todaro, Michela, Tolos, Laura, Torok, Gabriel, Torres, Diego F., Trois, Alessio, Turhan, Onur, Uttley, Phil, Vacchi, Andrea, Virgilli, Enrico, Vogel, Channah, Walton, Dave, Wang, Jian, Wang, Xianqi, Wang, Bo, Wang, Langping, Wang, Xiaofeng, Wang, Dianlong, Wang, Yusa, Wang, Juan, Wang, Hao, Wang, Ruijie, Wang, Ping, Wang, Lingjun, Wang, Wenshuai, Wang, Tian, Wang, Haoyu, Wang, Zhanshan, Watts, Anna L., Wen, Xiangyang, Wilms, Jörn, Winter, Berend, Wu, Xin, Wu, Chao, Wu, Zhenyu, Wu, Qiong, Wu, Kaiji, Xiong, Hao, Xiong, Shaolin, Xu, Wei, Xu, Zhao, Xu, Jingjing, Xu, Xiongwei, Xue, Jiadai, Yan, Yongqing, Yan, Xingtao, Yang, Xianghui, Yang, Yanji, Yang, Xiongtao, Yang, Sheng, Yang, Jiawei, Yang, Yingquan, Yi, Shuxu, Yu, Yonggao, Yu, Ke, Zampa, Ganluigi, Zampa, Nicola, Zane, Silvia, Zdziarski, Andrzej A., Zhang, Long, Zhang, Shu, Zhang, Wenda, Zhang, Xiaoli, Zhang, Zhen, Zhang, Jiawei, Zhang, Fan, Zhang, Ziliang, Zhang, Dali, Zhang, Honglin, Zhang, Aimei, Zhang, Tong, Zhang, Hongmei, Zhang, Juan, Zhang, Liang, Zhang, Yueting, Zhao, Li, Zhao, Baosheng, Zhao, Zijian, Zhao, Xiaofan, Zhao, Haisheng, Zhao, Xiaoyun, Zheng, Shijie, Zhou, Yupeng, Zhou, Xiaohong, Zhu, Jiahuan, Zhu, Yuxuan, Zhu, Cheng, Zhu, Zhencai, Zorzi, Nicola, and Zwart, Frans

Abstract

The enhanced X-ray Timing and Polarimetry mission (eXTP) is a flagship observatory for X-ray timing, spectroscopy and polarimetry developed by an International Consortium. Thanks to its very large collecting area, good spectral resolution and unprecedented polarimetry capabilities, eXTP will explore the properties of matter and the propagation of light in the most extreme conditions found in the Universe. eXTP will, in addition, be a powerful X-ray observatory. The mission will continuously monitor the X-ray sky, and will enable multiwavelength and multi-messenger studies. The mission is currently in phase B, which will be completed in the middle of 2022.

Published
2022

28. Enhanced X-ray Timing and Polarimetry mission: eXTP: an update on its scientific cases, mission profile and development status

Author

den Herder, Jan-Willem A., Nikzad, Shouleh, Nakazawa, Kazuhiro, Zhang, Shuang-Nan, Santangelo, Andrea, Xu, Yupeng, Feroci, Marco, Hernanz, Margarita, Lu, Fangjun, Chen, Yong, Feng, Hua, Nandra, Kirpal, Jiang, Weichun, Svoboda, Jiri, Brandt, Søren, Schanne, Stéphane, in't Zand, Jean, Michalska, Malgosia, Bozzo, Enrico, Kalemci, Emrah, Agudo, Ivan, Ahangarianabhari, Mahdi, Aitink-Kroes, Gabby, An, Zhenghua, Cao, Jiewei, Cao, Xuelei, Chen, Tianxiang, Chen, Can, Chen, Yupeng, Cheng, Yaodong, Cong, Min, Cui, Weiwei, Cui, Tao, Wu, Zhenyu, Liu, Yichen, Su, Yongquan, Wang, Jian, Zhang, Zhen, Jin, Ge, Li, Longhui, Qiu, Xiangbiao, Lin, Yanjian, Li, Tao, Zhang, Jiawei, Wu, Chao, Xu, Wei, Hu, Zexun, Xu, Zhao, Qiao, Fangjian, Pan, Kai, Zhang, Shu, Song, Liming, He, Huilin, Zhang, Fan, Liu, Hongwei, Liu, Xiaojing, Yang, Yanji, Song, Zeyu, Zhang, Jiawei, Yu, Ke, Wang, Yusa, Li, Wei, Han, Dawei, Wang, Juan, Zhang, Ziliang, Wang, Hao, Zhang, Dali, Gao, Min, Ma, Jia, Huo, Jia, Li, Maoshun, Hou, Dongjie, Yang, Xiongtao, Zhao, Zijian, Zhao, Xiaofan, Xu, Jingjing, Luo, Laidan, Zhu, Yuxuan, Zhang, Honglin, Liu, Xiaohua, Gu, Yudong, Du, Yuanyuan, Yang, Sheng, Sun, Liang, Jiang, Jiechen, Yang, Jiawei, Dong, Zefang, Dai, Boyu, Jiao, Yang, Wen, Xiangyang, Meng, Bin, Zhang, Aimei, Wang, Ruijie, Zhang, Tong, Lu, Bing, Gao, Na, Xu, Xiongwei, Luo, Tao, Qi, Liqiang, Li, Gang, Qu, Jinlu, Xiong, Shaolin, Tao, Liao, Jia, Shumei, Ge, Mingyu, Zheng, Shijie, Li, Xiaobo, Ma, Xiang, Huang, Yue, Li, Chengkui, Nie, Jianyin, Zhao, Haisheng, Guan, Ju, Liao, Jinyuan, Zhang, Hongmei, Zhang, Juan, Wang, Ping, Zhao, Xiaoyun, Wang, Lingjun, Zhang, Liang, Yi, Shuxu, Li, Bing, Tan, Ying, Qi, Fazhi, Wang, Wenshuai, Ou, Ge, Hu, Hao, Shi, Jingyan, Hu, Qingbao, Jiang, Xiaowei, Li, Haibo, Hu, Yu, Jiang, Bowen, Tenzer, Chris, Perinati, Emanuele, and Pliego, Samuel

Published
2022
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29. Automated and Intelligent Data Migration Strategy in High Energy Physical Storage Systems

Author

Zhenjing Cheng, Haibo Li, Qi Xu, Hu Qingbao, Lu Wang, Cheng Yaodong, and Gang Chen

Subjects
Data access, Software, business.industry, Process (engineering), Deep learning, Distributed computing, Data management, Computer data storage, Volume (computing), Artificial intelligence, business, Data migration
Abstract

As a data-intensive computing application, high-energy physics requires to process and store massive data at the PB or EB level. It requires high performance data access and large volume of data storage as well. Some enterprises and research organizations are beginning to use tiered storage architectures, using tapes, disks or solid drives at the same time to reduce hardware purchase costs and power consumption. Tiered storage requires data management software to migrate less active data to lower cost storage devices. Thus an automated data migration strategy is very necessary. Data access requests are driven by the behavior of users or programs. There must be associations between different files that are accessed consecutively. This paper proposes a method to predict the heat of data access and use data heat trend as the basis criteria for data migration. This paper proposes a deep learning algorithm model to predict the evolution trend of data access heat. This paper discussed the implementation of some initial parts of the system. Then some preliminary experiments are conducted with these parts.

Published
2019
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30. Evolution of the LHAASO Distributed Computing System based Cloud.

Author

Doglioni, C., Kim, D., Stewart, G.A., Silvestris, L., Jackson, P., Kamleh, W., Huang, Qiulan, Li, Haibo, Cheng, Yaodong, Shi, Jingyan, Zheng, Wei, and Hu, Qingbao

Subjects
DISTRIBUTED computing, COMPUTER scheduling, DATA integration, COMPUTER architecture, CLOUD computing, MAINTENANCE costs
Abstract

In this paper we will describe the LHAASO distributed computing system based on virtualization and cloud computing technologies. Particularly, we discuss the key points of integrating distributed resources. A solution of integrating cross-domain resources is proposed, which adopt the Openstack+HTCondor to make the distributed resources work as a whole resource pool. A flexible resource scheduling strategy and a job scheduling policy are presented to realize the resource expansion on demand and the efficient job scheduling to remote sites transparently, so as to improve the overall resource utilization. We will also introduce the deployment of the computing system located in Daocheng, the LHAASO observation base using cloud-based architecture, which greatly helps to reduce the operation and maintenance cost as well as to make sure the system availability and stability. Finally, we will show running status of the system. [ABSTRACT FROM AUTHOR]

Published
2020
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31. CDFS: A high-efficiency Data Access System for Storage Federations.

Author

Doglioni, C., Kim, D., Stewart, G.A., Silvestris, L., Jackson, P., Kamleh, W., Fu, Shiyuan, Xu, Qi, Cheng, Yaodong, and Chen, Gang

Subjects
PARTICLE physics, DISTRIBUTED computing, DATA management, COMPUTER software, INFORMATION retrieval
Abstract

High energy physics (HEP) experiments, such as LHAASO, produce a large amount of data, which is usually stored and processed on distributed sites. Nowadays, the distributed data management system faces some challenges such as global file namespace, efficient data access and storage. Focusing on those problems, this paper proposed a cross-domain data access file system (CDFS), applying data deduplication and compression as the storage-optimized engine, aiming at dynamically building an aggregate view of multiple distributed storages and accessing data in a fast and efficient way. The test based on the raw data of LHAASO experiment showed that the CDFS could present a unique repository based on distributed sites in LHAASO. And the storage-optimized engine reduces the storage consumption of the raw data by more than 50%. [ABSTRACT FROM AUTHOR]

Published
2020
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32. Heat Prediction of High Energy Physical Data Based on LSTM Recurrent Neural Network.

Author

Doglioni, C., Kim, D., Stewart, G.A., Silvestris, L., Jackson, P., Kamleh, W., Cheng, Zhenjing, Wang, Lu, Cheng, Yaodong, and Chen, Gang

Subjects
PARTICLE physics, ARTIFICIAL neural networks, ALGORITHMS, INFORMATION retrieval
Abstract

High-energy physics computing is a typical data-intensive calculation. Each year, petabytes of data needs to be analyzed, and data access performance is increasingly demanding. The tiered storage system scheme for building a unified namespace has been widely adopted. Generally, data is stored on storage devices with different performances and different prices according to different access frequency. When the heat of the data changes, the data is then migrated to the appropriate storage tier. At present, heuristic algorithms based on artificial experience are widely used in data heat prediction. Due to the differences in computing models of different users, the accuracy of prediction is low. A method for predicting future access popularity based on file access characteristics with the help of LSTM deep learning algorithm is proposed as the basis for data migration in hierarchical storage. This paper uses the real data of high-energy physics experiment LHAASO as an example for comparative testing. The results show that under the same test conditions, the model has higher prediction accuracy and stronger applicability than existing prediction models. [ABSTRACT FROM AUTHOR]

Published
2020
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48. Sharing LCG files across different platforms

Author

Wang Lu, Liu Aigui, Cheng Yaodong, and Cheng Gang

Subjects
History, Grid middleware, Database, Java, Interface (Java), Computer science, computer.software_genre, Computer Science Applications, Education, Operating system, Web service, Architecture, computer, computer.programming_language
Abstract

Currently more and more heterogeneous resources are integrated into LCG. Sharing LCG files across different platforms, including different OS and grid middleware, is a basic issue. We implemented web service interface for LFC and pseudo LCG file access client by using globus Java CoG Kit. This paper describes the architecture, implementation, and performance testing, tuning and usage scenario.

Published
2008
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