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{"title":"Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service.","authors":"A Hayrapetyan, A Tumasyan, W Adam, J W Andrejkovic, T Bergauer, S Chatterjee, K Damanakis, M Dragicevic, P S Hussain, M Jeitler, N Krammer, A Li, D Liko, I Mikulec, J Schieck, R Schöfbeck, D Schwarz, M Sonawane, S Templ, W Waltenberger, C-E Wulz, M R Darwish, T Janssen, P Van Mechelen, E S Bols, J D'Hondt, S Dansana, A De Moor, M Delcourt, H El Faham, S Lowette, I Makarenko, D Müller, A R Sahasransu, S Tavernier, M Tytgat, G P Van Onsem, S Van Putte, D Vannerom, B Clerbaux, A K Das, G De Lentdecker, L Favart, P Gianneios, D Hohov, J Jaramillo, A Khalilzadeh, F A Khan, K Lee, M Mahdavikhorrami, A Malara, S Paredes, L Thomas, M Vanden Bemden, C Vander Velde, P Vanlaer, M De Coen, D Dobur, Y Hong, J Knolle, L Lambrecht, G Mestdach, K Mota Amarilo, C Rendón, A Samalan, K Skovpen, N Van Den Bossche, J van der Linden, L Wezenbeek, A Benecke, A Bethani, G Bruno, C Caputo, C Delaere, I S Donertas, A Giammanco, K Jaffel, Sa Jain, V Lemaitre, J Lidrych, P Mastrapasqua, K Mondal, T T Tran, S Wertz, G A Alves, E Coelho, C Hensel, T Menezes De Oliveira, A Moraes, P Rebello Teles, M Soeiro, W L Aldá Júnior, M Alves Gallo Pereira, M Barroso Ferreira Filho, H Brandao Malbouisson, W Carvalho, J Chinellato, E M Da Costa, G G Da Silveira, D De Jesus Damiao, S Fonseca De Souza, R Gomes De Souza, J Martins, C Mora Herrera, L Mundim, H Nogima, J P Pinheiro, A Santoro, A Sznajder, M Thiel, A Vilela Pereira, C A Bernardes, L Calligaris, T R Fernandez Perez Tomei, E M Gregores, P G Mercadante, S F Novaes, B Orzari, Sandra S Padula, A Aleksandrov, G Antchev, R Hadjiiska, P Iaydjiev, M Misheva, M Shopova, G Sultanov, A Dimitrov, L Litov, B Pavlov, P Petkov, A Petrov, E Shumka, S Keshri, S Thakur, T Cheng, T Javaid, L Yuan, Z Hu, J Liu, K Yi, G M Chen, H S Chen, M Chen, F Iemmi, C H Jiang, A Kapoor, H Liao, Z-A Liu, R Sharma, J N Song, J Tao, C Wang, J Wang, Z Wang, H Zhang, A Agapitos, Y Ban, A Levin, C Li, Q Li, Y Mao, S J Qian, X Sun, D Wang, H Yang, L Zhang, C Zhou, Z You, N Lu, G Bauer, X Gao, D Leggat, H Okawa, Z Lin, C Lu, M Xiao, C Avila, D A Barbosa Trujillo, A Cabrera, C Florez, J Fraga, J A Reyes Vega, J Mejia Guisao, F Ramirez, M Rodriguez, J D Ruiz Alvarez, D Giljanovic, N Godinovic, D Lelas, A Sculac, M Kovac, T Sculac, P Bargassa, V Brigljevic, B K Chitroda, D Ferencek, S Mishra, A Starodumov, T Susa, A Attikis, K Christoforou, S Konstantinou, J Mousa, C Nicolaou, F Ptochos, P A Razis, H Rykaczewski, H Saka, A Stepennov, M Finger, M Finger, A Kveton, E Ayala, E Carrera Jarrin, A A Abdelalim, E Salama, M A Mahmoud, Y Mohammed, K Ehataht, M Kadastik, T Lange, S Nandan, C Nielsen, J Pata, M Raidal, L Tani, C Veelken, H Kirschenmann, K Osterberg, M Voutilainen, S Bharthuar, E Brücken, F Garcia, K T S Kallonen, R Kinnunen, T Lampén, K Lassila-Perini, S Lehti, T Lindén, L Martikainen, M Myllymäki, M M Rantanen, H Siikonen, E Tuominen, J Tuominiemi, P Luukka, H Petrow, M Besancon, F Couderc, M Dejardin, D Denegri, J L Faure, F Ferri, S Ganjour, P Gras, G Hamel de Monchenault, V Lohezic, J Malcles, J Rander, A Rosowsky, M Ö Sahin, A Savoy-Navarro, P Simkina, M Titov, M Tornago, C Baldenegro Barrera, F Beaudette, A Buchot Perraguin, P Busson, A Cappati, C Charlot, M Chiusi, F Damas, O Davignon, A De Wit, B A Fontana Santos Alves, S Ghosh, A Gilbert, R Granier de Cassagnac, A Hakimi, B Harikrishnan, L Kalipoliti, G Liu, J Motta, M Nguyen, C Ochando, L Portales, R Salerno, J B Sauvan, Y Sirois, A Tarabini, E Vernazza, A Zabi, A Zghiche, J-L Agram, J Andrea, D Apparu, D Bloch, J-M Brom, E C Chabert, C Collard, S Falke, U Goerlach, C Grimault, R Haeberle, A-C Le Bihan, M Meena, G Saha, M A Sessini, P Van Hove, S Beauceron, B Blancon, G Boudoul, N Chanon, J Choi, D Contardo, P Depasse, C Dozen, H El Mamouni, J Fay, S Gascon, M Gouzevitch, C Greenberg, G Grenier, B Ille, I B Laktineh, M Lethuillier, L Mirabito, S Perries, A Purohit, M Vander Donckt, P Verdier, J Xiao, I Bagaturia, I Lomidze, Z Tsamalaidze, V Botta, L Feld, K Klein, M Lipinski, D Meuser, A Pauls, N Röwert, M Teroerde, S Diekmann, A Dodonova, N Eich, D Eliseev, F Engelke, J Erdmann, M Erdmann, P Fackeldey, B Fischer, T Hebbeker, K Hoepfner, F Ivone, A Jung, M Y Lee, F Mausolf, M Merschmeyer, A Meyer, S Mukherjee, D Noll, F Nowotny, A Pozdnyakov, Y Rath, W Redjeb, F Rehm, H Reithler, U Sarkar, V Sarkisovi, A Schmidt, A Sharma, J L Spah, A Stein, F Torres Da Silva De Araujo, L Vigilante, S Wiedenbeck, S Zaleski, C Dziwok, G Flügge, W Haj Ahmad, T Kress, A Nowack, O Pooth, A Stahl, T Ziemons, A Zotz, H Aarup Petersen, M Aldaya Martin, J Alimena, S Amoroso, Y An, S Baxter, M Bayatmakou, H Becerril Gonzalez, O Behnke, A Belvedere, S Bhattacharya, F Blekman, K Borras, A Campbell, A Cardini, C Cheng, F Colombina, S Consuegra Rodríguez, G Correia Silva, M De Silva, G Eckerlin, D Eckstein, L I Estevez Banos, O Filatov, E Gallo, A Geiser, A Giraldi, V Guglielmi, M Guthoff, A Hinzmann, A Jafari, L Jeppe, N Z Jomhari, B Kaech, M Kasemann, C Kleinwort, R Kogler, M Komm, D Krücker, W Lange, D Leyva Pernia, K Lipka, W Lohmann, R Mankel, I-A Melzer-Pellmann, M Mendizabal Morentin, A B Meyer, G Milella, A Mussgiller, L P Nair, A Nürnberg, Y Otarid, J Park, D Pérez Adán, E Ranken, A Raspereza, B Ribeiro Lopes, J Rübenach, A Saggio, M Scham, S Schnake, P Schütze, C Schwanenberger, D Selivanova, K Sharko, M Shchedrolosiev, R E Sosa Ricardo, D Stafford, F Vazzoler, A Ventura Barroso, R Walsh, Q Wang, Y Wen, K Wichmann, L Wiens, C Wissing, Y Yang, A Zimermmane Castro Santos, A Albrecht, S Albrecht, M Antonello, S Bein, L Benato, S Bollweg, M Bonanomi, P Connor, M Eich, K El Morabit, Y Fischer, C Garbers, E Garutti, A Grohsjean, J Haller, H R Jabusch, G Kasieczka, P Keicher, R Klanner, W Korcari, T Kramer, V Kutzner, F Labe, J Lange, A Lobanov, C Matthies, A Mehta, L Moureaux, M Mrowietz, A Nigamova, Y Nissan, A Paasch, K J Pena Rodriguez, T Quadfasel, B Raciti, M Rieger, D Savoiu, J Schindler, P Schleper, M Schröder, J Schwandt, M Sommerhalder, H Stadie, G Steinbrück, A Tews, M Wolf, S Brommer, M Burkart, E Butz, T Chwalek, A Dierlamm, A Droll, N Faltermann, M Giffels, A Gottmann, F Hartmann, R Hofsaess, M Horzela, U Husemann, J Kieseler, M Klute, R Koppenhöfer, J M Lawhorn, M Link, A Lintuluoto, S Maier, S Mitra, M Mormile, Th Müller, M Neukum, M Oh, M Presilla, G Quast, K Rabbertz, B Regnery, N Shadskiy, I Shvetsov, H J Simonis, M Toms, N Trevisani, R F Von Cube, M Wassmer, S Wieland, F Wittig, R Wolf, X Zuo, G Anagnostou, G Daskalakis, A Kyriakis, A Papadopoulos, A Stakia, P Kontaxakis, G Melachroinos, A Panagiotou, I Papavergou, I Paraskevas, N Saoulidou, K Theofilatos, E Tziaferi, K Vellidis, I Zisopoulos, G Bakas, T Chatzistavrou, G Karapostoli, K Kousouris, I Papakrivopoulos, E Siamarkou, G Tsipolitis, A Zacharopoulou, K Adamidis, I Bestintzanos, I Evangelou, C Foudas, C Kamtsikis, P Katsoulis, P Kokkas, P G Kosmoglou Kioseoglou, N 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Bouchamaoui, P Das, G Dezoort, P Elmer, A Frankenthal, B Greenberg, N Haubrich, G Kopp, S Kwan, D Lange, A Loeliger, D Marlow, I Ojalvo, J Olsen, A Shevelev, D Stickland, C Tully, S Malik, A S Bakshi, V E Barnes, S Chandra, R Chawla, S Das, A Gu, L Gutay, M Jones, A W Jung, D Kondratyev, A M Koshy, M Liu, G Negro, N Neumeister, G Paspalaki, S Piperov, V Scheurer, J F Schulte, M Stojanovic, J Thieman, A K Virdi, F Wang, W Xie, J Dolen, N Parashar, A Pathak, D Acosta, T Carnahan, K M Ecklund, P J Fernández Manteca, S Freed, P Gardner, F J M Geurts, W Li, O Miguel Colin, B P Padley, R Redjimi, J Rotter, E Yigitbasi, Y Zhang, A Bodek, P de Barbaro, R Demina, J L Dulemba, A Garcia-Bellido, O Hindrichs, A Khukhunaishvili, N Parmar, P Parygin, E Popova, R Taus, K Goulianos, B Chiarito, J P Chou, Y Gershtein, E Halkiadakis, M Heindl, C Houghton, D Jaroslawski, O Karacheban, I Laflotte, A Lath, R Montalvo, K Nash, H Routray, S Salur, S Schnetzer, S Somalwar, R Stone, S A Thayil, S Thomas, J Vora, H Wang, H Acharya, D Ally, A G Delannoy, S Fiorendi, S Higginbotham, T Holmes, A R Kanuganti, N Karunarathna, L Lee, E Nibigira, S Spanier, D Aebi, M Ahmad, O Bouhali, R Eusebi, J Gilmore, T Huang, T Kamon, H Kim, S Luo, R Mueller, D Overton, D Rathjens, A Safonov, N Akchurin, J Damgov, V Hegde, A Hussain, Y Kazhykarim, K Lamichhane, S W Lee, A Mankel, T Peltola, I Volobouev, A Whitbeck, E Appelt, Y Chen, S Greene, A Gurrola, W Johns, R Kunnawalkam Elayavalli, A Melo, F Romeo, P Sheldon, S Tuo, J Velkovska, J Viinikainen, B Cardwell, B Cox, J Hakala, R Hirosky, A Ledovskoy, C Neu, C E Perez Lara, P E Karchin, A Aravind, S Banerjee, K Black, T Bose, S Dasu, I De Bruyn, P Everaerts, C Galloni, H He, M Herndon, A Herve, C K Koraka, A Lanaro, R Loveless, J Madhusudanan Sreekala, A Mallampalli, A Mohammadi, S Mondal, G Parida, L Pétré, D Pinna, A Savin, V Shang, V Sharma, W H Smith, D Teague, H F Tsoi, W Vetens, A Warden, S Afanasiev, V Andreev, Yu Andreev, T Aushev, M Azarkin, A Babaev, A Belyaev, V Blinov, E Boos, V Borshch, D Budkouski, M Chadeeva, V Chekhovsky, R Chistov, A Demiyanov, A Dermenev, T Dimova, D Druzhkin, M Dubinin, L Dudko, A Ershov, G Gavrilov, V Gavrilov, S Gninenko, V Golovtcov, N Golubev, I Golutvin, I Gorbunov, A Gribushin, Y Ivanov, V Kachanov, V Karjavine, A Karneyeu, V Kim, M Kirakosyan, D Kirpichnikov, M Kirsanov, V Klyukhin, O Kodolova, V Korenkov, A Kozyrev, N Krasnikov, A Lanev, P Levchenko, N Lychkovskaya, V Makarenko, A Malakhov, V Matveev, V Murzin, A Nikitenko, S Obraztsov, V Oreshkin, V Palichik, V Perelygin, S Petrushanko, S Polikarpov, V Popov, O Radchenko, M Savina, V Savrin, V Shalaev, S Shmatov, S Shulha, Y Skovpen, S Slabospitskii, V Smirnov, A Snigirev, D Sosnov, V Sulimov, E Tcherniaev, A Terkulov, O Teryaev, I Tlisova, A Toropin, L Uvarov, A Uzunian, A Vorobyev, N Voytishin, B S Yuldashev, A Zarubin, I Zhizhin, A Zhokin","doi":"10.1007/s41781-024-00124-1","DOIUrl":null,"url":null,"abstract":"<p><p>Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.</p>","PeriodicalId":36026,"journal":{"name":"Computing and Software for Big Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11374919/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computing and Software for Big Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41781-024-00124-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/4 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.
未来几十年，大型科学实验（如欧洲核子研究中心大型强子对撞机的 CMS 实验）的计算需求将急剧增加。为了补充未来中央处理器（CPU）上运行的软件性能的提高，探索在数据处理中使用协处理器具有巨大的潜力和意义。协处理器是一类计算机处理器，是中央处理器的补充，通常能通过架构设计的选择改善某些功能的执行。我们探索了协处理器上的优化网络推理服务（SONIC）方法，并研究了在大规模数据处理中部署这种即服务方法的问题。在研究中，我们采用了 CMS 实验的数据处理工作流程，在 CPU 上运行主要工作流程，同时将若干机器学习（ML）推理任务卸载到远程或本地协处理器（特别是图形处理器（GPU））上。通过在谷歌云、普渡大学二级计算中心以及两者的结合处进行的实验，我们展示了这些 ML 算法在协处理器上的加速效果，以及整个工作流相应吞吐量的提高。这种方法可以很容易地推广到不同类型的协处理器上，并部署在本地 CPU 上，而不会降低吞吐量性能。我们强调，SONIC 方法能够提高协处理器的使用率，并可移植到不同类型的协处理器上运行工作流。
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