Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Blach, Nils"'
Autor:
Bonato, Tommaso, Kabbani, Abdul, De Sensi, Daniele, Pan, Rong, Le, Yanfang, Raiciu, Costin, Handley, Mark, Schneider, Timo, Blach, Nils, Ghalayini, Ahmad, Alves, Daniel, Papamichael, Michael, Caulfield, Adrian, Hoefler, Torsten
With the rapid growth of machine learning (ML) workloads in datacenters, existing congestion control (CC) algorithms fail to deliver the required performance at scale. ML traffic is bursty and bulk-synchronous and thus requires quick reaction and str
Externí odkaz:
http://arxiv.org/abs/2404.01630
Autor:
Besta, Maciej, Memedi, Florim, Zhang, Zhenyu, Gerstenberger, Robert, Piao, Guangyuan, Blach, Nils, Nyczyk, Piotr, Copik, Marcin, Kwaśniewski, Grzegorz, Müller, Jürgen, Gianinazzi, Lukas, Kubicek, Ales, Niewiadomski, Hubert, O'Mahony, Aidan, Mutlu, Onur, Hoefler, Torsten
The field of natural language processing (NLP) has witnessed significant progress in recent years, with a notable focus on improving large language models' (LLM) performance through innovative prompting techniques. Among these, prompt engineering cou
Externí odkaz:
http://arxiv.org/abs/2401.14295
Autor:
Besta, Maciej, Catarino, Afonso Claudino, Gianinazzi, Lukas, Blach, Nils, Nyczyk, Piotr, Niewiadomski, Hubert, Hoefler, Torsten
Publikováno v:
Proceedings of Learning on Graphs (LOG), 2023
Many graph representation learning (GRL) problems are dynamic, with millions of edges added or removed per second. A fundamental workload in this setting is dynamic link prediction: using a history of graph updates to predict whether a given pair of
Externí odkaz:
http://arxiv.org/abs/2311.18526
Autor:
Blach, Nils, Besta, Maciej, De Sensi, Daniele, Domke, Jens, Harake, Hussein, Li, Shigang, Iff, Patrick, Konieczny, Marek, Lakhotia, Kartik, Kubicek, Ales, Ferrari, Marcel, Petrini, Fabrizio, Hoefler, Torsten
Publikováno v:
Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI '24) Santa Clara, CA, USA April 16-18, 2024
Novel low-diameter network topologies such as Slim Fly (SF) offer significant cost and power advantages over the established Fat Tree, Clos, or Dragonfly. To spearhead the adoption of low-diameter networks, we design, implement, deploy, and evaluate
Externí odkaz:
http://arxiv.org/abs/2310.03742
Autor:
Besta, Maciej, Blach, Nils, Kubicek, Ales, Gerstenberger, Robert, Podstawski, Michal, Gianinazzi, Lukas, Gajda, Joanna, Lehmann, Tomasz, Niewiadomski, Hubert, Nyczyk, Piotr, Hoefler, Torsten
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence 2024 (AAAI'24)
We introduce Graph of Thoughts (GoT): a framework that advances prompting capabilities in large language models (LLMs) beyond those offered by paradigms such as Chain-of-Thought or Tree of Thoughts (ToT). The key idea and primary advantage of GoT is
Externí odkaz:
http://arxiv.org/abs/2308.09687
Autor:
Besta, Maciej, Gerstenberger, Robert, Fischer, Marc, Podstawski, Michał, Blach, Nils, Egeli, Berke, Mitenkov, Georgy, Chlapek, Wojciech, Michalewicz, Marek, Niewiadomski, Hubert, Müller, Jürgen, Hoefler, Torsten
Publikováno v:
Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, 2023 (SC '23)
Graph databases (GDBs) are crucial in academic and industry applications. The key challenges in developing GDBs are achieving high performance, scalability, programmability, and portability. To tackle these challenges, we harness established practice
Externí odkaz:
http://arxiv.org/abs/2305.11162
Autor:
Lakhotia, Kartik, Monroe, Laura, Isham, Kelly, Besta, Maciej, Blach, Nils, Hoefler, Torsten, Petrini, Fabrizio
In this paper, we present PolarStar, a novel family of diameter-3 network topologies derived from the star product of two low-diameter factor graphs. The proposed PolarStar construction gives the largest known diameter-3 network topologies for almost
Externí odkaz:
http://arxiv.org/abs/2302.07217
Autor:
Besta, Maciej, Kanakagiri, Raghavendra, Kwasniewski, Grzegorz, Ausavarungnirun, Rachata, Beránek, Jakub, Kanellopoulos, Konstantinos, Janda, Kacper, Vonarburg-Shmaria, Zur, Gianinazzi, Lukas, Stefan, Ioana, Luna, Juan Gómez, Copik, Marcin, Kapp-Schwoerer, Lukas, Di Girolamo, Salvatore, Konieczny, Marek, Blach, Nils, Mutlu, Onur, Hoefler, Torsten
Simple graph algorithms such as PageRank have been the target of numerous hardware accelerators. Yet, there also exist much more complex graph mining algorithms for problems such as clustering or maximal clique listing. These algorithms are memory-bo
Externí odkaz:
http://arxiv.org/abs/2104.07582
Professionals in modern healthcare systems are increasingly burdened by documentation workloads. Documentation of the initial patient anamnesis is particularly relevant, forming the basis of successful further diagnostic measures. However, manually p
Externí odkaz:
http://arxiv.org/abs/2011.01696
Autor:
Besta, Maciej, Gerstenberger, Robert, Fischer, Marc, Podstawski, Michał, Müller, Jürgen, Blach, Nils, Egeli, Berke, Mitenkov, George, Chlapek, Wojciech, Michalewicz, Marek, Hoefler, Torsten
Graph databases (GDBs) are crucial in academic and industry applications. The key challenges in developing GDBs are achieving high performance, scalability, programmability, and portability. To tackle these challenges, we harness established practice
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86709abb2df4c136a77a745f5605eb89