Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Kwasniewski, Grzegorz"'
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, Miglioli, Cesare, Labini, Paolo Sylos, Tětek, Jakub, Iff, Patrick, Kanakagiri, Raghavendra, Ashkboos, Saleh, Janda, Kacper, Podstawski, Michal, Kwasniewski, Grzegorz, Gleinig, Niels, Vella, Flavio, Mutlu, Onur, Hoefler, Torsten
Publikováno v:
Proceedings of the ACM/IEEE International Conference on High Performance Computing, Networking, Storage and Analysis, November 2022
Important graph mining problems such as Clustering are computationally demanding. To significantly accelerate these problems, we propose ProbGraph: a graph representation that enables simple and fast approximate parallel graph mining with strong theo
Externí odkaz:
http://arxiv.org/abs/2208.11469
Autor:
Ziogas, Alexandros Nikolaos, Kwasniewski, Grzegorz, Ben-Nun, Tal, Schneider, Timo, Hoefler, Torsten
Multilinear algebra kernel performance on modern massively-parallel systems is determined mainly by data movement. However, deriving data movement-optimal distributed schedules for programs with many high-dimensional inputs is a notoriously hard prob
Externí odkaz:
http://arxiv.org/abs/2206.08301
Autor:
Calotoiu, Alexandru, Ben-Nun, Tal, Kwasniewski, Grzegorz, Licht, Johannes de Fine, Schneider, Timo, Schaad, Philipp, Hoefler, Torsten
C is the lingua franca of programming and almost any device can be programmed using C. However, programming mod-ern heterogeneous architectures such as multi-core CPUs and GPUs requires explicitly expressing parallelism as well as device-specific pro
Externí odkaz:
http://arxiv.org/abs/2112.11879
Autor:
Kwasniewski, Grzegorz, Kabić, Marko, Ben-Nun, Tal, Ziogas, Alexandros Nikolaos, Saethre, Jens Eirik, Gaillard, André, Schneider, Timo, Besta, Maciej, Kozhevnikov, Anton, VandeVondele, Joost, Hoefler, Torsten
Publikováno v:
Published at Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November, 2021(SC'21)
Matrix factorizations are among the most important building blocks of scientific computing. State-of-the-art libraries, however, are not communication-optimal, underutilizing current parallel architectures. We present novel algorithms for Cholesky an
Externí odkaz:
http://arxiv.org/abs/2108.09337
Autor:
Besta, Maciej, Grob, Raphael, Miglioli, Cesare, Bernold, Nicola, Kwasniewski, Grzegorz, Gjini, Gabriel, Kanakagiri, Raghavendra, Ashkboos, Saleh, Gianinazzi, Lukas, Dryden, Nikoli, Hoefler, Torsten
Publikováno v:
Proceedings of the 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'22), 2022
Link prediction is one of the central problems in graph mining. However, recent studies highlight the importance of higher-order network analysis, where complex structures called motifs are the first-class citizens. We first show that existing link p
Externí odkaz:
http://arxiv.org/abs/2106.00761
Autor:
Kwasniewski, Grzegorz, Ben-Nun, Tal, Gianinazzi, Lukas, Calotoiu, Alexandru, Schneider, Timo, Ziogas, Alexandros Nikolaos, Besta, Maciej, Hoefler, Torsten
Determining I/O lower bounds is a crucial step in obtaining communication-efficient parallel algorithms, both across the memory hierarchy and between processors. Current approaches either study specific algorithms individually, disallow programmatic
Externí odkaz:
http://arxiv.org/abs/2105.07203
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
Autor:
Besta, Maciej, Vonarburg-Shmaria, Zur, Schaffner, Yannick, Schwarz, Leonardo, Kwasniewski, Grzegorz, Gianinazzi, Lukas, Beranek, Jakub, Janda, Kacper, Holenstein, Tobias, Leisinger, Sebastian, Tatkowski, Peter, Ozdemir, Esref, Balla, Adrian, Copik, Marcin, Lindenberger, Philipp, Kalvoda, Pavel, Konieczny, Marek, Mutlu, Onur, Hoefler, Torsten
Publikováno v:
International Conference on Very Large Data Bases (VLDB), 2021
We propose GraphMineSuite (GMS): the first benchmarking suite for graph mining that facilitates evaluating and constructing high-performance graph mining algorithms. First, GMS comes with a benchmark specification based on extensive literature review
Externí odkaz:
http://arxiv.org/abs/2103.03653
Function-as-a-Service (FaaS) is one of the most promising directions for the future of cloud services, and serverless functions have immediately become a new middleware for building scalable and cost-efficient microservices and applications. However,
Externí odkaz:
http://arxiv.org/abs/2012.14132