Zobrazeno 91 - 100
of 608
pro vyhledávání: '"Hoefler, Torsten"'
Autor:
Ziogas, Alexandros Nikolaos, Schneider, Timo, Ben-Nun, Tal, Calotoiu, Alexandru, De Matteis, Tiziano, Licht, Johannes de Fine, Lavarini, Luca, Hoefler, Torsten
Python has become the de facto language for scientific computing. Programming in Python is highly productive, mainly due to its rich science-oriented software ecosystem built around the NumPy module. As a result, the demand for Python support in High
Externí odkaz:
http://arxiv.org/abs/2107.00555
Publikováno v:
Published in Proceedings of The International Conference for High Performance Computing Networking, Storage, and Analysis (SC '21) (2021)
The allreduce operation is one of the most commonly used communication routines in distributed applications. To improve its bandwidth and to reduce network traffic, this operation can be accelerated by offloading it to network switches, that aggregat
Externí odkaz:
http://arxiv.org/abs/2106.15565
High performance is needed in many computing systems, from batch-managed supercomputers to general-purpose cloud platforms. However, scientific clusters lack elastic parallelism, while clouds cannot offer competitive costs for high-performance applic
Externí odkaz:
http://arxiv.org/abs/2106.13859
Autor:
Gianinazzi, Lukas, Fries, Maximilian, Dryden, Nikoli, Ben-Nun, Tal, Besta, Maciej, Hoefler, Torsten
We present a novel neural architecture to solve graph optimization problems where the solution consists of arbitrary node labels, allowing us to solve hard problems like graph coloring. We train our model using reinforcement learning, specifically po
Externí odkaz:
http://arxiv.org/abs/2106.03594
Autor:
De Sensi, Daniele, Costa Molero, Edgar, Di Girolamo, Salvatore, Vanbever, Laurent, Hoefler, Torsten
Publikováno v:
In Future Generation Computer Systems March 2024 152:70-82
The growing size of data center and HPC networks pose unprecedented requirements on the scalability of simulation infrastructure. The ability to simulate such large-scale interconnects on a simple PC would facilitate research efforts. Unfortunately,
Externí odkaz:
http://arxiv.org/abs/2105.12663
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
Publikováno v:
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. SC 2021. Article No.: 16
Practical applications of quantum computers require millions of physical qubits and it will be challenging for individual quantum processors to reach such qubit numbers. It is therefore timely to investigate the resource requirements of quantum algor
Externí odkaz:
http://arxiv.org/abs/2105.01109
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