Pregled bibliografske jedinice broj: 1151524
An overview of dense eigenvalue solvers for distributed memory systems
An overview of dense eigenvalue solvers for distributed memory systems // Proceedings of the 44th International Convention on Information, Communication and Electronic Technology (MIPRO) / Skala, Karolj (ur.).
Rijeka: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2021. str. 265-271 doi:10.23919/MIPRO52101.2021.9596900 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1151524 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
An overview of dense eigenvalue solvers for
distributed memory systems
Autori
Davidović, Davor
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 44th International Convention on Information, Communication and Electronic Technology (MIPRO)
/ Skala, Karolj - Rijeka : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2021, 265-271
ISBN
978-953-233-101-1
Skup
44th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2021)
Mjesto i datum
Opatija, Hrvatska, 27.09.2021. - 01.10.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
eigenvalue solvers ; high-performance computing ; distributed-memory ; large-scale systems
Sažetak
Solving large-scale eigenvalue problems is a central problem in many research areas, such as electronic structure calculations, macromolecular simulations, solid states, theoretical physics, and combinatorial optimization. The computation of the required eigenvalues and the corresponding eigenvectors of the large matrices is a challenging task that requires considerable computational time. Therefore, the computation of such problems is usually performed on large computational resources consisting of a large number of computational nodes interconnected by fast network and often equipped with accelerators, such as graphic processing units. Nowadays, when the whole world is vying for the first exascale supercomputer and the computational appetite of researchers is greater than ever, the need for scalable and powerful eigenvalue solvers capable of utilising such large machines with distributed memory is crucial for further breakthroughs in research. This paper reviews existing numerical linear algebra packages and libraries that implement solvers for dense eigenvalue problems and are tailored to distributed-memory systems. The survey analysis has shown that there are numerous eigenvalue solvers for distributed memory systems. However, not many of them are able to exploit the full potential of modern, heterogeneous, GPU- based machines with complex memory hierarchies.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Računarstvo
POVEZANOST RADA
Projekti:
--UIP-2020-02-4559 - Skalabilni algoritmi visokih performansi za buduće heterogene distribuirane računalne sustave (HybridScale) (Davidović, Davor) ( CroRIS)
KK.01.1.1.01.0009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (EK )
Ustanove:
Institut "Ruđer Bošković", Zagreb
Profili:
Davor Davidović
(autor)