Szczegóły publikacji
Opis bibliograficzny
Bridging the gap between HPC and Cloud using HyperFlow and PaaSage / Dennis Hoppe, [et al.], Maciej MALAWSKI, Bartosz BALIŚ, Maciej PAWLIK, Kamil FIGIELA, Dariusz KRÓL, Michał ORZECHOWSKI, Jacek KITOWSKI, Marian BUBAK // W: Parallel Processing and Applied Mathematics : 12th international conference, PPAM 2017 : Lublin, Poland, September 10–13, 2017 : revised selected papers, Pt. 1 / eds. Roman Wyrzykowski [et al.]. — Cham: Springer International Publishing, cop. 2018. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 10777. Theoretical Computer Science and General Issues ; ISSN 0302-9743). — ISBN: 978-3-319-78023-8; e-ISBN: 978-3-319-78024-5. — S. 432–442. — Bibliogr. s. 441–442, Abstr.
Autorzy (11)
- Hoppe Dennis
- Sandoval Yosandra
- Sulistio Anthony
- AGHMalawski Maciej
- AGHBaliś Bartosz
- AGHPawlik Maciej
- AGHFigiela Kamil
- AGHKról Dariusz
- AGHOrzechowski Michał
- AGHKitowski Jacek
- AGHBubak Marian
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 119819 |
|---|---|
| Data dodania do BaDAP | 2019-02-11 |
| Tekst źródłowy | URL |
| DOI | 10.1007/978-3-319-78024-5_38 |
| Rok publikacji | 2018 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Parallel Processing and Applied Mathematics 2017 |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
A hybrid HPC/Cloud architecture is a potential solution to the ever-increasing demand for high-availability on-demand resources for eScience applications. eScience applications are primarily compute-intensive, and thus require HPC resources. They usually also include pre- and post-processing steps, which can be moved into the Cloud in order to keep costs low. We believe that currently no methodology exists to bridge the gap between HPC and Cloud in a seamless manner. The goal is to lower the gap for non-professionals in order to exploit external facilities through an automated deployment and scaling both vertically (HPC) and horizontally (Cloud). This paper demonstrates how representative eScience applications can easily be transferred from HPC to Cloud using the model-based cross-cloud deployment platform PaaSage.
