Ιδρυματικό Αποθετήριο
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Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/D3411926-5317-40D6-A869-3071D319742B | - |
| Αναγνωριστικό | https://doi.org/10.1109/FPL.2019.00052 | - |
| Αναγνωριστικό | https://ieeexplore.ieee.org/document/8892241 | - |
| Γλώσσα | en | - |
| Μέγεθος | 8 pages | en |
| Τίτλος | Data stream statistics over sliding windows: how to summarize 150 million updates per second on a single node | en |
| Δημιουργός | Chrysos Grigorios | en |
| Δημιουργός | Χρυσος Γρηγοριος | el |
| Δημιουργός | Papapetrou, Odysseas 1978- | en |
| Δημιουργός | Pnevmatikatos Dionysios | en |
| Δημιουργός | Πνευματικατος Διονυσιος | el |
| Δημιουργός | Dollas Apostolos | en |
| Δημιουργός | Δολλας Αποστολος | el |
| Δημιουργός | Garofalakis Minos | en |
| Δημιουργός | Γαροφαλακης Μινως | el |
| Εκδότης | Institute of Electrical and Electronics Engineers | en |
| Περίληψη | Traditional data management systems map information using centralized and static data structures. Modern applications need to process in real time datasets much larger than system memory. To achieve this, they use dynamic entities that are updated with streaming input data over a sliding window. For efficient and high performance processing, approximate sketch synopses of input streams have been proposed as effective means for the summarization of streaming data over large sliding windows with probabilistic accuracy guarantees. This work presents a system-level solution to accelerate the Exponential Count-Min (ECM) sketch algorithm on reconfigurable technology. Different reconfigurable architectures for the sketch structure that correspond to different cost and performance tradeoffs are presented. We map the proposed system-level ECM sketch architectures to a high-end modern HPC platform to achieve guaranteed and best-effort update rates up to 150 and 180 million tuples per second respectively. We compare the performance of the implemented system against the best optimized multi-thread software alternative and show that our scalable full-system accelerators outperform software solutions by 5-7.5x for Virtex6 devices and in excess of 10x for current Ultrascale devices. | en |
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Τύπος | Conference Full Paper | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2020-04-27 | - |
| Ημερομηνία Δημοσίευσης | 2019 | - |
| Θεματική Κατηγορία | ECM sketch | en |
| Θεματική Κατηγορία | Exponential histogram | en |
| Θεματική Κατηγορία | Reconfigurable architecture | en |
| Θεματική Κατηγορία | Reconfigurable computing | en |
| Θεματική Κατηγορία | Stream processing | en |
| Βιβλιογραφική Αναφορά | G. Chrysos, O. Papapetrou, D. Pnevmatikatos, A. Dollas and M. Garofalakis, "Data stream statistics over sliding windows: how to summarize 150 million updates per second on a single node," in 29th International Conferenceon Field-Programmable Logic and Applications, 2019, pp. 278-285. doi: 10.1109/FPL.2019.00052 | en |
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