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Implementation of mutual information and transfer entropy algorithms with FPGA-based SuperComputer

Iordanou Konstantinos

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Extent89 pagesen
TitleImplementation of mutual information and transfer entropy algorithms with FPGA-based SuperComputeren
TitleΥλοποίηση των αλγορίθμων mutual information και transfer entropy με υπερ-υπολογιστή βασισμένο σε αναδιατασσόμενη λογικήel
CreatorIordanou Konstantinosen
CreatorΙορδανου Κωνσταντινοςel
Contributor [Thesis Supervisor]Dollas Apostolosen
Contributor [Thesis Supervisor]Δολλας Αποστολοςel
Contributor [Committee Member]Garofalakis Minosen
Contributor [Committee Member]Γαροφαλακης Μινωςel
Contributor [Committee Member]Papaefstathiou Ioannisen
Contributor [Committee Member]Παπαευσταθιου Ιωαννηςel
PublisherΠολυτεχνείο Κρήτηςel
PublisherTechnical University of Creteen
Academic UnitTechnical University of Crete::School of Electrical and Computer Engineeringen
Academic UnitΠολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστώνel
DescriptionA thesis submitted in fulfillment of the requirements for the degree of Diploma in Electrical and Computer Engineering en
Content SummaryIt is widely known that contemporary applications are bounded by massive computational demands. With conventional CPUs falling out of favor due to their limitations, the industry of Hybrid-SuperComputers using reconfigurable logic which is a growing field in the area of Computer Systems. This thesis explores the Convey Computer, and more specifically the platform HC-2ex which is a hybrid platform with increased computational capacity as well as a combination of a high-bandwidth memory interface with an architecture featuring multiple levels of computational parallelism. This platform selected in order to efficiently map computationally intensive algorithms in modern hardware. We address two challenging problems within this framework, the first being time-series analysis by focusing on the calculation of the Mutual Information (MI) statistical value and the second being the Transfer Entropy (TE) statistical value between two time-series. The problems of Mutual Information and Transfer Entropy respectively, have been addressed by the research community for low-precision arithmetic applications, but the performance of these algorithms have not been evaluated on platforms like Convey Computer. This is the first work to extensively study of using this platform, by identifying the pros and cons of Convey Computer with computationally intensive algorithms as well as describing how these algorithms can efficiently utilized. In terms of result, Mutual Information and Transfer Entropy implementations compared with implemented architectures on other platforms like Maxeler. Compared to the reference software, the implementation of MI algorithm yielded 13x speedup as well as the implementation of TE yielded 15x speedup for high dimensional data using 32-bit precision arithmetic on Convey HC-2ex.en
Type of ItemΔιπλωματική Εργασίαel
Type of ItemDiploma Worken
Date of Item2017-06-28-
Date of Publication2017-
SubjectTransfer entropyen
SubjectMutual informationen
SubjectConvey HC-2exen
SubjectReconfigurable computingen
Bibliographic CitationKonstantinos Iordanou, "Implementation of mutual information and transfer entropy algorithms with FPGA-based SuperComputer", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2017en
Bibliographic CitationΚωνσταντίνος Ιορδάνου, "Υλοποίηση των αλγορίθμων mutual information και transfer entropy με υπερ-υπολογιστή βασισμένο σε αναδιατασσόμενη λογική", Διπλωματική Εργασία, Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2017el

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