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Σχεδίαση πλατφόρμας βασισμένης σε αναδιατασσόμενη λογική για εξόρυξη δεδομένων από ροές

Kritikakis Charalabos

Πλήρης Εγγραφή

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Περίληψη

Stream join is one of the most fundamental operations to relate information from different streams. The challenging task is to use systems with memory and run-time constraints in order to store and analyze massive volumes of streaming data. Hence, it is important to maximize the processing which is done on-the-fly as the streaming data arrives. This paper presents an FPGA-based architecture that maps the most performance-efficient stream join algorithm, i.e. ScaleJoin, to reconfigurable logic. The system was fully implemented on a Convey HC-2ex hybrid computer and experimental performance evaluation shows that the proposed system outperforms by up to one order of magnitude the corresponding fully optimized software-based solution running on a high-end 48-core multiprocessor platform, by exploiting the high internal bandwidth of present-day FPGAs. The proposed architecture can be used as a generic template for mapping other stream processing algorithms, taking into consideration real-world challenges.

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