The Ultimate DataFlow for Ultimate SuperComputers-on-a-Chip, for Scientific Computing, Geo Physics, Complex Mathematics, and Information Processing

The Ultimate DataFlow for Ultimate SuperComputers-on-a-Chip, for Scientific Computing, Geo Physics, Complex Mathematics, and Information Processing

This article starts from the assumption that near future 100BTransistor SuperComputers-on-a-Chip will include N big multi-core processors, 1000N small many-core processors, a TPU-like fixed-structure systolic array accelerator for the most frequently used Machine Learning algorithms needed in bandwi...

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Hauptverfasser: Milutinovic, Veljko, Azer, Erfan Sadeqi, Yoshimoto, Kristy, Klimeck, Gerhard, Djordjevic, Miljan, Kotlar, Milos, Bojovic, Miroslav, Miladinovic, Bozidar, Korolija, Nenad, Stankovic, Stevan, Filipović, Nenad, Babovic, Zoran, Kosanic, Miroslav, Tsuda, Akira, Valero, Mateo, De Santo, Massimo, Neuhold, Erich, Skoručak, Jelena, Dipietro, Laura, Ratkovic, Ivan
Format: Artikel
Sprache:eng
Schlagworte:
Computer Science - Distributed, Parallel, and Cluster Computing
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Zusammenfassung:This article starts from the assumption that near future 100BTransistor SuperComputers-on-a-Chip will include N big multi-core processors, 1000N small many-core processors, a TPU-like fixed-structure systolic array accelerator for the most frequently used Machine Learning algorithms needed in bandwidth-bound applications and a flexible-structure reprogrammable accelerator for less frequently used Machine Learning algorithms needed in latency-critical applications.
DOI:10.48550/arxiv.2009.10593