A Survey of Selected Algorithms Used in Military Applications from the Viewpoints of Dataflow and GaAs

no code implementations • 30 Sep 2021 • Ilir Capuni, Veljko Milutinovic

This is a short survey of ten algorithms that are often used for military purposes, followed by analysis of their potential suitability for dataflow and GaAs, which are a specific architecture and technology for supercomputers on a chip, respectively.

A Survey on Mathematical Aspects of Machine Learning in GeoPhysics: The Cases of Weather Forecast, Wind Energy, Wave Energy, Oil and Gas Exploration

no code implementations • 5 Feb 2021 • Miroslav Kosanic, Veljko Milutinovic

This paper reviews the most notable works applying machine learning techniques (ML) in the context of geophysics and corresponding subbranches.

BIG-bench Machine Learning Geophysics

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

no code implementations • 20 Sep 2020 • Veljko Milutinovic, Erfan Sadeqi Azer, Kristy Yoshimoto, Gerhard Klimeck, Miljan Djordjevic, Milos Kotlar, Miroslav Bojovic, Bozidar Miladinovic, Nenad Korolija, Stevan Stankovic, Nenad Filipović, Zoran Babovic, Miroslav Kosanic, Akira Tsuda, Mateo Valero, Massimo De Santo, Erich Neuhold, Jelena Skoručak, Laura Dipietro, Ivan Ratkovic

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.

Distributed, Parallel, and Cluster Computing