Miloš Kotlar

Miloš Kotlar

Miloš Kotlar received his B.Sc. (2016) and M.Sc. (2017) degrees in Electrical and Computer Engineering from the University of Belgrade, School of Electrical Engineering, Serbia. He is a Ph.D. candidate at the School of Electrical Engineering, University of Belgrade. His general research interests include implementation of energy efficient tensor implementations using the dataflow paradigm (FPGA and ASIC accelerators) and meta learning approaches for anomaly detection tasks.

Publications

Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
Veljko Milutinović, Nenad Mitić, Aleksandar Kartelj, Miloš Kotlar. © 2022. 296 pages.
Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural...
Handbook of Research on Methodologies and Applications of Supercomputing
Handbook of Research on Methodologies and Applications of Supercomputing
Veljko Milutinović, Miloš Kotlar. © 2021. 393 pages.
As computers continue to remain essential tools for the pursuit of physics, medicine, economics, social sciences, and more, supercomputers are proving that they can further...
An Introduction to Controlflow and Dataflow Supercomputing
An Introduction to Controlflow and Dataflow Supercomputing
Miloš Kotlar. © 2021. 4 pages.
In the controlflow paradigm, based on the finite automata theory, one writes a program in order to control the flow of data through the hardware. In the dataflow paradigm, one...
The Ultimate Data Flow for Ultimate Super Computers-on-a-Chip
The Ultimate Data Flow for Ultimate Super Computers-on-a-Chip
Veljko Milutinović, Miloš Kotlar, Ivan Ratković, Nenad Korolija, Miljan Djordjevic, Kristy Yoshimoto, Mateo Valero. © 2021. 7 pages.
This chapter 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...