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Akademický článek

Fault Tolerant Distributed Python Software Transactional Memory

Autor: POPOVIC, M., BASICEVIC, I., DJUKIC, M.

Publikováno v: Advances in Electrical and Computer Engineering, Vol 20, Iss 4, Pp 19-28 (2020)

Much of the previous research has been done on distributed software transactional memories targeting data centers in Internet clouds, which resulted in nondeterministic and nonrealtime middleware solutions mainly written in Java and C++. On the oth

Externí odkaz: https://doaj.org/article/ca92b9c7a73646ec89a4e85e5409b4c7

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Akademický článek

An Automatic Instruction-Level Parallelization of Machine Code

Autor: MARINKOVIC, V., POPOVIC, M., DJUKIC, M.

Publikováno v: Advances in Electrical and Computer Engineering, Vol 18, Iss 1, Pp 27-36 (2018)

Prevailing multicores and novel manycores have made a great challenge of modern day - parallelization of embedded software that is still written as sequential. In this paper, automatic code parallelization is considered, focusing on developing a pa

Externí odkaz: https://doaj.org/article/379cded5f2f44b39affd4ab139554997

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A hybrid quantum-classical fusion neural network to improve protein-ligand binding affinity predictions for drug discovery

Autor: Domingo, L., Chehimi, M., Banerjee, S., Yuxun, S. He, Konakanchi, S., Ogunfowora, L., Roy, S., Selvaras, S., Djukic, M., Johnson, C.

The field of drug discovery hinges on the accurate prediction of binding affinity between prospective drug molecules and target proteins, especially when such proteins directly influence disease progression. However, estimating binding affinity deman

Externí odkaz: http://arxiv.org/abs/2309.03919

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Akademický článek

Embedded Processor Oriented Compiler Infrastructure

Autor: DJUKIC, M., POPOVIC, M., CETIC, N., POVAZAN, I.

Publikováno v: Advances in Electrical and Computer Engineering, Vol 14, Iss 3, Pp 123-130 (2014)

In the recent years, research of special compiler techniques and algorithms for embedded processors broaden the knowledge of how to achieve better compiler performance in irregular processor architectures. However, industrial strength compilers, be

Externí odkaz: https://doaj.org/article/b3ae8b246f754377bbb8f89ae91a00a8

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Hybrid quantum-classical convolutional neural networks to improve molecular protein binding affinity predictions

Autor: Domingo, L., Djukic, M., Johnson, C., Borondo, F.

One of the main challenges in drug discovery is to find molecules that bind specifically and strongly to their target protein while having minimal binding to other proteins. By predicting binding affinity, it is possible to identify the most promisin

Externí odkaz: http://arxiv.org/abs/2301.06331

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