A simple "embedded" reasoning inference engine with application example in the X-ray Photoelectron Spectroscopy. - János Végh (Comput. Phys. Commun., 2004)

A Multicore-aware Von Neumann Programming Model. - János Végh; Zsolt Bagoly; Ádám Kicsák; Péter Molnár (ICSOFT EA, 2014)

An Alternative Implementation for Accelerating Some Functions of Operating System. - János Végh; Ádám Kicsák; Zsolt Bagoly; Péter Molnár (ICSOFT EA, 2014)

A configurable accelerator for manycores: the Explicitly Many-Processor Approach. - János Végh (CoRR, 2016)

Comments on the parallelization efficiency of the Sunway TaihuLight supercomputer. - János Végh (CoRR, 2016)

A new kind of parallelism and its programming in the Explicitly Many-Processor Approach. - János Végh (CoRR, 2016)

Can Broken Multicore Hardware be Mended? - János Végh (CoRR, 2016)

A figure of merit for describing the performance of scaling of parallelization. - János Végh; Péter Molnár; József Vásárhelyi (CoRR, 2016)

How Amdahl's low restricts supercomputer applications and building ever bigger supercomputers. - János Végh (CoRR, 2017)

Statistical considerations on limitations of supercomputers. - János Végh (CoRR, 2017)

Renewing computing paradigms for more efficient parallelization of single-threads. - János Végh (CoRR, 2018)

Limitations of performance of Exascale Applications and supercomputers they are running on. - János Végh (CoRR, 2018)

Introducing the explicitly many-processor approach. - János Végh (Parallel Comput., 2018)

The performance wall of parallelized sequential computing: the dark performance and the roofline of performance gain. - János Végh (CoRR, 2019)

Classic versus modern computing: analogies with classic versus modern physics. - János Végh (CoRR, 2019)

Finally, how many efficiencies the supercomputers have? And, what do they measure? - János Végh (CoRR, 2020)

Re-evaluating scaling methods for distributed parallel systems. - János Végh (CoRR, 2020)

How deep the machine learning can be. - János Végh (CoRR, 2020)

Do we know the operating principles of our computers better than those of our brain? - János Végh; Ádám József Berki (CoRR, 2020)

Which scaling rule applies to Artificial Neural Networks. - János Végh (CoRR, 2020)

How to extend the Single-Processor Paradigm to the Explicitly Many-Processor Approach. - János Végh (CoRR, 2020)

Introducing temporal behavior to computing science. - János Végh (CoRR, 2020)

On the spatiotemporal behavior in biology-mimicking computing systems. - János Végh; Ádám József Berki (CoRR, 2020)

von Neumann's missing "Second Draft": what it should contain. - János Végh (CoRR, 2020)

Finally, how many efficiencies the supercomputers have? - János Végh (J. Supercomput., 2020)

Why Learning and Machine Learning Are Different. - János Végh; Ádám József Berki (Adv. Artif. Intell. Mach. Learn., 2021)

Revising the Classic Computing Paradigm and Its Technological Implementations. - János Végh (Informatics, 2021)

Which scaling rule applies to large artificial neural networks. - János Végh (Neural Comput. Appl., 2021)

Towards Generalizing the Information Theory for Neural Communication. - János Végh; Ádám József Berki (Entropy, 2022)