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News
October 1, 2026
HSE Researchers Show How Congenital Motor Disorders Affect Brain Development
Researchers from HSE University’s Institute for Cognitive Neuroscience have synthesised the findings of their previous studies on brain development in children with obstetric brachial plexus palsy and arthrogryposis. Their analysis shows that impaired motor function in early childhood not only limits children’s motor experience but also affects memory, categorical thinking, and information processing. The study has been published in Frontiers in Psychology.
October 1, 2026
Window into the Body: Scientists Develop Neural Network to Detect Risk of 15 Diseases from Retinal Images
Russian universities, with the participation of HSE University, Sber, and Z-union, have developed a neural network that can simultaneously assess the risk of 15 types of pathology from retinal photographs, including not only eye diseases but also cardiovascular conditions. The AI system can help clinicians detect potentially concerning changes at an early stage, identify signs reflecting the condition of retinal blood vessels, and determine whether a patient may need further examination. The paper has been published in Frontiers in Medicine.
September 30, 2026
'We Did Not Limit the Time for Questions'
The International Laboratory for Supercomputer Atomistic Modelling and Multi-Scale Analysis at HSE University held a major conference on molecular dynamics. Participants had the opportunity to attend all the presentations, while speakers were given as much time as they needed to answer questions. The HSE News Service interviewed Grigory Smirnov, Head of the Laboratory, and Genri Norman, Chief Research Fellow, about the conference preparations and the discussions it generated.

 

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Методы преобразования параллелизма в процессе высокоуровневого синтеза СБИС

Моделирование и анализ информационных систем. 2022. Т. 29. № 1. С. 60–72.
Рыженко И. Н., Непомнящий О. В., Легалов А. И., Шайдуров В. В.

In this paper methods for increasing the efficiency of VLSI development based on the method of architecture-independent design are proposed. The route of high-level VLSI synthesis is considered. The principle of constructing a VLSI hardware model based on the functional-flow programming paradigm is stated.
The results of the development of methods and algorithms for transformation functional-parallel programs into programs in HDL languages that support the design process of digital chips are presented. The principles of assessment are considered and the classes of resources required for the analysis of design solutions are identified. Reduction coefficients and methods of their calculation for each resource class have been introduced. An algorithm for calculating the reduction coefficients and estimating the required resources is proposed. An algorithm for converting parallelism is proposed, taking into account the specified constraints of the target platform. A mechanism for the exchange of metrics with an architecture-dependent level has been developed. Examples of parallelism reduction for the FPGA platform and practical implementation of FFT algorithms in the Virtex® UltraScale FPGA basis are given. The developed methods and algorithms make it possible to use the method of architecture-independent synthesis for transferring VLSI projects to various architectures by changing the parallelism of the circuit and equivalent transformations of parallel programs. The proposed approach provides many options for hardware solutions for implementation on various target platforms.

Research target: Computer Science
Language: Russian
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Keywords: VLSIdataflowпараллельные вычисленияparallel computingfunctional programmingВысокоуровневый синтезфункционально-потоковое параллельное программированиеhigh-level synthesisпотоки данныхцифровая интегральная схема
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