Artem Grigorovich, a graduate of NSU’s Department of Information Technologies, developed a performance evaluation module that supports the launch of test algorithms used in blockchain technology on several quantum platforms simultaneously. This will help developers track the progress of existing quantum platforms and use the most productive to solve blockchain mining problems.
Growth in the performance of computing systems has started to slow down. The laws of quantum mechanics dictate that reducing the size of transistors cannot continue indefinitely. Recently, parallel computing systems have been used to achieve performance gains. However, not every algorithm lends itself to parallelization, and there is also a limit on the growth of supercomputer performance. Computers specializing in a certain class of tasks maximizes gains in work speed. Using quantum computers enumeration and factorization problems used in cryptography are solved much more efficiently.
Grigorovich explained the significance of his work,
The idea for this research arose in the course of analyzing the latest achievements in the field of quantum computing. Currently, work is underway to create quantum computers, and developers of quantum platforms provide open access to them. There is a need to run test problems on different quantum computers and compare quantum platforms. This raises the challenge of creating test problems to assess the performance of platforms, as well as specialized software that automates comparative analysis. In the studies published so far, quantum chemistry problems are used for performance testing. The algorithms considered in my work will evaluate the performance of quantum computers solving cryptographic problems.
This research included analysis of existing quantum platforms and proposing algorithms and metrics to evaluate the performance. The resulting software conducts performance tests and provides tools for analyzing the results that allows tracking the development of platforms focused on quantum computing. The results were presented at the International Scientific Student Conference - 2020 in the “Instrumental and Applied Software Systems" section.
