This paper leverages " XNOROP" to define and solve two critical tasks in BNNs. The first task, referred to as the "Forward Task", involves estimating the inference rate of a given model when deployed on a specific target device . The second task, known as the "Inverse Task", outlines a systematic procedure to identify a set of target devices capable of achieving a required inference rate when deploying the model . Additionally, we extend the foundational formula of "XNOROP" and introduce “LXNOROP” which incorporates considerations for memory access time, enhancing its applicability for real-world deployment scenarios.

Шаккуф А. (науч. рук. Громов В.С.) Forward and inverse tasks for inference rate estimation in binary neural networks // Сборник тезисов докладов конгресса молодых ученых. Электронное издание. – СПб: Университет ИТМО, [2025]. URL: https://kmu.itmo.ru/digests/article/15191