Deep Reinforcement Learning for Resource Constrained HLS Scheduling

Deep Reinforcement Learning for Resource Constrained HLS Scheduling

High-level synthesis (HLS) scheduling, an NP-hard problem, is a process that auto-mates VLSI design and is a very important step in silicon compilation. HLS takes as input a behavioral description of a system with a set of constraints and outputs an RTL description of a digital system. The two main...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Makhoul, Rim (author)
التنسيق: masterThesis
منشور في: 2022
الموضوعات:
Integrated circuits > Very large scale integration > Computer simulation
Reinforcement learning
Lebanese American University > Dissertations
Dissertations, Academic
الوصول للمادة أونلاين:http://hdl.handle.net/10725/13937
https://doi.org/10.26756/th.2022.419
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php
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الانترنت

http://hdl.handle.net/10725/13937
https://doi.org/10.26756/th.2022.419
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php

مواد مشابهة