Product Details

autoAx: An Open-Source Automated Design Space Exploration Framework for Approximate Accelerators in FPGAs and ASICs

Created: 2023

Czech title
autoAx: Automatizovaný framework pro automatické prohledávání návrhového prostoru pro aproximativní akcelerátory v obvodech FPGA a ASIC s otevřeným zdrojovým kódem
Type
software
License
Use of the result by another entity is possible without acquiring a license (the result is not licensed)
License Fee
The licensor does not require a license fee for the result
Authors
Keywords

approximate computing, high level synthesis, machine learning

Description

The automated generation of approximate circuits and accelerators has been a useful design strategy to achieve energy efficiency and/or performance improvements. In this work, we propose a framework, autoAx, that leverages machine learning models that evaluate the state-of-the-art approximate components to explore the architecture space effectively. These accelerators are modeled at RTL and optimized using an evolutionary algorithm. The AutoAx framework is extensible, open-source, and can assist in exploring new directions in high-level approximation. 

Location
License Conditions
Projects
Application-specific HW/SW architectures and their applications, BUT, Vnitřní projekty VUT, FIT-S-23-8141, 2023-2026, running
Research groups
Departments
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