Acknowledgements

The development of IIDEAA tools has been involving a great amount of other external projects, including:

• The LLVM Compiler Infrastructure
• The ParadisEO framework

The LLVM project is licensed under the UIUC/NCSA license. To read more about this license, please visit: http://llvm.org

ParadisEO is released under the CeCILL license. To read a copy of this license, please visit: http://www.cecill.info

Conversely, IIDEAA tools are released under the GNU Affero General Public License v3.0. To read a copy of this license, please visit: https://www.gnu.org/licenses/agpl-3.0.html

The team

IIDEAA tools are realized by people and master-students within the Embedded Laboratory of the Department of Electrical Engineering and Information Technologies - University of Naples Federico II. The project leader is Mario Barbareschi.

Main developers:

• Salvatore Barone
• Federico Iannucci
• Pierpaolo Bagnasco
• Antonio Tammaro

Main collaborators:

• Alberto Bosio
• Antonino Mazzeo

Dissemination

The approximation-by-mutation was introduced first in Q3 of 2015 and publicily released during the Q2 of 2016. So far, IIDEAA tools have been presented during several events and conferences.

The scientific results given by IIDEAA are published in the following papers:

1. Barbareschi, Mario, Federico Iannucci, and Antonino Mazzeo. "Automatic design space exploration of approximate algorithms for big data applications." Advanced Information Networking and Applications Workshops (WAINA), 2016 30th International Conference on. IEEE, 2016.
2. Barbareschi, Mario, Federico Iannucci, and Antonino Mazzeo. "An extendible design exploration tool for supporting approximate computing techniques." Design and Technology of Integrated Systems in Nanoscale Era (DTIS), 2016 International Conference on. IEEE, 2016.
3. Barbareschi, Mario, Federico Iannucci, and Antonino Mazzeo. "A Pruning Technique for B&B Based Design Exploration of Approximate Computing Variants." VLSI (ISVLSI), 2016 IEEE Computer Society Annual Symposium on. IEEE, 2016.
4. Salvatore Barone, Marcello Traiola, Mario Barbareschi and Alberto Bosio. "Multi-Objective Application-driven Approximate Design Method" in IEEE Access, 2021, doi: 10.1109/ACCESS.2021.3087858.

Other publications:

1. Amelino, Domenico, et al. "Implementing Approximate Computing Techniques by Automatic Code Mutation." WAPCO (WAPCO 2017) 3rd Workshop On Approximate Computing In conjunction with HiPEAC, 2017
2. Wali, Imran et al. "Approximate Computing: Design & Test for Integrated Circuits." LATS (LATS2017) 18th IEEE Latin American Test Symposium, 2017.