Prof. Freddy Gabbay

Dean of Faculty of Engineering
Faculty of Engineering
Prof. Freddy Gabbay

Building 14, Dean's Office

Research

  • Computer Architecture
  • Hardware accelerators
  • Artificial Intelligence and Machine Learning
  • VLSI design:Design, Synthesis and Place-and-route
  • VLSI design:Advanced process technology
  • VLSI design: Reliability and high-volume manufacturing

Publications

A. Karbachevsky, C. Baskin, E. Zheltonozhskii, Y. Yermolin, F. Gabbay, A. Bronstein, A. Mendelson, Early-Stage Neural Network Hardware Performance Analysis. Sustainability,vol. 13, no. 717, 2021.​

F. Gabbay, A. Mendelson. Asymmetric Aging Effect on Modern Microprocessors. Microelectronics Reliability. vol. 119, 2021, 114090.  ISSN 0026-2714

F. Gabbay and G. Shomron. Compression of Neural Networks for Specialized Tasks via Value Locality. Mathematics, vol. 9, no. 20: 2612, 2021.

F. Gabbay, S. Bar-Lev, O. Montano and N. Hadad. A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients. Appl. Sci. 2021, 11, 10417.

F. Gabbay, A. Mendelson, B. Salameh and M. Ganaiem, F. Gabbay, A. Mendelson, B. Salameh and M. Ganaiem, A Design Flow and Tool for Avoiding Asymmetric Aging, in IEEE Design & Test, vol. 39, no. 6, 2022, pp. 111-118.

F. Gabbay, B. Salomon and G. Shomron. Structured Compression of Convolutional Neural Networks for Specialized Tasks Mathematics, VOL. 10, no. 19, 2022: 3679...

F. Gabbay, Ori Schweitzer and Rotem Lev Aharoni. Deep Neural Network Memory Performance and Throughput Modeling and Simulation Framework. Mathematics 2022, 10, 4144.

F. Gabbay; A. Mendelson. Electromigration-Aware Architecture for Modern Microprocessors. J. Low Power Electronics and Applications, vol. 13, no. 7., 2023.

S. Kurzum, G. Shomron, F. Gabbay and U. Weiser, Enhancing DNN Training Efficiency Via Dynamic Asymmetric Architecture, in IEEE Computer Architecture Letters, vol. 22, no. 1, pp. 49-52, Jan.-June 2023.

A. Mendelson, A. Shoufan, K. Belwafi, H. Al Hamadi, A. Ahmed, F. Gabbay, M. S. Sandro, P. Ozgur, S. R. Psiakis, J. Lukkarila, K. Basu, M. Hassan, A. Acquaviva, A. Bartolini Francesco, B. E. Parisi, D. Rossi, S. Sugumar, L. Benini, M Bertogna and S. Thakkar. Leveraging RISC-V in Combatting Vulnerabilities in Autonomous Systems. IEEE Spectrum. May 2023.

F. Gabbay and A. Mendelson. Electromigration-Aware Memory Hierarchy Architecture. J. Low Power Electron. Appl. 2023, 13, 44.

F. Gabbay, A. Mendelson, B. Salameh and M. Ganaiem, Asymmetric Aging Avoidance EDA Tool. In Proceedings of the 2021 34th SBC/SBMicro/IEEE/ACM Symposium on Integrated Circuits and Systems Design (SBCCI), 2021, pp. 1-6.

G. Shomron, F. Gabbay, S. Kurzum and U. Weiser, Post-Training Sparsity-Aware Quantization. In Proceedings of the Thirty-Fifth Conference on Neural Information Processing System, NeurIPS, vol. 34, 2021.

F. Gabbay, Y. Stav, B. Salomon, R. Cohen, RISC-V and Machine Learning Accelerator Hackathon – Enhancing Undergraduate Student's Perception of Essential Chip Design Skills. In Proceedings of the 16th Annual International Technology, Education and Development Conference, Valencia, pp. 2921-2926, 2022, INTED 2022.

F. Gabbay and A. Mendelson, Electromigration-Aware Instruction Execution for Modern Microprocessors. In Proceedings of the 4th International Conference on Microelectronic Device and Technologies (MicDAT '2022), pp. 60-66, 2022.

F. Gabbay, F. Ramadan, M. Ganaiem , Ofrie Rosenthal and Lior Bashari. The Effect of Transistor Aging on GPGPUs. In Proceedings of the 5th International Conference on Microelectronic Device and Technologies (MicDAT '2023)