Mohammad Hassani Sadi, M.Sc.
Anschrift
Erwin-Schrödinger-Straße
Gebäude 12, Raum 228
67663 Kaiserslautern
Kontakt
Telefon: (+49) 631 / 205-4803
Fax: (+49) 631 / 205-4437
Email: m.sadi(at)rptu.de
Forschungsgebiete
- Hardware Accelerators for Machine Learning
- Computer Arithmetic
Publikationen
Novel Adaptive Quantization Methodology for 8-bit Floating-Point DNN Training
M. H. Sadi, C. Sudarshan, N. Wehn. Design Automation for Embedded Systems, Springer Journal, Volume 28, pages 91–110, (2024)
A Critical Assessment of DRAM-PIM Architectures - Trends, Challenges and Solutions
C. Sudarshan, M. H. Sadi, L. Steiner, C. Weis, N. Wehn. International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS XXII), July, 2022, Samos Island, Greece.
A Weighted Current Summation based Mixed Signal DRAM-PIM Architecture for Deep Neural Network Inference
C. Sudarshan, T. Soliman, J. Lappas, C. Weis, M. H. Sadi, M. Jung, A. Guntoro, N. Wehn. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Special Issue "Revolution of AI and Machine Learning with Processing-in-Memory (PIM): from Systems, Architectures, to Circuits", June, 2022.
Optimization of DRAM based PIM Architecture for Energy-Efficient Deep Neural Network Training
C. Sudarshan, M. H. Sadi, C. Weis, N. Wehn. IEEE International Symposium on Circuits and Systems (ISCAS), May, 2022, Austin, TX, USA.
FPGA-based Trainable Autoencoder for Communication Systems
J. Ney, S. Dörner, M. Herrmann, M. H. Sadi, J. Clausius, S. ten Brink, N. Wehn. ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, February, 2022, Virtual Conference.