55 citations · 66 across the 10 of their papers we have counts for
4 papers · 1 filter
Chiplet-Gym: Optimizing Chiplet-based AI Accelerator Design with Reinforcement Learning
Kaniz Mishty, Mehdi Sadi
Modern Artificial Intelligence (AI) workloads demand computing systems with large silicon area to sustain throughput and competitive performance. However, prohibitive manufacturing…
System and Design Technology Co-optimization of SOT-MRAM for High-Performance AI Accelerator Memory System
Kaniz Mishty, Mehdi Sadi
SoCs are now designed with their own AI accelerator segment to accommodate the ever-increasing demand of Deep Learning (DL) applications. With powerful MAC engines for matrix multi…
Designing Efficient and High-performance AI Accelerators with Customized STT-MRAM
Kaniz Mishty, Mehdi Sadi
In this paper, we demonstrate the design of efficient and high-performance AI/Deep Learning accelerators with customized STT-MRAM and a reconfigurable core. Based on model-driven d…
Special Session: Reliability Analysis for ML/AI Hardware
Shamik Kundu, Kanad Basu, Mehdi Sadi +4
Artificial intelligence (AI) and Machine Learning (ML) are becoming pervasive in today's applications, such as autonomous vehicles, healthcare, aerospace, cybersecurity, and many c…