4 citations · 4 across the 5 of their papers we have counts for
6 papers
Silicon Photonic 2.5D Interposer Networks for Overcoming Communication Bottlenecks in Scale-out Machine Learning Hardware Accelerators
Febin Sunny, Ebadollah Taheri, Mahdi Nikdast +1
Modern machine learning (ML) applications are becoming increasingly complex and monolithic (single chip) accelerator architectures cannot keep up with their energy efficiency and t…
Machine Learning Accelerators in 2.5D Chiplet Platforms with Silicon Photonics
Febin Sunny, Ebadollah Taheri, Mahdi Nikdast +1
Domain-specific machine learning (ML) accelerators such as Google's TPU and Apple's Neural Engine now dominate CPUs and GPUs for energy-efficient ML processing. However, the evolut…
ReSiPI: A Reconfigurable Silicon-Photonic 2.5D Chiplet Network with PCMs for Energy-Efficient Interposer Communication
Ebadollah Taheri, Sudeep Pasricha, Mahdi Nikdast
2.5D chiplet systems have been proposed to improve the low manufacturing yield of large-scale chips. However, connecting the chiplets through an electronic interposer imposes a hig…
DeFT: A Deadlock-Free and Fault-Tolerant Routing Algorithm for 2.5D Chiplet Networks
Ebadollah Taheri, Sudeep Pasricha, Mahdi Nikdast
By interconnecting smaller chiplets through an interposer, 2.5D integration offers a cost-effective and high-yield solution to implement large-scale modular systems. Nevertheless,…
A Survey on Silicon Photonics for Deep Learning
Febin P Sunny, Ebadollah Taheri, Mahdi Nikdast +1
Deep learning has led to unprecedented successes in solving some very difficult problems in domains such as computer vision, natural language processing, and general pattern recogn…
AdEle: An Adaptive Congestion-and-Energy-Aware Elevator Selection for Partially Connected 3D NoCs
Ebadollah Taheri, Ryan G. Kim, Mahdi Nikdast
By lowering the number of vertical connections in fully connected 3D networks-on-chip (NoCs), partially connected 3D NoCs (PC-3DNoCs) help alleviate reliability and fabrication iss…