63 citations · 118 across the 10 of their papers we have counts for
12 papers
Profile-Guided Parallel Task Extraction and Execution for Domain Specific Heterogeneous SoC
Liangliang Chang, Joshua Mack, Benjamin Willis +4
In this study, we introduce a methodology for automatically transforming user applications in the radar and communication domain written in C/C++ based on dynamic profiling to a pa…
Proactively Predicting Dynamic 6G Link Blockages Using LiDAR and In-Band Signatures
Shunyao Wu, Chaitali Chakrabarti, Ahmed Alkhateeb
Line-of-sight link blockages represent a key challenge for the reliability and latency of millimeter wave (mmWave) and terahertz (THz) communication networks. To address this chall…
ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning
Jingtao Li, Adnan Siraj Rakin, Xing Chen +3
This work aims to tackle Model Inversion (MI) attack on Split Federated Learning (SFL). SFL is a recent distributed training scheme where multiple clients send intermediate activat…
SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks
Gokul Krishnan, Sumit K. Mandal, Manvitha Pannala +4
In-memory computing (IMC) on a monolithic chip for deep learning faces dramatic challenges on area, yield, and on-chip interconnection cost due to the ever-increasing model sizes.…
Versa: A Dataflow-Centric Multiprocessor with 36 Systolic ARM Cortex-M4F Cores and a Reconfigurable Crossbar-Memory Hierarchy in 28nm
Sung Kim, Morteza Fayazi, Alhad Daftardar +10
We present Versa, an energy-efficient processor with 36 systolic ARM Cortex-M4F cores and a runtime-reconfigurable memory hierarchy. Versa exploits algorithm-specific characteristi…
Impact of On-Chip Interconnect on In-Memory Acceleration of Deep Neural Networks
Gokul Krishnan, Sumit K. Mandal, Chaitali Chakrabarti +3
With the widespread use of Deep Neural Networks (DNNs), machine learning algorithms have evolved in two diverse directions -- one with ever-increasing connection density for better…