1 citations · 1 across the 3 of their papers we have counts for
4 papers
IMPACT:InMemory ComPuting Architecture Based on Y-FlAsh Technology for Coalesced Tsetlin Machine Inference
Omar Ghazal, Wei Wang, Shahar Kvatinsky +3
The increasing demand for processing large volumes of data for machine learning models has pushed data bandwidth requirements beyond the capability of traditional von Neumann archi…
In-Memory Learning Automata Architecture using Y-Flash Cell
Omar Ghazal, Tian Lan, Shalman Ojukwu +3
The modern implementation of machine learning architectures faces significant challenges due to frequent data transfer between memory and processing units. In-memory computing, pri…
IMBUE: In-Memory Boolean-to-CUrrent Inference ArchitecturE for Tsetlin Machines
Omar Ghazal, Simranjeet Singh, Tousif Rahman +8
In-memory computing for Machine Learning (ML) applications remedies the von Neumann bottlenecks by organizing computation to exploit parallelism and locality. Non-volatile memory d…
Finite State Automata Design using 1T1R ReRAM Crossbar
Simranjeet Singh, Omar Ghazal, Chandan Kumar Jha +6
Data movement costs constitute a significant bottleneck in modern machine learning (ML) systems. When combined with the computational complexity of algorithms, such as neural netwo…