3 papers indexed
Vibhanshu Sharma, Pratyush Dhingra, Janardhan Rao Doppa, Partha Pratim Pande
Processing-In-Memory (PIM) has emerged as a promising technology for accelerating machine learning (ML) workloads. Specifically, non-volatile memory-based PIM architectures have enabled effective ML acceleration due to their ability to perform energy-efficient matrix-vector multi…
Pratyush Dhingra, Pramit Kumar Pal, Janardhan Rao Doppa, Partha Pratim Pande
Mixture of Experts (MoE) architectures have emerged as a dominant paradigm for scaling Large Language Models (LLMs). However, MoE inference on conventional hardware is constrained by three fundamental bottlenecks. These encompass the massive memory bandwidth required to fetch non…
Yassine Chemingui, Chenhua Fan, Honghao Wei, Janardhan Rao Doppa
Safe reinforcement learning typically enforces safety by bounding expected cumulative costs, a criterion that often fails to detect rare but catastrophic tail events. To overcome these limitations, this paper introduces SteinGate, a boundary-aware distributional safety certificat…