3 papers
cs.AR2025
Res-DPU: Resource-shared Digital Processing-in-memory Unit for Edge-AI Workloads
Mukul Lokhande, Narendra Singh Dhakad, Seema Chouhan +2
Processing-in-memory (PIM) has emerged as the go to solution for addressing the von Neumann bottleneck in edge AI accelerators. However, state-of-the-art (SoTA) digital PIM approac…
cs.AR2025
POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration
Mukul Lokhande, Santosh Kumar Vishvakarma
The increasing complexity of AI models requires flexible hardware capable of supporting diverse precision formats, particularly for energy-constrained edge platforms. This work pre…
cs.AR2025
QForce-RL: Quantized FPGA-Optimized Reinforcement Learning Compute Engine
Anushka Jha, Tanushree Dewangan, Mukul Lokhande +1
Reinforcement Learning (RL) has outperformed other counterparts in sequential decision-making and dynamic environment control. However, FPGA deployment is significantly resource-ex…