1 citations · 2 across the 8 of their papers we have counts for
9 papers
SPARX: Secure and Privacy-Aware Approximate CNN Acceleration with Edge RISC-V SoC
Sonu Kumar, Akash Sankhe, Mukul Lokhande +1
Edge-AI systems increasingly require real-time CNN inference under strict energy, performance, security, and privacy constraints. Approximate computing improves hardware efficiency…
CARMEN: CORDIC-Accelerated Resource-Efficient Multi-Precision Inference Engine for Deep Learning
Sonu Kumar, Mukul Lokhande, Santosh Kumar Vishvakarma +1
This paper presents CARMEN, a runtime-adaptive, CORDIC-accelerated multi-precision vector engine for resource-efficient deep learning inference. The key insight is that CORDIC iter…
L-SPINE: A Low-Precision SIMD Spiking Neural Compute Engine for Resource-efficient Edge Inference
Sonu Kumar, Mukul Lokhande, Santosh Kumar Vishvakarma
Spiking Neural Networks (SNNs) offer a promising solution for energy-efficient edge intelligence; however, their hardware deployment is constrained by memory overhead, inefficient…
CORVET: A CORDIC-Powered, Resource-Frugal Mixed-Precision Vector Processing Engine for High-Throughput AIoT applications
Sonu Kumar, Mohd Faisal Khan, Mukul Lokhande +1
This brief presents a runtime-adaptive, performance-enhanced vector engine featuring a low-resource, iterative CORDIC-based MAC unit for edge AI acceleration. The proposed design e…
SPADE: A SIMD Posit-enabled compute engine for Accelerating DNN Efficiency
Sonu Kumar, Lavanya Vinnakota, Mukul Lokhande +2
The growing demand for edge-AI systems requires arithmetic units that balance numerical precision, energy efficiency, and compact hardware while supporting diverse formats. Posit a…
ReLANCE: A Resource-Efficient Low-Latency Cortical Neural Acceleration Engine
Sonu Kumar, Arjun S. Nair, Bhawna Chaudhary +2
We present a Cortical Neural Pool (CNP) architecture featuring a high-speed, resource-efficient CORDIC based Hodgkin-Huxley (RCHH) neuron model. Unlike shared CORDIC-based DNN appr…
Re-FRAME the Meeting Summarization SCOPE: Fact-Based Summarization and Personalization via Questions
Frederic Kirstein, Sonu Kumar, Terry Ruas +1
Meeting summarization with large language models (LLMs) remains error-prone, often producing outputs with hallucinations, omissions, and irrelevancies. We present FRAME, a modular…
MCP Guardian: A Security-First Layer for Safeguarding MCP-Based AI System
Sonu Kumar, Anubhav Girdhar, Ritesh Patil +1
As Agentic AI gain mainstream adoption, the industry invests heavily in model capabilities, achieving rapid leaps in reasoning and quality. However, these systems remain largely co…
HYDRA: Hybrid Data Multiplexing and Run-time Layer Configurable DNN Accelerator
Sonu Kumar, Komal Gupta, Gopal Raut +2
Deep neural networks (DNNs) offer plenty of challenges in executing efficient computation at edge nodes, primarily due to the huge hardware resource demands. The article proposes H…