5 citations · 6 across the 12 of their papers we have counts for
13 papers
SparseCraft: Agentic Hardware-Software Co-Optimization for Sparse Computing
Rajatabha Chakraborty, M P Samartha, Vedant Pahariya +1
Sparse-accelerator design spaces are usually searched against analytical models, so a design point is admitted on what a model predicts rather than on what the hardware does. Spars…
ProbSplat: Efficient Probabilistic Hardware for Gaussian Splatting in 3D Scene Reconstruction
Siddarth Gottumukkula, M P Samartha, Vedant Pahariya +3
This paper presents ProbSplat, a Compute-in-Memory (CIM)-inspired architecture based on programmable and energy efficient floating-gate inverter columns for probabilistic computing…
Phase Matters: Characterizing Heterogeneous Vision-Language Inference on a Mobile SoC
Aryama V Murthy, Yashas N Kotre, Prathmesh Sharma +3
Recent phone-class mobile SoCs expose practical NPU execution paths for on-device vision-language model (VLM) inference, but developers still lack phase-level guidance for mapping…
TernaryLM: Memory-Efficient Language Modeling via Native 1.5-Bit Quantization with Adaptive Layer-wise Scaling
Nisharg Nargund, Priyesh Shukla
Large language models (LLMs) achieve remarkable performance but demand substantial computational resources, limiting deployment on edge devices and resource-constrained environment…
Semantic-Guided 3D Gaussian Splatting for Transient Object Removal
Aditi Prabakaran, Priyesh Shukla
Transient objects in casual multi-view captures cause ghosting artifacts in 3D Gaussian Splatting (3DGS) reconstruction. Existing solutions relied on scene decomposition at signifi…
Dual-Signal Adaptive KV-Cache Optimization for Long-Form Video Understanding in Vision-Language Models
Vishnu Sai, Dheeraj Sai, Srinath B +2
Vision-Language Models (VLMs) face a critical memory bottleneck when processing long-form video content due to the linear growth of the Key-Value (KV) cache with sequence length. E…
Bidirectional Quantum Processor Interfacing by a 4-Kelvin Analog Signal Chain for Superconducting Qubit Control and Quantum State Readout
Deepak R, Lokendra Kanawat, Jayadeep K +1
This paper presents a comprehensive cryogenic analog signal processing architecture designed for superconducting qubit control and quantum state readout operating at 4 Kelvin. The…
Navigating the Unknown: Uncertainty-Aware Compute-in-Memory Autonomy of Edge Robotics
Nastaran Darabi, Priyesh Shukla, Dinithi Jayasuriya +3
This paper addresses the challenging problem of energy-efficient and uncertainty-aware pose estimation in insect-scale drones, which is crucial for tasks such as surveillance in co…
Robust Monocular Localization of Drones by Adapting Domain Maps to Depth Prediction Inaccuracies
Priyesh Shukla, Sureshkumar S., Alex C. Stutts +3
We present a novel monocular localization framework by jointly training deep learning-based depth prediction and Bayesian filtering-based pose reasoning. The proposed cross-modal f…
MC-CIM: Compute-in-Memory with Monte-Carlo Dropouts for Bayesian Edge Intelligence
Priyesh Shukla, Shamma Nasrin, Nastaran Darabi +2
We propose MC-CIM, a compute-in-memory (CIM) framework for robust, yet low power, Bayesian edge intelligence. Deep neural networks (DNN) with deterministic weights cannot express t…
Probabilistic Localization of Insect-Scale Drones on Floating-Gate Inverter Arrays
Priyesh Shukla, Ankith Muralidhar, Nick Iliev +3
We propose a novel compute-in-memory (CIM)-based ultra-low-power framework for probabilistic localization of insect-scale drones. The conventional probabilistic localization approa…
Low Power Unsupervised Anomaly Detection by Non-Parametric Modeling of Sensor Statistics
Ahish Shylendra, Priyesh Shukla, Saibal Mukhopadhyay +2
This work presents AEGIS, a novel mixed-signal framework for real-time anomaly detection by examining sensor stream statistics. AEGIS utilizes Kernel Density Estimation (KDE)-based…
: Markov Chain Monte Carlo Sampling in SRAM for Fast Bayesian Inference
Priyesh Shukla, Ahish Shylendra, Theja Tulabandhula +1
This work discusses the implementation of Markov Chain Monte Carlo (MCMC) sampling from an arbitrary Gaussian mixture model (GMM) within SRAM. We show a novel architecture of SRAM…