9 papers
DVA-Neurons: Design and Verification of Adaptive LIF Neurons: From Single-Neuron Dynamics to Multi-Neuron Spiking Networks
Thanh Pham, Riadul Islam
Spiking Neural Networks (SNNs) offer a promising path toward ultra-low-power artificial intelligence inference by emulating the event-driven computation of biological neurons. Howe…
LiteEvent-AE: Lightweight Autoencoder for Event-Based Vision on Low-Latency Energy-Constrained Edge Devices
Riadul Islam, Joey Mule, Dhandeep Challagundla +3
Event-based vision has emerged as a promising paradigm for energy-aware artificial intelligence (AI), offering sparse, low-latency visual signals that reduce redundant data process…
Time--to--Digital Converter (TDC)--Based Resonant Compute--in--Memory for INT8 CNNs with Layer--Optimized SRAM Mapping
Dhandeep Challagundla, Ignatius Bezzam, Riadul Islam
In recent years, Compute-in-memory (CiM) architectures have emerged as a promising solution for deep neural network (NN) accelerators. Multiply-accumulate~(MAC) is considered a {\t…
TSPC-PFD: TSPC-Based Low-Power High-Resolution CMOS Phase Frequency Detector
Dhandeep Challagundla, Venkata Krishna Vamsi Sundarapu, Ignatius Bezzam +1
Phase Frequency Detectors (PFDs) are essential components in Phase-Locked Loop (PLL) and Delay-Locked Loop (DLL) systems, responsible for comparing phase and frequency differences…
EA: An Event Autoencoder for High-Speed Vision Sensing
Riadul Islam, Joey Mulé, Dhandeep Challagundla +2
High-speed vision sensing is essential for real-time perception in applications such as robotics, autonomous vehicles, and industrial automation. Traditional frame-based vision sys…
PGR-DRC: Pre-Global Routing DRC Violation Prediction Using Unsupervised Learning
Riadul Islam, Dhandeep Challagundla
Leveraging artificial intelligence (AI)-driven electronic design and automation (EDA) tools, high-performance computing, and parallelized algorithms are essential for next-generati…
Event-Based Crossing Dataset (EBCD)
Joey Mulé, Dhandeep Challagundla, Rachit Saini +1
Event-based vision revolutionizes traditional image sensing by capturing asynchronous intensity variations rather than static frames, enabling ultrafast temporal resolution, sparse…
Architectural Exploration of Application-Specific Resonant SRAM Compute-in-Memory (rCiM)
Dhandeep Challagundla, Ignatius Bezzam, Riadul Islam
While general-purpose computing follows Von Neumann's architecture, the data movement between memory and processor elements dictates the processor's performance. The evolving compu…
Descriptor: Face Detection Dataset for Programmable Threshold-Based Sparse-Vision
Riadul Islam, Sri Ranga Sai Krishna Tummala, Joey Mulé +5
Smart focal-plane and in-chip image processing has emerged as a crucial technology for vision-enabled embedded systems with energy efficiency and privacy. However, the lack of spec…