5 papers
Accurate and Resource-Efficient Federated Continual Learning
Jebacyril Arockiaraj, Dhruv Parikh, Jayashree Adivarahan +2
Federated continual learning (FCL) must learn from distributed task streams under limited resources, such as communication, computation, memory, and label availability. Existing FC…
Efficient and Accurate Graph Classification with Hyperdimensional Computing on FPGA
Jebacyril Arockiaraj, Dhruv Parikh, Viktor Prasanna
Real-time, energy-efficient inference on edge devices is essential for graph classification across a range of applications. Hyperdimensional Computing (HDC) is a brain-inspired com…
ImageHD: Energy-Efficient On-Device Continual Learning of Visual Representations via Hyperdimensional Computing
Jebacyril Arockiaraj, Dhruv Parikh, Viktor Prasanna
On-device continual learning (CL) is critical for edge AI systems operating on non-stationary data streams, but most existing methods rely on backpropagation or exemplar-heavy clas…
System-Level Performance Modeling of Photonic In-Memory Computing
Jebacyril Arockiaraj, Sasindu Wijeratne, Sugeet Sunder +4
Photonic in-memory computing is a high-speed, low-energy alternative to traditional transistor-based digital computing that utilizes high photonic operating frequencies and bandwid…
Primitive-Driven Acceleration of Hyperdimensional Computing for Real-Time Image Classification
Dhruv Parikh, Jebacyril Arockiaraj, Viktor Prasanna
Hyperdimensional Computing (HDC) represents data using extremely high-dimensional, low-precision vectors, termed hypervectors (HVs), and performs learning and inference through lig…