45 citations · 214 across the 86 of their papers we have counts for
5 papers · 2 filters
Optical Computing for Deep Neural Network Acceleration: Foundations, Recent Developments, and Emerging Directions
Sudeep Pasricha
Emerging artificial intelligence applications across the domains of computer vision, natural language processing, graph processing, and sequence prediction increasingly rely on dee…
ARTEMIS: A Mixed Analog-Stochastic In-DRAM Accelerator for Transformer Neural Networks
Salma Afifi, Ishan Thakkar, Sudeep Pasricha
Transformers have emerged as a powerful tool for natural language processing (NLP) and computer vision. Through the attention mechanism, these models have exhibited remarkable perf…
OPIMA: Optical Processing-In-Memory for Convolutional Neural Network Acceleration
Febin Sunny, Amin Shafiee, Abhishek Balasubramaniam +2
Recent advances in machine learning (ML) have spotlighted the pressing need for computing architectures that bridge the gap between memory bandwidth and processing power. The adven…
Silicon Photonic 2.5D Interposer Networks for Overcoming Communication Bottlenecks in Scale-out Machine Learning Hardware Accelerators
Febin Sunny, Ebadollah Taheri, Mahdi Nikdast +1
Modern machine learning (ML) applications are becoming increasingly complex and monolithic (single chip) accelerator architectures cannot keep up with their energy efficiency and t…
Accelerating Neural Networks for Large Language Models and Graph Processing with Silicon Photonics
Salma Afifi, Febin Sunny, Mahdi Nikdast +1
In the rapidly evolving landscape of artificial intelligence, large language models (LLMs) and graph processing have emerged as transformative technologies for natural language pro…