4 citations · 6 across the 7 of their papers we have counts for
8 papers
Sustainable Transformer Neural Network Acceleration with Stochastic Photonic Computing
S. Afifi, O. Alo, I. Thakkar +1
Transformers achieve state-of-the-art performance in natural language processing, vision, and scientific computing, but demand high computation and memory. To address these challen…
Accelerating Diffusion Models for Generative AI Applications with Silicon Photonics
Tharini Suresh, Salma Afifi, Sudeep Pasricha
Diffusion models have revolutionized generative AI, with their inherent capacity to generate highly realistic state-of-the-art synthetic data. However, these models employ an itera…
PhotoGAN: Generative Adversarial Neural Network Acceleration with Silicon Photonics
Tharini Suresh, Salma Afifi, Sudeep Pasricha
Generative Adversarial Networks (GANs) are at the forefront of AI innovation, driving advancements in areas such as image synthesis, medical imaging, and data augmentation. However…
SafeLight: Enhancing Security in Optical Convolutional Neural Network Accelerators
Salma Afifi, Ishan Thakkar, Sudeep Pasricha
The rapid proliferation of deep learning has revolutionized computing hardware, driving innovations to improve computationally expensive multiply-and-accumulate operations in deep…
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…
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…
GHOST: A Graph Neural Network Accelerator using Silicon Photonics
Salma Afifi, Febin Sunny, Amin Shafiee +2
Graph neural networks (GNNs) have emerged as a powerful approach for modelling and learning from graph-structured data. Multiple fields have since benefitted enormously from the ca…
TRON: Transformer Neural Network Acceleration with Non-Coherent Silicon Photonics
Salma Afifi, Febin Sunny, Mahdi Nikdast +1
Transformer neural networks are rapidly being integrated into state-of-the-art solutions for natural language processing (NLP) and computer vision. However, the complex structure o…