4 papers · 1 filter
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…
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…