Hari Subramoni

MCR-DL: Mix-and-Match Communication Runtime for Deep Learning

2023

In recent years, the training requirements of many state-of-the-art Deep Learning (DL) models have scaled beyond the compute and memory capabilities of a single processor, and necessitated distribution among processors. Training such massive models necessitates …

Flover: A Temporal Fusion Framework for Efficient Autoregressive Model Parallel Inference

2023

Autoregressive models, despite their commendable performance in a myriad of generative tasks, face challenges stemming from their inherently sequential structure. Inference on these models, by design, harnesses a temporal dependency, where the current token's probability …