4 papers
Distributed Hybrid Parallelism for Large Language Models: Comparative Study and System Design Guide
Hossam Amer, Rezaul Karim, Ali Pourranjbar +3
With the rapid growth of large language models (LLMs), a wide range of methods have been developed to distribute computation and memory across hardware devices for efficient traini…
EPAS: Efficient Training with Progressive Activation Sharing
Rezaul Karim, Maryam Dialameh, Yang Liu +2
We present a novel method for Efficient training with Progressive Activation Sharing (EPAS). This method bridges progressive training paradigm with the phenomenon of redundant QK (…
ECHO-LLaMA: Efficient Caching for High-Performance LLaMA Training
Maryam Dialameh, Rezaul Karim, Hossein Rajabzadeh +5
This paper introduces ECHO-LLaMA, an efficient LLaMA architecture designed to improve both the training speed and inference throughput of LLaMA architectures while maintaining its…
Single Parent Family: A Spectrum of Family Members from a Single Pre-Trained Foundation Model
Habib Hajimolahoseini, Mohammad Hassanpour, Foozhan Ataiefard +2
This paper introduces a novel method of Progressive Low Rank Decomposition (PLRD) tailored for the compression of large language models. Our approach leverages a pre-trained model,…