3 papers
cs.LG2025
Characterizing and Efficiently Accelerating Multimodal Generation Model Inference
Yejin Lee, Anna Sun, Basil Hosmer +27
Generative artificial intelligence (AI) technology is revolutionizing the computing industry. Not only its applications have broadened to various sectors but also poses new system…
cs.LG2025
Accelerating Transformer Inference and Training with 2:4 Activation Sparsity
Daniel Haziza, Timothy Chou, Dhruv Choudhary +7
In this paper, we demonstrate how to leverage 2:4 sparsity, a popular hardware-accelerated GPU sparsity pattern, to activations to accelerate large language model training and infe…
cs.DC2024
SimpleFSDP: Simpler Fully Sharded Data Parallel with torch.compile
Ruisi Zhang, Tianyu Liu, Will Feng +4
Distributed training of large models consumes enormous computation resources and requires substantial engineering efforts to compose various training techniques. This paper present…