5 papers
From Skew to Symmetry: Node-Interconnect Multi-Path Balancing with Execution-time Planning for Modern GPU Clusters
Jinghan Yao, Kaushik Kandadi, Bharath Ramesh +2
Modern GPU-based high-performance computing clusters offer unprecedented communication bandwidth through heterogeneous intra-node interconnects and inter-node networks. However, de…
MAC-Attention: a Match-Amend-Complete Scheme for Fast and Accurate Attention Computation
Jinghan Yao, Sam Adé Jacobs, Walid Krichene +2
Long-context decoding in LLMs is IO-bound: each token re-reads an ever-growing KV cache. Prior accelerations cut bytes via compression, which lowers fidelity, or selection/eviction…
Characterizing Communication Patterns in Distributed Large Language Model Inference
Lang Xu, Kaushik Kandadi Suresh, Quentin Anthony +2
Large Language Models (LLMs) built on transformer architectures have transformed natural language processing, achieving remarkable performance across diverse applications. While di…
Training Ultra Long Context Language Model with Fully Pipelined Distributed Transformer
Jinghan Yao, Sam Ade Jacobs, Masahiro Tanaka +3
Large Language Models (LLMs) with long context capabilities are integral to complex tasks in natural language processing and computational biology, such as text generation and prot…
Scaling Large Language Model Training on Frontier with Low-Bandwidth Partitioning
Lang Xu, Quentin Anthony, Jacob Hatef +4
Scaling up Large Language Model(LLM) training involves fitting a tremendous amount of training parameters across a limited number of workers. However, methods like ZeRO-3 that dras…