6 citations · 11 across the 5 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.DC2023★ 1 cited
Tessel: Boosting Distributed Execution of Large DNN Models via Flexible Schedule Search
Zhiqi Lin, Youshan Miao, Guanbin Xu +4
Increasingly complex and diverse deep neural network (DNN) models necessitate distributing the execution across multiple devices for training and inference tasks, and also require…
cs.AR2023★ 6 cited
Splitwise: Efficient generative LLM inference using phase splitting
Pratyush Patel, Esha Choukse, Chaojie Zhang +4
Recent innovations in generative large language models (LLMs) have made their applications and use-cases ubiquitous. This has led to large-scale deployments of these models, using…
cs.PF2023
Look-Up mAI GeMM: Increasing AI GeMMs Performance by Nearly 2.5x via msGeMM
Saeed Maleki
AI models are increasing in size and recent advancement in the community has shown that unlike HPC applications where double precision datatype are required, lower-precision dataty…