18 citations · 39 across the 5 of their papers we have counts for
Showing cs.DCShow all
3 papers · 1 filter
cs.DC2026
A Few GPUs, A Whole Lotta Scale: Faithful LLM Training Emulation with PrismLLM
Shaoke Xi, ChonLam Lao, Boyi Jia +11
Large language model (LLM) training today runs on clusters spanning thousands of GPUs. While this scale enables rapid model advances, developing, debugging, and performance-tuning…
cs.DC2022
PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems
Yuanxing Zhang, Langshi Chen, Siran Yang +12
The development of personalized recommendation has significantly improved the accuracy of information matching and the revenue of e-commerce platforms. Recently, it has 2 trends: 1…
cs.DC2019★ 15 cited
AliGraph: A Comprehensive Graph Neural Network Platform
Rong Zhu, Kun Zhao, Hongxia Yang +5
An increasing number of machine learning tasks require dealing with large graph datasets, which capture rich and complex relationship among potentially billions of elements. Graph…