6 citations · 12 across the 8 of their papers we have counts for
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cs.LG2023★ 1 cited
ROAM: memory-efficient large DNN training via optimized operator ordering and memory layout
Huiyao Shu, Ang Wang, Ziji Shi +3
As deep learning models continue to increase in size, the memory requirements for training have surged. While high-level techniques like offloading, recomputation, and compression…
cs.DC2023★ 1 cited
Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity
Haojun Xia, Zhen Zheng, Yuchao Li +6
With the fast growth of parameter size, it becomes increasingly challenging to deploy large generative models as they typically require large GPU memory consumption and massive com…