19 citations · 19 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 19 cited
Revisiting Neural Retrieval on Accelerators
Jiaqi Zhai, Zhaojie Gong, Yueming Wang +4
Retrieval finds a small number of relevant candidates from a large corpus for information retrieval and recommendation applications. A key component of retrieval is to model (user,…
cs.IR2023
MTrainS: Improving DLRM training efficiency using heterogeneous memories
Hiwot Tadese Kassa, Paul Johnson, Jason Akers +7
Recommendation models are very large, requiring terabytes (TB) of memory during training. In pursuit of better quality, the model size and complexity grow over time, which requires…