1 citations · 1 across the 3 of their papers we have counts for
3 papers
AutoCSF: Provably Space-Efficient Indexing of Skewed Key-Value Workloads via Filter-Augmented Compressed Static Functions
David Torres Ramos, Vihan Lakshman, Chen Luo +2
We study the problem of building space-efficient, in-memory indexes for massive key-value datasets with highly skewed value distributions. This challenge arises in many data-intens…
CARAMEL: A Succinct Read-Only Lookup Table via Compressed Static Functions
Benjamin Coleman, David Torres Ramos, Vihan Lakshman +2
Lookup tables are a fundamental structure in many data processing and systems applications. Examples include tokenized text in NLP, quantized embedding collections in recommendatio…
BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware
Nicholas Meisburger, Vihan Lakshman, Benito Geordie +9
Efficient large-scale neural network training and inference on commodity CPU hardware is of immense practical significance in democratizing deep learning (DL) capabilities. Present…