Distributed Tera-Scale Similarity Search with MPI: Provably Efficient Similarity Search over billions without a Single Distance Computation. - Nicholas Meisburger; Anshumali Shrivastava (CoRR, 2020)

A Tale of Two Efficient and Informative Negative Sampling Distributions. - Shabnam Daghaghi; Tharun Medini; Nicholas Meisburger; Beidi Chen; Mengnan Zhao; Anshumali Shrivastava (ICML, 2021)

Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More. - Shabnam Daghaghi; Nicholas Meisburger; Mengnan Zhao; Anshumali Shrivastava (MLSys, 2021)

Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More. - Shabnam Daghaghi; Nicholas Meisburger; Mengnan Zhao; Yong Wu; Sameh Gobriel; Charlie Tai; Anshumali Shrivastava (CoRR, 2021)

Distributed SLIDE: Enabling Training Large Neural Networks on Low Bandwidth and Simple CPU-Clusters via Model Parallelism and Sparsity. - Minghao Yan; Nicholas Meisburger; Tharun Medini; Anshumali Shrivastava (CoRR, 2022)

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; Joshua Engels; David Torres Ramos; Pratik Pranav; Benjamin Coleman; Benjamin Meisburger; Shubh Gupta; Yashwanth Adunukota; Siddharth Jain; Tharun Medini; et al. (CIKM, 2023)

From Research to Production: Towards Scalable and Sustainable Neural Recommendation Models on Commodity CPU Hardware. - Anshumali Shrivastava; Vihan Lakshman; Tharun Medini; Nicholas Meisburger; Joshua Engels; David Torres Ramos; Benito Geordie; Pratik Pranav; Shubh Gupta; Yashwanth Adunukota; Siddharth Jain (RecSys, 2023)

BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Neural Networks on Commodity CPU Hardware. - Nicholas Meisburger; Vihan Lakshman; Benito Geordie; Joshua Engels; David Torres Ramos; Pratik Pranav; Benjamin Coleman; Benjamin Meisburger; Shubh Gupta; Yashwanth Adunukota; Tharun Medini; Anshumali Shrivastava (CoRR, 2023)