Nicholas Meisburger

Orcid: 0009-0009-5301-6421

According to our database1, Nicholas Meisburger authored at least 8 papers between 2020 and 2023.

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Bibliography

2023
BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Neural Networks on Commodity CPU Hardware.
CoRR, 2023

From Research to Production: Towards Scalable and Sustainable Neural Recommendation Models on Commodity CPU Hardware.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Distributed SLIDE: Enabling Training Large Neural Networks on Low Bandwidth and Simple CPU-Clusters via Model Parallelism and Sparsity.
CoRR, 2022

2021
Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More.
CoRR, 2021

Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More.
Proceedings of Machine Learning and Systems 2021, 2021

A Tale of Two Efficient and Informative Negative Sampling Distributions.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Distributed Tera-Scale Similarity Search with MPI: Provably Efficient Similarity Search over billions without a Single Distance Computation.
CoRR, 2020


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