106 citations · 167 across the 26 of their papers we have counts for
4 papers · 1 filter
How to use Persistent Memory in your Database
Dimitrios Koutsoukos, Raghav Bhartia, Ana Klimovic +1
Persistent or Non Volatile Memory (PMEM or NVM) has recently become commercially available under several configurations with different purposes and goals. Despite the attention to…
Plumber: Diagnosing and Removing Performance Bottlenecks in Machine Learning Data Pipelines
Michael Kuchnik, Ana Klimovic, Jiri Simsa +2
Input pipelines, which ingest and transform input data, are an essential part of training Machine Learning (ML) models. However, it is challenging to implement efficient input pipe…
Towards Demystifying Serverless Machine Learning Training
Jiawei Jiang, Shaoduo Gan, Yue Liu +6
The appeal of serverless (FaaS) has triggered a growing interest on how to use it in data-intensive applications such as ETL, query processing, or machine learning (ML). Several sy…
tf.data: A Machine Learning Data Processing Framework
Derek G. Murray, Jiri Simsa, Ana Klimovic +1
Training machine learning models requires feeding input data for models to ingest. Input pipelines for machine learning jobs are often challenging to implement efficiently as they…