How Do ML Jobs Fail in Datacenters? Analysis of a Long-Term Dataset from an HPC Cluster

Author:

Chu Xiaoyu1ORCID,Talluri Sacheendra1ORCID,Versluis Laurens1ORCID,Iosup Alexandru1ORCID

Affiliation:

1. Vrije Universiteit Amsterdam, Amsterdam, Netherlands

Publisher

ACM

Reference14 articles.

1. Failure Analysis of Jobs in Compute Clouds: A Google Cluster Case Study

2. Learning from Failure Across Multiple Clusters: A Trace-Driven Approach to Understanding, Predicting, and Mitigating Job Terminations

3. Geoffrey C. Fox , James A. Glazier , J. C. S. Kadupitiya , Vikram Jadhao , Minje Kim , Judy Qiu , James P. Sluka , Endre T. Somogyi , Madhav V. Marathe , Abhijin Adiga , Jiangzhuo Chen , Oliver Beckstein , and Shantenu Jha . 2019 . Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation. In IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019 , Rio de Janeiro, Brazil, May 20--24 , 2019. IEEE, 422--429. https://doi.org/10.1109/IPDPSW.2019.00081 10.1109/IPDPSW.2019.00081 Geoffrey C. Fox, James A. Glazier, J. C. S. Kadupitiya, Vikram Jadhao, Minje Kim, Judy Qiu, James P. Sluka, Endre T. Somogyi, Madhav V. Marathe, Abhijin Adiga, Jiangzhuo Chen, Oliver Beckstein, and Shantenu Jha. 2019. Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation. In IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019, Rio de Janeiro, Brazil, May 20--24, 2019. IEEE, 422--429. https://doi.org/10.1109/IPDPSW.2019.00081

4. Shiraz: Exploiting System Reliability and Application Resilience Characteristics to Improve Large Scale System Throughput

5. Failures in large scale systems

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