Boosting scalable data analytics with modern programmable networks

Venue

ACM DAMON 2018

Authors

Marcel Blöcher Tobias Ziegler Carsten Binnig Patrick Eugster

Links

Paper

Abstract

Data center networks lie at the core of distributed data analytics frameworks running in large scale environments. Recent research seek to improve the system performance by optimizing the end-host network usage, e.g., optimally use RDMA [2] or zero copy I/O frameworks [5] for distributed data analytics frameworks. Such approaches allow these systems to leverage the high network-bandwidth at end-hosts, however, keep the network itself untouched which does not solve contention and scalability issues.

Bibtex

@inproceedings{2018-damon,
 Author = {Marcel Blöcher and Tobias Ziegler and Carsten Binnig and Patrick Eugster},
 Booktitle = {Proceedings of the 14th International Workshop on Data Management on New Hardware ({DAMON})},
 Doi = {10.1145/3211922.3211923},
 Pages = {1--3},
 Publisher = {{ACM}},
 Title = {Boosting scalable data analytics with modern programmable networks},
 Year = {2018}
}