@inproceedings{8fcfdfe92761482c94ff230596083c1a,
title = "Accelerating Big Data Infrastructure and Applications (Ongoing Collaboration)",
abstract = "High-performance computing (HPC) systems are increasingly being used for data-intensive, or 'Big Data', workloads. However, since traditional HPC workloads are compute-intensive, the HPC-Big Data convergence has created many challenges with optimizing data movement and processing on modern supercomputers. Our collaborative work addresses these challenges using a three-pronged approach: (i) measuring and modeling extreme-scale I/O workloads, (ii) designing a low-latency, scalable, on-demand burst-buffer solution, and (iii) optimizing graph algorithms for processing Big Data workloads. We describe the three areas of our collaboration and report on their respective developments.",
keywords = "Big Data, HPC, I/O, I/O modeling, burst buffers, data intensive, graph processing, graph store, performance measurement",
author = "Kevin Brown and Tianqi Xu and Keita Iwabuchi and Kento Sato and Adam Moody and Kathryn Mohror and Nikhil Jain and Abhinav Bhatele and Martin Schulz and Roger Pearce and Maya Gokhale and Satoshi Matsuoka",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 37th IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2017 ; Conference date: 05-06-2017 Through 08-06-2017",
year = "2017",
month = jul,
day = "13",
doi = "10.1109/ICDCSW.2017.74",
language = "English",
series = "Proceedings - IEEE 37th International Conference on Distributed Computing Systems Workshops, ICDCSW 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "343--347",
editor = "Ferreira, {Joao E.} and Teruo Higashino and Aibek Musaev",
booktitle = "Proceedings - IEEE 37th International Conference on Distributed Computing Systems Workshops, ICDCSW 2017",
}