DAPPER 2018: International Workshop on Data Analytics and Parallel Performance Belfast, UK, April 2, 2018 |
Conference website | https://dapper18.github.io |
Submission link | https://easychair.org/conferences/?conf=dapper18 |
Submission deadline | February 15, 2018 |
Optimizing high performance computing (HPC)/data centers, and applications running at these centers presents a unique set of challenges, and an opportunity to automate complex optimization tasks. The use of machine learning and statistical techniques to model and characterize performance data is gaining traction in the parallel community. The International Workshop on Data Analytics and Parallel Performance provides a forum for sharing academic and industrial research work focused on applying data analytics to performance analysis, debugging and optimization/tuning of parallel software and systems.
Submission Guidelines
We solicit 8-page full papers as well as 4-page short papers that focus on techniques at the intersection of parallel performance and data analytics. The 8-page full papers should describe original unpublished work, while 4-page short papers can be original unpublished work or ongoing work.
Papers must be submitted in PDF format (readable by Adobe Acrobat Reader 5.0 and higher) and formatted for 8.5” x 11” (U.S. Letter). Submissions are limited to 8 pages in the IEEE format, using the conference option. The 8-page limit includes figures, tables, and references.
All papers must be submitted through Easychair at: https://easychair.org/conferences/?conf=dapper18
A few selected accepted papers that describe unpublished work will be invited to submit to a special issue of The International Journal of High Performance Computing Applications.
Important Deadlines
- Submission deadline: February 15, 2018 (AoE)
- Notification of acceptance: March 5, 2018 (AoE)
List of Topics
Authors are invited to submit novel research as well as ongoing work pertaining to:
- Deep learning, neural networks
- Supervised/unsupervised machine learning
- Classification, regression, clustering
- Dimensionality reduction
- Data-driven modeling
applied to
- Performance analysis
- Debugging, performance debugging
- Performance optimization, auto-tuning
of/for
- Parallel benchmarks, proxy applications, and production codes
- Scientific workflows
- HPC workloads/Full system
- HPC/Data center facilities
Committees
Workshop Chairs
- Abhinav Bhatele, Lawrence Livermore National Laboratory
- Marc Casas, Barcelona Supercomputing Center
- Nikhil Jain, Lawrence Livermore National Laboratory
Venue
The workshop will be held in Belfast, Northern Ireland, UK on April 2, 2018.