![]() |
| |||||||||||||||
XLOOP 2019 : Workshop on Large-scale Experiment-in-the-Loop Computing | |||||||||||||||
Link: http://press3.mcs.anl.gov/xloop2019 | |||||||||||||||
| |||||||||||||||
Call For Papers | |||||||||||||||
1st Annual Workshop on Large-scale Experiment-in-the-Loop Computing @ SC
Monday PM, Nov. 18, 2019, Denver, Colorado, USA Workshop website: https://press3.mcs.anl.gov/xloop2019 Continued advances in computational power and high-speed networking is enabling a new model of scientific experiment, experiment-in-the-loop computing (EILC). In this model, high-end computing systems are closely coupled to experimental and observational infrastructure, and the two interact to drive a deeper understanding of physical phenomena. At the same time, advances and widespread adoption of machine learning enables new ways to register and use experimental data. Several research and development challenges are posed by this multifaceted paradigm, many of which are independent of the particular scientific application domain. New algorithms to integrate simulation outputs and experimental data sets must be developed. High performance data management and transfer techniques must be developed to manage and manipulate simulated and observed data sets. Workflows must be constructed with high levels of usability and understandability to enable scientific post-analysis and improvement of the computing solution. The Workshop on Experiment-in-the-Loop Computing (XLOOP 2019) will be a unique opportunity to promote this cross-cutting, interdisciplinary topic area. We invite papers, presentations, and participants from the physical and computer sciences, and encourage the sharing of ideas from across these domains to find common solutions and technologies to make rapid progress in EILC, so that many application areas can easily adopt these methods. The proceedings of the workshop was accepted for publishing by IEEE TCHPC. XLOOP is held in conjunction with SC19: The International Conference on High Performance Computing, Networking, Storage and Analysis and in co-operation with the IEEE Computer Society Technical Consortium on High Performance Computing (TCHPC). == Topics == Topics of interest include, but are not limited to: Machine learning applications in simulation or experiment control Case studies in EILC applications and solutions Data transfer techniques and technologies In situ analysis methods and tools relevant to experiment data Simulation and experiment validation methods and tools Workflow technologies to manage computation and experiment couplings Advanced systems architecture for EILC applications High-performance I/O methods and libraries Data integration and assimilation algorithms and technologies Performance evaluation in EILC applications and solutions Cyberinfrastructure and "big science" planning and reporting == Paper Submission == Please submit novel papers with up to 6 pages in IEEE style via the SC Linklings site. == Important dates == Submissions due: August 17, 2019 Author notification: September 2, 2019 Camera-ready version: September 16, 2019 Workshop @ SC: November 18, 2019, afternoon session. == Organization == Workshop Chairs: Justin M. Wozniak (Argonne National Laboratory) Nicholas Schwarz (Argonne National Laboratory) Contact us at xloop-chairs@lists.dsl.anl.gov . Workshop Program Committee: Francis Alexander (Brookhaven National Laboratory) Shantenu Jha (Rutgers) Bojan Nikolic (Square Kilometer Array, Cambridge) Raymond Osborn (Argonne National Laboratory) Marc F. Paterno (Fermi National Accelerator Laboratory) Amedeo Perazzo (SLAC National Accelerator Laboratory) Thomas E. Proffen (Oak Ridge National Laboratory) Lavanya Ramakrishnan (Lawrence Berkeley National Laboratory) Tobias Richter (European Spallation Source) Christine Sweeney (Los Alamos National Laboratory) Thomas D. Uram (Argonne National Laboratory) |
|