HEP-CCE: Promoting Computational Excellence
HEP-CCE Coordinators: Salman Habib (Argonne), Rob Roser (Fermilab), and Peter Nugent (LBNL)
The HEP-CCE is a cross-cutting initiative to promote excellence in high performance computing (HPC) including data-intensive applications, scientific simulations, and data movement and storage. Enhancing connections with DOE's Advanced Scientific Computing Research (ASCR) program is an important part of the Center's activities. This includes promoting future-looking R&D initiatives in exascale architectures and systems, intelligent networking, and new data management and data analysis tools. Although the HEP-CCE is not a service-oriented entity, limited resources are available to support collaborative computing efforts for the HEP community, including a common GitHub repository for open source codes, a website for aggregating useful information, and expertise within and without HEP for solving computational problems via the Expert Forum. The HEP-CCE also sponsors topical workshops and student training programs.
This is the first announcement of the Summer School on Machine Learning for High Energy Physics 2017, to be held in Reading, UK, July 17-23 2017. The school is organised by Yandex School of Data Analysis, Imperial College London and Higher School of Economics. Continue reading Summer School on Machine Learning for High Energy Physics 2017
The HEP-CCE announces a summer internship program for graduate students in the US who would like to work at Argonne National Laboratory, Fermilab National Accelerator Laboratory, and Lawrence Berkeley National Laboratory. The program covers the three high energy physics frontier areas (Cosmic, Energy, and Intensity) and is aimed at computationally-oriented graduate students interested in new educational, training, and research opportunities. A strong computing/computational background is highly desirable. Continue reading HEP-CCE Announces: Graduate Student Summer Internship Program
All NERSC Cori and Edison users are eligible to apply for early access to the regular KNL partition, which allows running jobs up to full system scale free of charge from March 1 to July 1. All users can currently run small jobs, but early access will enable users to run at scale.
To apply for early access, users will need to collect performance data on their application and fill out the application form at https://my.nersc.gov/knleap.php . We are accepting one application per repo, and the application can be submitted by any member of the repo. Please direct any questions to the consultants via my.nersc.gov, help.nersc.gov, or firstname.lastname@example.org .
Argonne’s intensive two-week summer training program on extreme-scale computing will be held July 30—August 11, 2017. The deadline to apply is March 10, 2017. Doctoral students, postdocs, and scientists interested in conducting computational science and engineering research on large-scale computers are encouraged to apply. For more information, visit: http://extremecomputingtraining.anl.gov/
Both CMS and ATLAS are amongst the six projects selected for the program that offers NERSC and vendor support in porting codes to the KNL architecture.