One challenge of using leadership computing resources is reading and writing data in scalable ways that does not lead to bottlenecks or performance penalties on the shared filesystems. This Workshop aims to bring together leading IO experts in the HEP field with experts from DOE ASCR Facilities to discuss how to move forward in the next years to make HEP software more friendly to millions of parallel threads accessing files on shared disks.
On February 26-March 2, 2018, Brookhaven National Laboratory (BNL) hosted a hackathon targeting the Intel Xeon Phi (formerly code-named Knights Landing, or KNL) processors for scientists to come together to optimize their application code performance on the KNL-based supercomputers. Out of the five teams who participated, two teams came from the high energy physics community:
- APES (Accelerator Particle Energy Simulator): A code for tracking particle-device and particle-particle interactions that has the potential to be used as the design platform for future particle accelerators. Team members all came from BNL.
- ART: a code for simulating the formation of structures in the universe, particularly galaxy clusters. Team members came from Yale University and University of Miami.
Each team was paired with a mentor with similar scientific background. They also had access to four floating mentors from Intel who brought expertise in OpenMP, Intel hardware architectures, compilers and performance profiling tools. The teams worked with their mentors for five days in a hands-on setting. By the end of the week, all teams achieved significant performance improvements for their codes, with ART and APES achieving >2X and >5X speedup, respectively.
The HEP-CCE is happy to announce a call for applications to its 2018 GRADUATE STUDENT SUMMER INTERNSHIP PROGRAM. This program gives graduate students in HEP with a strong interest in computing a chance to work with teams at DOE laboratories on challenging problems currently facing HEP.
Applications to the program should include a CV, a statement of current research, and a short statement on how participation in the program will benefit the student’s current work and future career. A letter of recommendation from the student’s research adviser is also required.
Deadline: March 2, 2018
The Computational Science Initiative Division at Brookhaven National Laboratory, in partnership with the HEP Center for Computational Excellence (CCE) and the ECP SOLLVE project, will host the first KNL Hackathon on February 26-March 2, 2018. All current and potential users of the Intel Knights Landing-based systems are encouraged to submit an application to participate.
To participate, please submit a team application at www.bnl.gov/knlhackathon2018. Deadline for application is January 5, 2018. All applications will be peer-reviewed, and notification of acceptance will be sent out by January 14, 2018.
For more information, visit www.bnl.gov/knlhackathon2018.
The next ECP IDEAS Best Practices for HPC Software Developers
Webinar, “Managing Defects in HPC Software Development”, is scheduled
to take place on November at 1:00 pm ET and will be presented by Tom
Evans of ORNL. For more information and/or to register, visit
The DOE Exascale Computing Project (ECP) is pleased to sponsor a webinar presented by Sameer Shende of the University of Oregon on the TAU Performance System. The webinar will take place on Wednesday, November 8, at 1:00 pm ET.
OLCF users are invited to participate in webinar presented by Michael Wolfe
of NVIDIA titled “Scalable Node Programming with OpenACC” on Wednesday,
September 20, at 1:00 pm ET. For more information and/or to register,
NERSC is hosting a joint Data Day and the annual NERSC Users Group meeting, NUG 2017, will be held in conjunction this year Sept. 19 to 21, 2017 . In-person registration is closed but it is still possible to join remotely
Amazon research awards associated with Machine/Deep Learning announced, click here for details.
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