HPC-AI Advisory Council Announces 8th Annual APAC Advanced RDMA Programming Workshop and Competition

July 15, 2020

SUNNYVALE, Calif., July 15, 2020 — The HPC-AI Advisory Council, a for community benefit organization promoting high performance computing (HPC) and artificial intelligence (AI) education, announced registration is now open for its 8th Annual Advanced RDMA Programming Workshop and Competition. The 5-day online workshop (July 27 to August 2) followed by a 2-day hackathon will provide students with a comprehensive introduction to advanced network technologies and Remote Direct Memory Access (RDMA) programming for efficient server-to-server and server-to-storage communication.

RDMA has been widely used in HPC, AI, cloud and edge computing, telco and financial services, and more. RDMA is the key technology for efficient and scalable data transfers between data center servers, storage, and edge platforms. Joining the HPC-AI Advisory Council’s training and development efforts will be RDMA experts and mentors from the Chinese Institute of Computing Technology (ICT), the Ohio State University, the University of Science and Technology of China (USTC), and Tsinghua University, to deliver 30 hours of lectures, 8 hours of demo presentations and hands-on programming work. The lectures will include an advanced introduction to RDMA and programming, training on a variety of network offload features to optimize performance, as well as shared experiences from previous teams and participants from prior RDMA workshops and competitions.

“RDMA is becoming the key technology for optimizing applications running in modern HPC and AI data center infrastructures, and this is reflected in the high demand by data center companies around the world for students and graduates with RDMA programming expertise and skills,” said Gilad Shainer, chairman of the HPC-AI Advisory Council. “We welcome students in APAC to participate in the workshop and competition to further their RDMA expertise and help foster their careers in the industry. This will also be an opportunity to network and meet with the RDMA industry leaders and experts from the HPC-AI Advisory Council and from top universities around the world.”

20 teams are anticipated to join the online competition. Teams must register before July 22 to ensure eligibility. More information on the workshop and competition can be found here: http://www.hpcadvisorycouncil.com/events/2020/rdma/

The workshop will be conducted by:

  • Professor Cheng Li – a research professor at the School of Computer Science and Technology at University of Science and Technology of China (USTC) and a member of Advanced Data Systems Lab (ADSL).
  • Professor Dhabaleswar (DK) Panda – a Professor and University Distinguished Scholar of Computer Science and Engineering at the Ohio State University in the USA.
  • Mr. Gil Bloch – an RDMA programming instructor at the Hebrew University of Jerusalem in Israel and the Ben Gurion University in Israel.
  • Professor Jidong Zhai – a Tenured Associate Professor in the Computer Science Department of Tsinghua University.
  • Professor Yunquan Zhang – a Research Professor and the Director of Parallel Software Laboratory, Institute of Computing Technology, Chinese Academy of Sciences. He is also the Secretary General of CCF TCHPC, and the Chair of ACM SIGHPC China.

About HPC-AI Advisory Council

Founded in 2008, the HPC-AI Advisory Council (HPCAIAC) is a for community benefit organization with over 400 members committed to bridge the gap between high-performance computing and artificial intelligence use and its potential, bringing the beneficial capabilities of HPC and AI to new users for better research, education, innovation and product manufacturing, and brings users the expertise needed to operate HPC and AI systems, provide application designers with the tools needed to enable parallel computing, and to strengthen the qualification and integration of HPC and AI system products. For more information, please visit: www.hpcadvisorycouncil.com


Source: HPC-AI Advisory Council 

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