Intel Powers HLRN-IV Supercomputer at ZIB in Germany

Print Friendly, PDF & Email

In this video, Prof. Ramin Yahayapour from the University of Göttingen describes how the Lise supercomputer at ZIB is powering research and discovery. With 5.355 Petaflops of performance on the Linpack benchmark, the Atos system ranks #40 on the TOP500.

Intel, Atos and the North-German Supercomputing Alliance (HLRN) recently began the second phase of building the HLRN-IV supercomputer system at the Zuse Institute Berlin (ZIB) in Berlin. The system, named Lise, consists of 1,180 compute nodes powered by 2nd generation Intel® Xeon Platinum 9200 processors. With the help of Lise, researchers and scientists will be able to run compute-intensive projects involving mathematical simulations, machine learning and artificial intelligence (AI).

Working closely with Atos enabled us to reach a significant technology milestone at HLRN,” said Trish Damkroger, vice president and general manager of the Extreme Computing Group at Intel. “The long-standing partnership between Intel, Atos and HLRN continues to drive tremendous advancements in scientific research and discovery.”

HLRN operates a massively parallel supercomputing system that serves over 200 universities and research institutions in Germany. The Intel Xeon Platinum 9200 processors deliver the computing power HLRN needs to blend traditional simulation techniques with machine learning and artificial intelligence. The Lise supercomputer will allow HLRN to meet the increasing demands of scientists and researchers as they unlock the value of their data and make discoveries in:

  • Earth System Sciences – Including climate, oceans, rain forests, glaciers, Antarctic phytoplankton (microalgae), mineral dust cycles and the stratosphere.
  • Fluid Dynamics – Including turbulence models for ship turbines, wind turbines and aircraft wings.
  • Healthcare – Including computer-aided drug design, improving medical care at home, and a better understanding of illness and treatment of diseases.

Recognizing that the convergence of machine learning and AI with traditional simulation capabilities will continue to take researchers in many directions, Atos customized and optimized Lise compute nodes using the Intel Server System S9200WK as a foundation, while leveraging the flexibility inherent in Intel Xeon Platinum 9200 processors to support HLRN’s next generation of research.

By entering into the second phase of our efforts with Atos and Intel, our users will benefit right away from the more powerful system without needing to change their code. The HLRN-IV supercomputer provides true performance portability, which is a crucial aspect for our researchers in order to quickly benefit from the new, more powerful system,” said Professor Alexander Reinefeld of Zuse Institute Berlin.

Intel, Atos and HLRN started work on the HLRN-IV supercomputer in early 2019. In December 2019, the organizations kicked off the second phase of building the HLRN-IV system. In attendance at the event were Professor Dr. Christof Schütte, president of Zuse Institute Berlin; Professor Dr. Wolf-Dieter Lukas, state secretary at the Federal Ministry for Education and Research; Steffen Krach, state secretary at the State Ministry for Science and Research in Berlin; Björn Thümler, minister for Science and Culture in Lower Saxony; Ursula Morgenstern, CEO of Atos Deutschland; and Hannes Schwaderer, managing director of Intel Deutschland GmbH.

The event included lectures from dignitaries within the scientific community, such as Dr. Horst Simon (Berkeley Lab), and details of work being done at HLRN.

High Performance Across Diverse Research

In terms of science communities, HLRN has to support all types of workloads for their many researchers. Therefore, HLRN systems need to have the characteristics of a general purpose system but still be of the highest performance. Their final choice had no accelerators.

Although we looked at accelerators, including GPUs, as part of the procurement process, there was no advantage with regards to obtaining the highest performance in using GPUs or other accelerators in the system.”— Dr. Thomas Steinke, Head of ZIB Supercomputing

HLRN’s benchmarks are open and include benchmarks that can take advantage of GPUs. HLRN found that any advantage in performance on some workloads are insufficient, when considering the reduction in general purpose compute capacity, or additional costs involved. A homogeneous system based on the 2nd Gen Intel® Xeon® Scalable processors proved itself to be the best choice for the diverse needs of the HLRN scientists and researchers.

Beating Back Amdahl’s Law

Ever mindful of Amdahl’s Law, Dr. Thomas Steinke is fond of emphasizing the use of fast algorithms for fast computers. He shared that “The pressure of optimizing code for scaling on a node is less because of the high real-world performance of the 2nd Gen Intel Xeon Scalable processors compared to previous many-core architectures”.

The 2nd Gen Intel Xeon Scalable processor family offers an outstanding choice for high performance computing (HPC) and helps programmers cope with Amdahl’s Law.

Our users will benefit right away from the more powerful system without needing to change their code,” Prof. Reinefeld “AI and Machine Learning stand to impact all areas of HLRN research. A hot area of interest is the blending of machine learning and AI techniques with traditional simulation capabilities. While promising results have been reported, there is much work to be done. The exploration of algorithms is likely to take researchers in many directions, and this need for flexibility is one reason HLRN chose 2nd Gen Intel Xeon Scalable processors to support their next generation of research. Prof. Yahyapour emphasized that “the CPU is quite good for artificial intelligence and machine learning. That’s an area where we see more need from our researchers. Traditionally they were not so much into data intensive work but that’s something we see as a new trend for the new system that will also be of particular interest.”

Intel Advanced Vector Extensions 512 (Intel AVX-512) proved to be the logical choice to help increase HLRN’s compute power, and with the addition of Intel Deep Learning Boost (Intel DL Boost) to augment AVX-512, offered outstanding performance for the new frontier of HPC applications.

Sign up for our insideHPC Newsletter