High-performance computing and data analytics application support for the MPG

High-performance computing and data analytics application support for the MPG

The MPCDF provides high-level support for the development, optimization, analysis and visualization of high-performance computing (HPC) and data analytics (HPDA) applications to Max-Planck Institutes with high-end computing needs, e.g. in astrophysics, fusion research, materials and bio sciences, polymer research, and theoretical chemistry.

MPG supercomputer Cobra

MPG supercomputer Cobra

Based on Intel Xeon Skylake-SP processors and Nvidia GPUs (V100, RTX5000): 3424 compute nodes, 136,960 CPU-cores, 128 Tesla V100-32 GPUs, 240 Quadro RTX 5000 GPUs, 529 TB CPU RAM (DDR4), 7.9 TB GPU RAM HBM2, 11.4 PFlop/s peak (FP64) + 2.64 PFlop/s peak (FP32). 100 Gb/s Interconnect (Omnipath, nonblocking fabric over individual islands of 626 nodes). Operational since April 2018.

MPG supercomputer Raven

MPG supercomputer Raven

Based on Intel Xeon IceLake-SP processor 8360Y and Nvidia A100 GPU: 1592 CPU-compute nodes, 114,624 CPU-cores, 457 TB RAM (DDR4), 8.8 PFlop/s theoretical peak performance (FP64), 192 GPU-accelerated nodes providing 768 Nvidia A100 GPUs, 30 TB GPU RAM (HBM2), 16 PFlop/s theoretical peak performance (FP64, including tensor cores and host CPUs). HDR InfiniBand interconnect.

StorageTek tape library

StorageTek tape library

Data archive with research results of Max-Planck scientists. Here: picture of STK SL8500 tape library. Robots on the shelf rows reach each volume keeping the information available around the clock. Further tape libraries in operation from IBM. Data include experiment and simulated data from many science areas, e.g. from life and materials sciences or astro and fusion research, but also treasures of the World Heritage like sound recordings of endangered languages or images of rare frescoes.

National and international projects

National and international projects

The MPCDF, in partnership with different Max Planck Institutes is engaged in several national and international projects and research consortia, such as EU Centers of Excellence, with a focus in high-performance computing, data analytics and data management.

Welcome to the Max Planck Computing and Data Facility (MPCDF)

Mission

The Max Planck Computing and Data Facility (MPCDF, formerly known as RZG) is a cross-institutional competence centre of the Max Planck Society to support computational and data sciences. In close collaboration with domain scientists from the Max Planck Institutes the MPCDF is engaged in the development and optimization of algorithms and applications for high performance computing and data analytics as well as in the design and implementation of solutions for data-intensive projects. The MPCDF operates state-of-the-art supercomputers, several mid-range compute systems and data repositories for various Max Planck institutes, and provides an up-to-date infrastructure for data management including long-term archival.

 

Operational Information

MPCDF compute, data and network services operate normally.

Important notice for IPP: email services have been migrated to GWDG. Information is available in the IPP Intranet. Please contact the IPP Service Desks in Garching or Greifswald for problems or questions.

Important notice for MPQ: the MPCDF mail-server is accessible only from within the Garching network or externally via VPN.

In case of problems or questions concering MPCDF services please use one of these communication channels:

News at MPCDF

News

A new issue of the MPCDF computer bulletin Bits&Bytes was released. Read about high-performance computing software news, using Docker containers in the MPCDF GitLab CI environment, GO-Nexus, an enhanced data transfer and sharing service for MPCDF’s ...

The MPCDF has issued a brochure on "High-Performance Computing and Data Science in the Max Planck Society" with examples of science that is currently being supported by the MPCDF services.

Job Offers

No Vacancies

Upcoming Events

Accelerated Machine Learning and Deep Learning with Intel

Mar 8, 2023 09:30 AM (Local Time Germany) - Mar 9, 2023 04:00 PM
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May 11, 2023 09:30 AM (Local Time Germany) - May 12, 2023 12:30 PM
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