Delete hpcda.md

doc.zih.tu-dresden.de/docs/jobs_and_resources/hpcda.md

-# HPC for Data Analytics
-
-With the HPC-DA system, the TU Dresden provides infrastructure for High-Performance Computing and
-Data Analytics (HPC-DA) for German researchers for computing projects with focus in one of the
-following areas:
-
-- machine learning scenarios for large systems
-- evaluation of various hardware settings for large machine learning
-  problems, including accelerator and compute node configuration and
-  memory technologies
-- processing of large amounts of data on highly parallel machine
-  learning infrastructure.
-
-Currently we offer 25 Mio core hours compute time per year for external computing projects.
-Computing projects have a duration of up to one year with the possibility of extensions, thus
-enabling projects to continue seamlessly. Applications for regular projects on HPC-DA can be
-submitted at any time via the
-[online web-based submission](https://tu-dresden.de/zih/hochleistungsrechnen/zugang/hpc-da)
-and review system. The reviews of the applications are carried out by experts in their respective
-scientific fields. Applications are evaluated only according to their scientific excellence.
-
-ZIH provides a portfolio of preinstalled applications and offers support for software
-installation/configuration of project-specific applications. In particular, we provide consulting
-services for all our users, and advise researchers on using the resources in an efficient way.
-
-\<img align="right" alt="HPC-DA Overview"
-src="%ATTACHURL%/bandwidth.png" title="bandwidth.png" width="250" />
-
-## Access
-
-- Application for access using this
-  [Online Web Form](https://tu-dresden.de/zih/hochleistungsrechnen/zugang/hpc-da)
-
-## Hardware Overview
-
-- [Nodes for machine learning (Power9)](../jobs_and_resources/power9.md)
-- [NVMe Storage](../jobs_and_resources/nvme_storage.md) (2 PB)
-- [Warm archive](../data_lifecycle/file_systems.md#warm-archive) (10 PB)
-- HPC nodes (x86) for DA (island 6)
-- Compute nodes with high memory bandwidth:
-  [AMD Rome Nodes](../jobs_and_resources/rome_nodes.md) (island 7)
-
-Additional hardware:
-
-- [Multi-GPU-Cluster](../jobs_and_resources/alpha_centauri.md) for projects of SCADS.AI
-
-## File Systems and Object Storage
-
-- Lustre
-- BeeGFS
-- Quobyte
-- S3
-
-## HOWTOS
-
-- [Get started with HPC-DA](../software/get_started_with_hpcda.md)
-- [IBM Power AI](../software/power_ai.md)
-- [Work with Singularity Containers on Power9]**todo** Cloud
-- [TensorFlow on HPC-DA (native)](../software/tensorflow.md)
-- [Tensorflow on Jupyter notebook](../software/tensorflow_on_jupyter_notebook.md)
-- Create and run your own TensorFlow container for HPC-DA (Power9) (todo: no link at all in old compendium)
-- [TensorFlow on x86](../software/deep_learning.md)
-- [PyTorch on HPC-DA (Power9)](../software/pytorch.md)
-- [Python on HPC-DA (Power9)](../software/python.md)
-- [JupyterHub](../access/jupyterhub.md)
-- [R on HPC-DA (Power9)](../software/data_analytics_with_r.md)
-- [Big Data frameworks: Apache Spark, Apache Flink, Apache Hadoop](../software/big_data_frameworks.md)

doc.zih.tu-dresden.de/mkdocs.yml

@@ -97,7 +97,6 @@ nav:
     - Taurus: jobs_and_resources/system_taurus.md
     - Slurm Examples: jobs_and_resources/slurm_examples.md
     - Slurm: jobs_and_resources/slurm.md
-    - HPC-DA: jobs_and_resources/hpcda.md
     - Binding And Distribution Of Tasks: jobs_and_resources/binding_and_distribution_of_tasks.md
       #    - Queue Policy: jobs/policy.md
       #    - Examples: jobs/examples/index.md