From 9beb9a618eee9c71b234b2fe997cec050d39b653 Mon Sep 17 00:00:00 2001 From: Martin Schroschk <martin.schroschk@tu-dresden.de> Date: Fri, 1 Dec 2023 13:44:42 +0100 Subject: [PATCH] Remove systems overview (is in hardware overview page) and fix links --- .../docs/jobs_and_resources/overview.md | 76 +------------------ 1 file changed, 1 insertion(+), 75 deletions(-) diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/overview.md b/doc.zih.tu-dresden.de/docs/jobs_and_resources/overview.md index 42bfbf605..1d2e301f2 100644 --- a/doc.zih.tu-dresden.de/docs/jobs_and_resources/overview.md +++ b/doc.zih.tu-dresden.de/docs/jobs_and_resources/overview.md @@ -199,7 +199,7 @@ Pre-installed software on our HPC systems is managed via [modules](../software/m You can see the [list of software that's already installed and accessible via modules](https://gauss-allianz.de/de/application?organizations%5B0%5D=1200). However, there are many different variants of these modules available. Each cluster has its own set -of installed modules, [depending on their purpose](doc.zih.tu-dresden.de/docs/software/.md) +of installed modules, [depending on their purpose](../software/software.md). Specific modules can be found with: @@ -207,80 +207,6 @@ Specific modules can be found with: marie@compute$ module spider <software_name> ``` -### Available Hardware - -ZIH provides a broad variety of compute resources ranging from normal server CPUs of different -manufactures, large shared memory nodes, GPU-assisted nodes up to highly specialized resources for -[Machine Learning](../software/machine_learning.md) and AI. - -## Barnard - -The cluster **Barnard** is a general purpose cluster by Bull. It is based on Intel Sapphire Rapids -CPUs. - -- 630 diskless nodes, each with - - 2 x Intel Xeon Platinum 8470 (52 cores) @ 2.00 GHz, Multithreading enabled - - 512 GB RAM -- Hostnames: `n[1001-1630].barnard.hpc.tu-dresden.de` -- Login nodes: `login[1-4].barnard.hpc.tu-dresden.de` - -## Alpha Centauri - -The cluster **Alpha Centauri** (short: **Alpha**) by NEC provides AMD Rome CPUs and NVIDIA A100 GPUs -and designed for AI and ML tasks. - -- 34 nodes, each with - - 8 x NVIDIA A100-SXM4 Tensor Core-GPUs - - 2 x AMD EPYC CPU 7352 (24 cores) @ 2.3 GHz, Multithreading available - - 1 TB RAM - - 3.5 TB local memory on NVMe device at `/tmp` -- Hostnames: `i[8001-8037].alpha.hpc.tu-dresden.de` -- Login nodes: `login[1-2].alpha.hpc.tu-dresden.de` -- Further information on the usage is documented on the site [GPU Cluster Alpha Centauri](alpha_centauri.md) - -## Romeo - -The cluster **Romeo** is a general purpose cluster by NEC based on AMD Rome CPUs. - -- 192 nodes, each with - - 2 x AMD EPYC CPU 7702 (64 cores) @ 2.0 GHz, Multithreading available - - 512 GB RAM - - 200 GB local memory on SSD at `/tmp` -- Hostnames: `i[7001-7190].romeo.hpc.tu-dresden.de` (after - [recabling phase](architecture_2023.md#migration-phase)]) -- Login nodes: `login[1-2].romeo.hpc.tu-dresden.de` -- Further information on the usage is documented on the site [CPU Cluster Romeo](romeo.md) - -## Julia - -The cluster **Julia** is a large SMP (shared memory parallel) system by HPE based on Superdome Flex -architecture. - -- 1 node, with - - 32 x Intel(R) Xeon(R) Platinum 8276M CPU @ 2.20 GHz (28 cores) - - 47 TB RAM -- Configured as one single node -- 48 TB RAM (usable: 47 TB - one TB is used for cache coherence protocols) -- 370 TB of fast NVME storage available at `/nvme/<projectname>` -- Hostname: `smp8.julia.hpc.tu-dresden.de` (after - [recabling phase](architecture_2023.md#migration-phase)]) -- Further information on the usage is documented on the site [SMP System Julia](julia.md) - -## Power - -The cluster **power** by IBM is based on Power9 CPUs and provides NVIDIA V100 GPUs. -**power** is specifically designed for machine learning tasks. - -- 32 nodes, each with - - 2 x IBM Power9 CPU (2.80 GHz, 3.10 GHz boost, 22 cores) - - 256 GB RAM DDR4 2666 MHz - - 6 x NVIDIA VOLTA V100 with 32 GB HBM2 - - NVLINK bandwidth 150 GB/s between GPUs and host -- Hostnames: `ml[1-29].power9.hpc.tu-dresden.de` (after - [recabling phase](architecture_2023.md#migration-phase)]) -- Login nodes: `login[1-2].power9.hpc.tu-dresden.de` -- Further information on the usage is documented on the site [GPU Cluster Power9](power9.md) - ## Processing of Data for Input and Output Pre-processing and post-processing of the data is a crucial part for the majority of data-dependent -- GitLab