diff --git a/doc.zih.tu-dresden.de/docs/archive/hardware_overview_2022.md b/doc.zih.tu-dresden.de/docs/archive/hardware_overview_2022.md
new file mode 100644
index 0000000000000000000000000000000000000000..3974a2524de36f7dd2b2fdb03f5a54fa3375f6a0
--- /dev/null
+++ b/doc.zih.tu-dresden.de/docs/archive/hardware_overview_2022.md
@@ -0,0 +1,109 @@
+# HPC Resources
+
+HPC resources in ZIH systems comprise the *High Performance Computing and Storage Complex* and its
+extension *High Performance Computing – Data Analytics*. In total it offers scientists
+about 60,000 CPU cores and a peak performance of more than 1.5 quadrillion floating point
+operations per second. The architecture specifically tailored to data-intensive computing, Big Data
+analytics, and artificial intelligence methods with extensive capabilities for energy measurement
+and performance monitoring provides ideal conditions to achieve the ambitious research goals of the
+users and the ZIH.
+
+## Login and Export Nodes
+
+- 4 Login-Nodes `tauruslogin[3-6].hrsk.tu-dresden.de`
+ - Each login node is equipped with 2x Intel(R) Xeon(R) CPU E5-2680 v3 with 24 cores in total @
+ 2.50 GHz, Multithreading disabled, 64 GB RAM, 128 GB SSD local disk
+ - IPs: 141.30.73.\[102-105\]
+- 2 Data-Transfer-Nodes `taurusexport[3-4].hrsk.tu-dresden.de`
+ - DNS Alias `taurusexport.hrsk.tu-dresden.de`
+ - 2 Servers without interactive login, only available via file transfer protocols
+ (`rsync`, `ftp`)
+ - IPs: 141.30.73.\[82,83\]
+ - Further information on the usage is documented on the site
+ [Export Nodes](../data_transfer/export_nodes.md)
+
+## AMD Rome CPUs + NVIDIA A100
+
+- 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: `taurusi[8001-8034]`
+- Slurm partition: `alpha`
+- Further information on the usage is documented on the site [Alpha Centauri Nodes](../jobs_and_resources/alpha_centauri.md)
+
+## Island 7 - 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: `taurusi[7001-7192]`
+- Slurm partition: `romeo`
+- Further information on the usage is documented on the site [AMD Rome Nodes](../jobs_and_resources/rome_nodes.md)
+
+## Large SMP System HPE Superdome Flex
+
+- 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: `taurussmp8`
+- Slurm partition: `julia`
+- Further information on the usage is documented on the site [HPE Superdome Flex](../jobs_and_resources/sd_flex.md)
+
+## IBM Power9 Nodes for Machine Learning
+
+For machine learning, we have IBM AC922 nodes installed with this configuration:
+
+- 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: `taurusml[1-32]`
+- Slurm partition: `ml`
+
+## Island 6 - Intel Haswell CPUs
+
+- 612 nodes, each with
+ - 2 x Intel(R) Xeon(R) CPU E5-2680 v3 (12 cores) @ 2.50 GHz, Multithreading disabled
+ - 128 GB local memory on SSD
+- Varying amounts of main memory (selected automatically by the batch system for you according to
+ your job requirements)
+ * 594 nodes with 2.67 GB RAM per core (64 GB in total): `taurusi[6001-6540,6559-6612]`
+ - 18 nodes with 10.67 GB RAM per core (256 GB in total): `taurusi[6541-6558]`
+- Hostnames: `taurusi[6001-6612]`
+- Slurm Partition: `haswell`
+
+??? hint "Node topology"
+
+ 
+ {: align=center}
+
+## Island 2 Phase 2 - Intel Haswell CPUs + NVIDIA K80 GPUs
+
+- 64 nodes, each with
+ - 2 x Intel(R) Xeon(R) CPU E5-E5-2680 v3 (12 cores) @ 2.50 GHz, Multithreading disabled
+ - 64 GB RAM (2.67 GB per core)
+ - 128 GB local memory on SSD
+ - 4 x NVIDIA Tesla K80 (12 GB GDDR RAM) GPUs
+- Hostnames: `taurusi[2045-2108]`
+- Slurm Partition: `gpu2`
+- Node topology, same as [island 4 - 6](#island-6-intel-haswell-cpus)
+
+## SMP Nodes - up to 2 TB RAM
+
+- 5 Nodes, each with
+ - 4 x Intel(R) Xeon(R) CPU E7-4850 v3 (14 cores) @ 2.20 GHz, Multithreading disabled
+ - 2 TB RAM
+- Hostnames: `taurussmp[3-7]`
+- Slurm partition: `smp2`
+
+??? hint "Node topology"
+
+ 
+ {: align=center}
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/hdfview_memory.png b/doc.zih.tu-dresden.de/docs/archive/misc/hdfview_memory.png
similarity index 100%
rename from doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/hdfview_memory.png
rename to doc.zih.tu-dresden.de/docs/archive/misc/hdfview_memory.png
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/i4000.png b/doc.zih.tu-dresden.de/docs/archive/misc/i4000.png
similarity index 100%
rename from doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/i4000.png
rename to doc.zih.tu-dresden.de/docs/archive/misc/i4000.png
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/smp2.png b/doc.zih.tu-dresden.de/docs/archive/misc/smp2.png
similarity index 100%
rename from doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/smp2.png
rename to doc.zih.tu-dresden.de/docs/archive/misc/smp2.png
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/slurm_profiling.md b/doc.zih.tu-dresden.de/docs/archive/slurm_profiling.md
similarity index 96%
rename from doc.zih.tu-dresden.de/docs/jobs_and_resources/slurm_profiling.md
rename to doc.zih.tu-dresden.de/docs/archive/slurm_profiling.md
index deb9e3331aa774d11d4f167225074475eff6383f..3ca0a8e2b6e4618923a379ed8bcec854256b7fbf 100644
--- a/doc.zih.tu-dresden.de/docs/jobs_and_resources/slurm_profiling.md
+++ b/doc.zih.tu-dresden.de/docs/archive/slurm_profiling.md
@@ -70,7 +70,8 @@ More information about profiling with Slurm:
## Memory Consumption of a Job
If you are only interested in the maximal memory consumption of your job, you don't need profiling
-at all. This information can be retrieved from within [job files](slurm.md#batch-jobs) as follows:
+at all. This information can be retrieved from within
+[job files](../jobs_and_resources/slurm.md#batch-jobs) as follows:
```bash
#!/bin/bash
diff --git a/doc.zih.tu-dresden.de/docs/index.md b/doc.zih.tu-dresden.de/docs/index.md
index ab6e8ae4f7760d5fc768bf366b55a0e6289cc5c1..789eadf01a601eab561aed67a7909854a9b40506 100644
--- a/doc.zih.tu-dresden.de/docs/index.md
+++ b/doc.zih.tu-dresden.de/docs/index.md
@@ -31,6 +31,7 @@ Please also find out the other ways you could contribute in our
## News
+* **2023-06-01** [New hardware and complete re-design](jobs_and_resources/architecture_2023.md)
* **2023-01-04** [New hardware: NVIDIA Arm HPC Developer Kit](jobs_and_resources/arm_hpc_devkit.md)
* **2022-01-13** [Supercomputing extension for TU Dresden](https://tu-dresden.de/zih/die-einrichtung/news/supercomputing-cluster-2022)
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/architecture_2023.md b/doc.zih.tu-dresden.de/docs/jobs_and_resources/architecture_2023.md
new file mode 100644
index 0000000000000000000000000000000000000000..8894769eff1bbcf06aff553aa800d263f827ff12
--- /dev/null
+++ b/doc.zih.tu-dresden.de/docs/jobs_and_resources/architecture_2023.md
@@ -0,0 +1,57 @@
+# Architectural Re-Design 2023
+
+With the replacement of the Taurus system by the cluster `Barnard` in 2023,
+the rest of the installed hardware had to be re-connected, both with
+Infiniband and with Ethernet.
+
+
+{: align=center}
+
+## Compute Systems
+
+All compute clusters now act as separate entities having their own
+login nodes of the same hardware and their very own Slurm batch systems. The different hardware,
+e.g. Romeo and Alpha Centauri, is no longer managed via a single Slurm instance with
+corresponding partitions. Instead, you as user now chose the hardware by the choice of the
+correct login node.
+
+The login nodes can be used for smaller interactive jobs on the clusters. There are
+restrictions in place, though, wrt. usable resources and time per user. For larger
+computations, please use interactive jobs.
+
+## Storage Systems
+
+### Permananent Filesystems
+
+We now have `/home`, `/projects` and `/software` in a Lustre filesystem. Snapshots
+and tape backup are configured. For convenience, we will make the old home available
+read-only as `/home_old` on the data mover nodes for the data migration period.
+
+`/warm_archive` is mounted on the data movers, only.
+
+### Work Filesystems
+
+With new players with new software in the filesystem market it is getting more and more
+complicated to identify the best suited filesystem for temporary data. In many cases,
+only tests can provide the right answer, for a short time.
+
+For an easier grasp on the major categories (size, speed), the work filesystems now come
+with the names of animals:
+
+* `/data/horse` - 20 PB - high bandwidth (Lustre)
+* `/data/octopus` - 0.5 PB - for interactive usage (Lustre)
+* `/data/weasel` - 1 PB - for high IOPS (WEKA) - coming soon
+
+### Difference Between "Work" And "Permanent"
+
+A large number of changing files is a challenge for any backup system. To protect
+our snapshots and backup from work data,
+`/projects` cannot be used for temporary data on the compute nodes - it is mounted read-only.
+
+Please use our data mover mechanisms to transfer worthy data to permanent
+storages.
+
+## Migration Phase
+
+For about one month, the new cluster Barnard, and the old cluster Taurus
+will run side-by-side - both with their respective filesystems.
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/hardware_overview.md b/doc.zih.tu-dresden.de/docs/jobs_and_resources/hardware_overview.md
index 538296b4ea52aee6c99f132811af8112803adcf9..bf5f25146730bceb6b442bd20d4e08e73e0863fc 100644
--- a/doc.zih.tu-dresden.de/docs/jobs_and_resources/hardware_overview.md
+++ b/doc.zih.tu-dresden.de/docs/jobs_and_resources/hardware_overview.md
@@ -81,7 +81,7 @@ For machine learning, we have IBM AC922 nodes installed with this configuration:
??? hint "Node topology"
- 
+ 
{: align=center}
## Island 2 Phase 2 - Intel Haswell CPUs + NVIDIA K80 GPUs
@@ -105,5 +105,5 @@ For machine learning, we have IBM AC922 nodes installed with this configuration:
??? hint "Node topology"
- 
+ 
{: align=center}
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/hardware_overview_2023.md b/doc.zih.tu-dresden.de/docs/jobs_and_resources/hardware_overview_2023.md
new file mode 100644
index 0000000000000000000000000000000000000000..4580afcae33b7fcff1e8bfe8316d60596ff32295
--- /dev/null
+++ b/doc.zih.tu-dresden.de/docs/jobs_and_resources/hardware_overview_2023.md
@@ -0,0 +1,89 @@
+# HPC Resources
+
+The architecture specifically tailored to data-intensive computing, Big Data
+analytics, and artificial intelligence methods with extensive capabilities
+for performance monitoring provides ideal conditions to achieve the ambitious
+research goals of the users and the ZIH.
+
+## Overview
+
+From the users' perspective, there are separate clusters, all of them with their subdomains:
+
+| Name | Description | Year| DNS |
+| --- | --- | --- | --- |
+| **Barnard** | CPU cluster |2023| n[1001-1630].barnard.hpc.tu-dresden.de |
+| **Romeo** | CPU cluster |2020|i[8001-8190].romeo.hpc.tu-dresden.de |
+| **Alpha Centauri** | GPU cluster |2021|i[8001-8037].alpha.hpc.tu-dresden.de |
+| **Julia** | single SMP system |2021|smp8.julia.hpc.tu-dresden.de |
+| **Power** | IBM Power/GPU system |2018|ml[1-29].power9.hpc.tu-dresden.de |
+
+They run with their own Slurm batch system. Job submission is possible only from
+their respective login nodes.
+
+All clusters have access to these shared parallel filesystems:
+
+| Filesystem | Usable directory | Type | Capacity | Purpose |
+| --- | --- | --- | --- | --- |
+| Home | `/home` | Lustre | quota per user: 20 GB | permanent user data |
+| Project | `/projects` | Lustre | quota per project | permanent project data |
+| Scratch for large data / streaming | `/data/horse` | Lustre | 20 PB | |
+| Scratch for random access | `/data/rabbit` | Lustre | 2 PB | |
+
+These mount points are planned (September 2023):
+
+| Filesystem | Mount Point | Type | Capacity |
+| --- | --- | --- | --- |
+| Scratch for random access | `/data/weasel` | WEKA | 232 TB |
+| Scratch for random access | `/data/squirrel` | BeeGFS | xxx TB |
+
+## Barnard - Intel Sapphire Rapids CPUs
+
+- 630 diskless nodes, each with
+ - 2 x Intel Xeon CPU E5-2680 v3 (52 cores) @ 2.50 GHz, Multithreading enabled
+ - 512 GB RAM
+- Hostnames: `n1[001-630].barnard.hpc.tu-dresden.de`
+- Login nodes: `login[1-4].barnard.hpc.tu-dresden.de`
+
+## AMD Rome CPUs + NVIDIA A100
+
+- 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: `taurusi[8001-8034]` -> `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 [Alpha Centauri Nodes](alpha_centauri.md)
+
+## Island 7 - 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: `taurusi[7001-7192]` -> `i[7001-7190].romeo.hpc.tu-dresden.de`
+- Login nodes: `login[1-2].romeo.hpc.tu-dresden.de`
+- Further information on the usage is documented on the site [AMD Rome Nodes](rome_nodes.md)
+
+## Large SMP System HPE Superdome Flex
+
+- 1 node, with
+ - 32 x Intel Xeon 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: `taurussmp8` -> `smp8.julia.hpc.tu-dresden.de`
+- Further information on the usage is documented on the site [HPE Superdome Flex](sd_flex.md)
+
+## IBM Power9 Nodes for Machine Learning
+
+For machine learning, we have IBM AC922 nodes installed with this configuration:
+
+- 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: `taurusml[1-32]` -> `ml[1-29].power9.hpc.tu-dresden.de`
+- Login nodes: `login[1-2].power9.hpc.tu-dresden.de`
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/migration_2023.md b/doc.zih.tu-dresden.de/docs/jobs_and_resources/migration_2023.md
new file mode 100644
index 0000000000000000000000000000000000000000..4d66900f5018bac5d305205841d5a6b9fea1d905
--- /dev/null
+++ b/doc.zih.tu-dresden.de/docs/jobs_and_resources/migration_2023.md
@@ -0,0 +1,80 @@
+# Migration 2023
+
+## Brief Overview over Coming Changes
+
+All components of Taurus will be dismantled step by step.
+
+### New Hardware
+
+The new HPC system "Barnard" from Bull comes with these main properties:
+
+* 630 compute nodes based on Intel Sapphire Rapids
+* new Lustre-based storage systems
+* HDR Infiniband network large enough to integrate existing and near-future non-Bull hardware
+* To help our users to find the best location for their data we now use the name of
+animals (size, speed) as mnemonics.
+
+More details can be found in the [overview](/jobs_and_resources/hardware_overview_2023).
+
+### New Architecture
+
+Over the last decade we have been running our HPC system of high heterogeneity with a single
+Slurm batch system. This made things very complicated, especially to inexperienced users.
+To lower this hurdle we now create homogenous clusters with their own Slurm instances and with
+cluster specific login nodes running on the same CPU. Job submission is possible only
+from within the cluster (compute or login node).
+
+All clusters will be integrated to the new Infiniband fabric and have then the same access to
+the shared filesystems. This recabling requires a brief downtime of a few days.
+
+[Details on architecture](/jobs_and_resources/architecture_2023).
+
+### New Software
+
+The new nodes run on Linux RHEL 8.7. For a seamless integration of other compute hardware,
+all operating system will be updated to the same versions of OS, Mellanox and Lustre drivers.
+With this all application software was re-built consequently using GIT and CI for handling
+the multitude of versions.
+
+We start with `release/23.04` which is based on software reqeusts from user feedbacks of our
+HPC users. Most major software versions exist on all hardware platforms.
+
+## Migration Path
+
+Please make sure to have read [Details on architecture](/jobs_and_resources/architecture_2023) before
+further reading.
+
+The migration can only be successful as a joint effort of HPC team and users. Here is a description
+of the action items.
+
+|When?|TODO ZIH |TODO users |Remark |
+|---|---|---|---|
+| done (May 2023) |first sync /scratch to /data/horse/old_scratch2| |copied 4 PB in about 3 weeks|
+| done (June 2023) |enable access to Barnard| |initialized LDAP tree with Taurus users|
+| done (July 2023) | |install new software stack|tedious work |
+| ASAP | |adapt scripts|new Slurm version, new resources, no partitions|
+| August 2023 | |test new software stack on Barnard|new versions sometimes require different prerequisites|
+| August 2023| |test new software stack on other clusters|a few nodes will be made available with the new sw stack, but with the old filesystems|
+| ASAP | |prepare data migration|The small filesystems `/beegfs` and `/lustre/ssd`, and `/home` are mounted on the old systems "until the end". They will *not* be migrated to the new system.|
+| July 2023 | sync `/warm_archive` to new hardware| |using datamover nodes with Slurm jobs |
+| September 2023 |prepare recabling of older hardware (Bull)| |integrate other clusters in the IB infrastructure |
+| Autumn 2023 |finalize integration of other clusters (Bull)| |**~2 days downtime**, final rsync and migration of `/projects`, `/warm_archive`|
+| Autumn 2023 ||transfer last data from old filesystems | `/beegfs`, `/lustre/scratch`, `/lustre/ssd` are no longer available on the new systems|
+
+### Data Migration
+
+Why do users need to copy their data? Why only some? How to do it best?
+
+* The sync of hundreds of terabytes can only be done planned and carefully.
+(/scratch, /warm_archive, /projects). The HPC team will use multiple syncs
+to not forget the last bytes. During the downtime, /projects will be migrated.
+* User homes are relatively small and can be copied by the scientists.
+Keeping in mind that maybe deleting and archiving is a better choice.
+* For this, datamover nodes are available to run transfer jobs under Slurm.
+
+### A Graphical Overview
+
+(red: user action required):
+
+
+{: align=center}
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/architecture_2023.drawio b/doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/architecture_2023.drawio
new file mode 100644
index 0000000000000000000000000000000000000000..59ba4ad3b2f8b9387de2ede22079055aa3c9b864
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d/J/54UsCOVjFUA2OS/OcFzyvsPWQAm7kYwL75NJq6D6j9Bu67ChtxLcZH8z6eJkbuE9ZpkwfBd3PSIfhXuvdkR8/miw+OaaywFT33ZDtBMl8mRanz1Ri3ZLtpXgeQdxWXiyzsb1XXK1lDn0Oy1yGvT+NX2R/A9uAZjK3EuqI1Rf4qC2StML4hXzS7o98Gjt4lF9b/zkPSne7vsY1pPAN+h/DzgOL65J7WUZEs53ldps37GdxT3g/jJJ0DvjGxlOgCjRM4ge9D9r1IemRdXu+5L9uYhj7I869ofmBjeKyEH1K/R95kb2gd5eyD23q2Fd2Yk59d1fI3cYB8EV0nLJndkS3bETbdj8S+yz3JntUwDeMBwTTxfty6bnx8XrdtFaaJEYs2cgn0fcE0yB2ZnEFSzMpcAutD/XoL09D85TVMQ7owCSpMMwlZFjxWspMXDXxpYv2knT/rjJX1bTnAWPtwpPVxHRyZLGs+7tlwZEPmdRz5+TKv5W/qMq/nb/pk/hk4kuzOrDd/07xvhSMJd3o1HEnjHcB/emauq3kju93WvU/Lfb4f5TWbXpBNp99i+VF8RfiC4szZU3IHIb32e3MHyLF2cwe7cTSs5w5ofEO3P3cweyB3MPvi3AHynn1YkuPiix4sGWX75KKOJecU02YW2wSC4zGumQd51fB0hVObcti2xsw4nuzYjsdK9rey8/wstBYSo/ssC8zFHedBIJe8eb0+lprud55FYnFaCxcDzCGti4lTYlHCBFZGDYyK65XuN/AZ6QnmkmST1uQu+K4t93ps/4Vyr2NK5PHdfkzZlEM/pkxc/B7s2WjBciJ8NJTf5pgBMXfmVH5WcIv42YkzNn52FCXIG7D/STCeHj+blHlL9l/k/2gNMFaguC1imwp7lLXvh+stP0v2YmXl7ohMJb/KtnJp4kuMcTqzGKmNPbxeH1sM9k/BNInIvHPfxrM/K6apZF3HNF8ga8L1cYU7F9Zmr9z6HDTxY4URjLyRx/JKeReZD/8ELELP5lZYyV7vuW8NQyZVfrjCYIyRCOvSPxV+IV0vZdC4d97U8xYWE7kTtodvGCJfGBiMTVh+ZmpTCWJZGgvnvdnm83Nf7PJzrCNasya+DQk7uByPFjQ/UdPOoG5KuulaH0sypzVJcQ/5GLYziEPkuzl8Ye136N7AnJPafA73tL5D5MWN7AvUF8nOsY7wd5GTI59G9/YRA4j9z3K2O7AjRey07Ut7jPLsc4o/V7ARpHeoocZid8wzig2q33ceNGz6dEj2ZoU8fc2mz3ZkT0i3ZjTmic0R4BloXSauyUeyTEn2yFvSbyOvOTe/tyJ/MLnr+T340j3iR1ofFh/gvtC9fcz3IewQwW61ZT1E3uAhWQfQjZHJD/DcRTHyCPhNjDMgX+ow1lvApsNGNa9/ucyhe4O95OdT2AHXyKZ17z6501qgf8Smx3+/zdYn6ZvXzuXZq9Xbi38hb5CLDxoi90GxMOLeOB+zHCn+Jj+IPAs9bwh9YpwjNpFwVkbzkUL3cl6PEc0v55gQJ0FmFIdQfIRaFtkzwtcDwlUsgz3joAVyLIThYIeKSc72bBFQDJ84fI3WI2pmdJ9dwrYlprU2CNluLed+ws86o+/S33HcYeXHcyz1Irof4Ww8G+w03XsQGoxIeG4WSO6YcAU9Bz0T2bOM7CD0Gz0C81Dq/nPod5hIrmcvNRKuy3mYg/F04Jl5hO1zjPxh38kfZg7WBem6M4oy4Gb6TrKjMfnGzwe0/gv46jE+4/XKuSToJOncai8xIa0X0VN7rRz3O7FJhAEGro0vz7lWR7ECvaffI7+XZpJXzLgOSHFELvoFH0Ax4pJxE9n/VNZXRH5pOrwTmU1846+wNkk3TL2EfC1fh+9ATkDmlNZOavNgW5ob+Bg/ET9Z6ZDY3YK/SzhqdCF6RfEW5p18H2RC+sNxtviE2md990K8RPM3kFoG3wtzOClGYoORl3Flbmguionx5bT2uFYCXZyg7gUcRL6TbCd9n3QhZB9vvkO/R/MzQS2EZUw2iPQFWFX0Wr4/h410uc8k4nomyTuDjvI9SYY+59QEz5Hdx3s7b/g8dcXGYswzX75PNjEi3ef7T3YjiSPvyR/uTX+GuS+PNSdMueOcLda2XHPIDngJcmUX+DzLZawTiruG+bmMMSzreKSHCWOc1JU1VcmPXxdpaHKLyNXtEZuwPMhns7yXg9DkRmmMZPP4Wvlb7DeRk2O5RqnLmIxlSD43wn3IFpvvkwwC5HBLGfJYh5A7xtqUobGftI4N/l8BK9HfrqyPydmnFGxPd7yGpOZG9n/FuVPkN6GvtKaArSh2hA2iuS9SmfNC8oK83guuidJ9aF0tB5zLI513E5E52ecE683YrqHFA8DshdhY5BbngcgCaxVzPzevYWey1mvkHCc2pmY5J7zGyc5M+XNgTsRJsL+IZXHNRy11zHhlBb/I10iurKMjyJVteLpH7kiegfzGBfwX6m2w4fxcgeSCEauS3yYdkLWJPCxhKtsnALtOesu+kmNX6ALH3PRbKebF5boMzYvYtgTfl3EWqcsxCuOXQQFdoO+GiPMknxV7oks0B+QzBBfWZMtzUcpwyzZgShg277UZpB9pwLmYCD4SuA9jMX1hC+j/EDky2NC95O2RPyFdQx8BbHE0yyUWSsh+rPaiKwn3QlW6MjFyTj2zFmFTpR6as48IjQ7hmXCPrr7QuiA7ZOusFJPWfLLk3Gw+CrUYp2/N0jpzTOwGvdmxnGH3CvQnIE4ekE0v1yzW3INrlvBKOL5ordlpDEzOv0V2A7XYe8RFdu5pLUkeB9i+WBEuz8o+NLH1qcHnZFuWs8DmuNAzA2yciI3YmbUF/703Y9iNGIfidyd0n0mtBsj+NiD9ysv7LaBbM8Fq+K6NnREbTmPBMBQjCMZi/Q8kRz8UPUIOFK/ZVmDtxvLb0SRnLIs5lX61Sk8NZrGYsra2MWcejV9wUMS9XPX5JF2ZGVtNvo3z7g/YYjvPS/ZZlR8T277Hc9b8mODUpayxEXp3zto2GJhkYuczQE60aYO5vgR74Ir+zwrbB0n3QT+Ej3w52+JlXM519Rm+R7qM+orpbUTsSzHPXvz1HPVqyA3zdcd6ECVOpVcJ5gq9QXguwhEkhwXbUNJPtnG0rsXGEfZHL1qlzxJP7Kp8LuJf9Crw653YyF0l/+5z1ObNyn0utdWWT0S/F+rbRtcMPl3tDK6wPmJb4S+s94GLPiuxmeRbBMt6qN9yvSvHs8WM1QT/zmyMXXAeX3o7CZuSna7yCyH5NGALqUEx3ogRS8FfmPHN7FoIGP9xXJE4X7AWXJ6fH7UW5G8oPkvaa2LPfutJa0KwncxHkhtcQjJKjT2b454P4xLMbTHYJew/IHuubXLOhf2HkXfCcfAK8TP8zI51l3xLQvHAiLE6etyGouPF0Bd/Dx2fGB1f5YJbVkXCfq+OVWGzy54RI58WHl7OUad0k7yLufHZCDWHhfWtMlfGLtNzxwZHrRxrg2kMEm8tkIcdNOe+5q+Nnu8Z+1l/z34m3SN2N7Uw3+o5/BqtwbaeN+Rc9fvxM4W2ng89R03NyHifCB5ArTMcMVaiNWbjoYLwO/yA+OZAxp8CG+dtPz6KYuDsQvDB0Oj+DH2NNp7aV3pe4hKutxAuCiq7MvwSH763cQLN0T6WOd0ZedI8ZqKz+M40MXYHNo/tIMWCcW7wEup2mcRANBbxqSHpUAB9bcQYX+XDKSZv+nCyLQN3tKj7cPkNztdXuSJPav3zgNZJyLqL+cqbeKiuk1ITQ0w8dGzMh94E8xp42BN5DaQ2gOfl+i7rL9bnXnxE5o0rvMnyLueV7cHKh46LDs0d9CsK/l2hNpGXuPmswrx0n0q3WDcMfo6kroeeBZI5bG1Z72DMMp2bXjjBLBKzDMOkxNYJfHRpp9me2d9hDJntYT/FTtmYgzEs2dW4wtcXgzoW3bb0eFuTn63FsfzLuGsp/tzoeanLNb9q/bCNYXiezm3cJ7qB2mnA9r/CY6X/Ti5sHD6rxeGc+4Stlv45E9Pz2rpAf/KwHjPv27H4CHEx8kqcD2hhlVK/5/tx2XMN3z40ceaMc6Mcu5/VY/msgF6VOj6VPBPNg4O1ajCog9prPU+QRJ2YXmw/8k9mzY7YXuHZM9gSuRdiEmOHZN1zrg222BlV9YAyn9G1MZhP1N8mjfmsxUyoCQGbeISzwxqmRsyDfKDBaZO9yIzHEAo+IFlMk5qNJWxexpUGSyCGyHkt+WTTLJYIgUXlb+O8gZvQh2BwU39sTf50OmzYX6Nzxi+vHOMzUfcJJUamWEtwQfs37JrfIdcjvmDiSf4evW0pfHMZ/0GfgIk/sd6lj571G31Ttg+HMRlyvqHBwQHH0RTPk61xzPotTD5QchSRXb9sa/CsiHkKxnXNWBq4LDdxd874o/acPDc2t1rirLlf9/1Sn8nukbMeXwx6/6a0xdG8hg8mFh84Es/34ODaGIzfJZs18MvnmHJtzeYqfJPXxZ6KoI5Ra7aPe7ZML17O+yDyWo60QNwyCUwuyOTv0oL3OVhMHCU1vzT3aj13e/SAYQ8Txee1/BJscuwI3hoIdmesMTQ4rb0O4lYeQOauxBpiy7CXCr6d543k04h3G2vAYGPYP/gEqf1hvsjOyjqzOSSTV+DYkZ5v6Er8VK4JU59qrAm6d4ZYscRxkktCn0d9PcxIJ4dhj/9zqmsce0m/HOeKMEcZfKzNb+VsB6KB01gHmPcoa/k8wnSSPy/Xn8Qms/2ouwbyJEp6/V1/PukBvX8UD08ew8PV75lYiuz9rqvrqP0O7ZqF/Gtx37xa91VOOWAc19HzmbH1xj+gLlBMzLVJEZtxj0V3bQ8AeiD2qKPa2N74wYxjgyn6uVe2b9P4u2Ertpk5JoeGnuuHY5sqfi9MLtNB3G5iG6eRj7Lxe9nDy/4sb+EMxAZk7yRGfwR/dGoAHOv3YA/+7WjumnXp8Bq+qMYtsiWfuZxJfgL5tYdrADnn44FD8xpuKCbe6KKJGXj/5jS2ca7k9StZljZUxgpZx4XoImpHSR0TyNrhXGijtsH3w/7PGk7Ix9CNDk5I2Z6MynWA+Na+hpxiW7e39RCTu85sPipvxao29s4fzkfZmgDnoxyyKd18lKzbpkzrNQE87xI5JfSmJ42agORmjJ3hdQmMbGO+JBh1agKSt67lee/EzpS4pcqBlHHkQzmQMjYk/LUi+x6b6xT7XFj7PIDvYftl87Uj5H4XqL+t+FqZ/8xpHiP0FeHvsW+XMTDhRMRDMfY0epAlfTdE73WjjrpATDARrNKQFedPWD9q9hn94vwedWT6+9zokdRGcF/0fBVJzU4JPrF7k7mOHQ3LWITnnfNGyP/ZeDpuYhMbD9u8uOQBuF/E6K34vrIWyjXar8hTcG+F8Tmr/Ugwr8/90guLQbi2XOXJar7oHfe2Neyl5Ken2Aed0m9Kn2THvnK/57BmX+cmv13aV8QsganzWvuKWnwgMWlv7qi0r2btsX1tXevkjth2LFq5I+yrxD699vVGjZVzfPvSH5o6w9NsK9cZmrYVPdHiO3zs7+M5MXWGBHXwIjWYL0bdtBhx/cXEKRfA3mlua3+J2NACvXEmB9qJxaq83sr40rnJp3Cs2a4P98VggnX5uWq6y7mcjv30pBdgYvXY+qz2a8lXl/rNMfHW5nCMfSjrbmPkqXrrObGpwSb++OvsLfI7zqhdg7X2tkD9uo6R0bsyKeehqsEOUc808c28kfdrYWSf+9qlfuk0bWuJObs12CrfX+YwbE9F43rZGzC3uSFfbHAamr6vQPJoTXueiG3jmKWWK6xymt3aatCsrTZ1tlXvLePML7S3Tp+9tTHUk+wtsGhe2Vt6pvCB+oetL3K8ENt5jmzcx3m1vvqHjcF2ybRjb5Fz8K1/qOxtF/uX9rayn+Ve/DF6J21dISr11OZky14M2Ar4F8GkA0/qX8DRc9/EdhR/Dpq4DjEiyzvxseeplo/C2qNnZUwYQu5Vbja+K7FPiQcEQ8lrYxs4n8H70VvXa3nhqLQFz2tzTS3wiXhWbMGijmeTCruWPS0T2B/T00LxtvSI1/LNRhfPTP4Y2EZ0CvlGE6+gFp+08Szbxp6elh338UmvRcOeog8J8W9vr8sna61DYwcGZEN6bW3RqZ0vM6/K4bHPxbkEtr5d5t1tjbORdy9t6byVd5/X/Z13Xq91Y99I084S3kl30iMieaR6PNmqe4jdiGp1yMpuNDDwE+oeXWxL352belQd13LsxLh25vTg2sDg2h3vGeR8ZOJXuHZmcW3eg2v9T+Bap7Kzs9DUHhH/5uiJNLYTe4/L3F6JVZs59nrd1vbm2F6XZs5t0ZtfL/M2sveQMAb2nPbj2vC8itvNtTS38dRYYpkuri3zDfOgrL9Nh363/paEvF+uintaeTWb/5deIMkZTArpL2zlxGQ/LeZjb/rmUd9l+zHG/mbZI4lcR1jlUcscN+KMO+mVHRr7NUe+RL4/XVl/z/4bNo30yTE1wlpOrN1PU/NpzdwxekRzE0/U8zycL+A+EevbBBfsJXc8Cc2aruGOIfK7XF+jdRfKWuKeJPbnFhdwTXNR640qr5k82ZRtmd2v7I7Q77vow1vAyKk3juZW/nvZU5CVeGvUj3s/1VNo44cKI4oPCdjPia0tOvkEqTs4j9cdKP5Z0nwVqZWxMzb5KvI9IuPlMDe5PAf9fnX/Kb27q72pbdLnaWBtrOSN5qhVOmat+MihNXInpo+kkzswOIBjhjIHyfUbf8z5e6yFYTenlbcxwKSQPKORF+vsJO/BAEUTAwxbvj42+60nj2AAyRWw3y7rabEr48tyGwN3flvmVOQXmb4Hk8ORtWp6gRaN3FM9FuCeS/Lx2AvRxliyh4h8neR76zpt6x6D/Vhqyg7nrWTOOna3xKx81lnH7vqmZltwH66xuxxTP253fVMHC+Vcraxjd817+AfT+0k4cBk/Fdei58Q3z0Q2MZUeHLKJsh8UmH21G/fb3KCKa2Pk6IvzT/fIob6+q+oY/fX1kWDZXbn/Xux1gHqYwbmetdfYP5WYGob0zD9Yw6jFZ2UNo94vUdUwTLzxRXU8wQYGb+Ecg+xO/F7SssG1WoX4vFKnOI+z5L4qjCvA33XzfBxTNGOEjt1t5cPF7gZVjn2+L3u5iyywvdxJcy1tyxyG4FvgxqKOF40/DAnHG7w527d6ucse9Qr3lrakmUeo5286edz6a8bZtTrHLLe5XdIlrhWJrzC9J9N50LTPjd6Thn02/lJ6T2zMWPA+y/7ek3b+Nqp65ht1B/i2Mi8WP2Sj0VciNppwnulTd/EsorvDcNSqOyTQP5PHkf3Cw6BbX6jsMtu4RdMuE5bwKrs8zyWGGu5trIPeGql7zPaS44L/Q/13aHoVZ671v3J+g/Rzx2XMw7V5W9/r1hnk7AjEcq7kHCp7knT7uQv08wrWQE6A7L/JheLsn9reE4430Ach+Bz1VlOni3g/rq0tmn0uqx10tFZThI3BntK8ZpOx3z20e135vIqHam9lrgpxYtlvaeOvQPp8+/IbxlZGfHZKGwvniLdKLMx4tNmLVtYye2s5A4l9TS9oWXtDLbew/YtcczI+dFDVlwmrkz2k55n5Mp8NP9rqGRjKPp4oDhq9szhDic88ZTte1Ht4xY7X62+DAn1AjRwg427JZbXwyr5Rg6v3Cnxerljqv4wV2vty7Loc2v5ZsTHR6pGeILs3h3vy805PEH0P+bGn9AR15GywNHqUra+tenrmODvCK+36cvhpPI09JcuZzSPb8UnPsqxju49E8DTr0JPzyI3aZ28f4aLRq+y0anVl/1XfHh6z1uv1unBc4ut6P6H0X5U95J1+WdG/sp8CubGCe99sb0yjli05udj21AJX7Nm3y5kYNR1Psfadp+Tk+MwwzsnF36j+UeaRv3CPGWS7qtal1HQLrM3mHrPaMzd1uNUPYOr0Zy39xR53Y0PJhuWmNuKXdbIuLnF6cIk7uuirgSTfUnerXFy3xzuXWMnINm/rLfcN1ms5O873ULxmY0XOXTXlgFhxH/+6XpwXwb/f/vrq/dWbLPszchbcH8dzMsOZDHfo2WEsXaSF3ctP6yegv5E+Zj5DjO1Ezj2zxTyUHA35DPJHZn+lx2cOXch5Ebw3X/YDYJy7srdQzvYpZP9ybM4K4P1KeSLnsLE+yBkwQ9PnaPaiy55K7MULTIyPPJVrzkrCeVkuY17Zhw/fZfpw567MM/ZeTgrGYJyjmTljswcZuUbOwefAR9IvOWI/jzM2sN+a5BOtoFfYi4V92u55eabPvHVdcpz0XdujELJ8sK+M8PkY/QrTmVvVoTJX6jGz8jyqBL3gsDFyLpzL+6bNWSX0XfRl8tkqfMZCeSbeivdf8m8WnFvyOW5m27AyOTD0uSIftkKv0d720I+nc7PnnPSw4HMGCosPJB42vesRzrXj/dbAlehpx9oIuT5MuAdn+mJ/ce2MTPgc9EzidwLeO0HjQC1jLHuP5WwyOdcbe5VRI8qr3HXmjWqYflTWULCXdm7i/pndbwzbTP5y4pmzGoHZfM7x8JktKx91Cd5ThzOBYJMlbuE4Hme1VGdZDM2ZRZWOjYEBTZ6Z9NKVHifZQw4czzUynG3L/eU412GV89lSnJuhOE3uwefQ8Rl/cl6p17puahOr3O6TH/O9sG+N5maZMcYeFWVuPRjJmYlulfPHOk123LvCOoI4ZN7UET7LZWZx7p7xLf2d1PcSOVNjGtu9UiSvGcf8Cdv7CZ/HN+Kzngc2xpV1HGEvhMGR5brD+GeIa7CWgRn9hM+dytD3FpizI8vxs+6zftpzddGfirMbzfgLjt/NuuBeNDP+1PaXFSLP2K/6nJHvSRzZozXYyjmTKewF1jlsHWMePksmQv2E98ND9/b12iJ600eF1L3J5nL+XPokY47/0RNrZBaOuK4xMPmBhi7v+OzAM97rSr8tff7I/XEPDOocUQqsn4kOTzAes9cZ54kg7zTZ05rcc/6V7QHON0WOhvdPV7YZPY9LnKWVcv13xHhpnoldTk1PxsDHvpJEzj3IpXe8ZZOjWcB1EbOf1s4522PukcZ8w/7jPJa59JdH1Toy+sDnn/M6ilIvqXKaYucuAu7HHMveMWuHfakFc64fdjiU/FcGnQpNPo3PKsM5/s3rVZ3axmqylia5nJWOOYtxNp5j5iyw51+QHpl9HUMn4XPwSMYXO5ynyDks1MtLO16dN+EnbOfncpaXrFV3ZPe+RvXP7f1jV3L4jEtdWcvD/ajyeTs+I4nswTn7GPSVJr6pKeMcy1DObmN7b85LmGE/MWqIoTmXgWQwkDOW5NwPb2z34k1ZT4xvxxksfDYP5E/zRjZR1pOL+hXNL8WTk4Y/xlkZI8RpnOeQGuGodZ3XP/bV2HOBxVfSHE1C23tj8rfYm8N7B8dsM7F+4VuGiKcCc0aFuQ6dnHvSo4e+j/LcNYflUsgZgtBz5N46OEJ8fsB7yQXrEn6JWUbYD0Jjs7makP3ZxasIZx3iTG/kVlBX5PnFvokizaAbfI4E53FW/H4U8X6LIinP2EnMWV3lmXDAkD5ytjg7QOyQqQ3CHxcrORNjit/NEF+7UvNJ5cw20ukRn8GP/XipradiHQHj+LIPR/ADzpcCPh9zDWWWm/Nme64bn8N9avNynJAD9uzL+fbAyKiDJOzvE+RJOecAHZoAnwE7wL+SjAamBjd3uF4SDQKTV78jf4ZaKGxBNkYtjM+Piv2GfeFcCGN+Ezule86RIs+CPjzpmXO5/kjYmGupFBdgj4Y5iwZ5kr30ZKfYO+2f2300iHkXnMOHrc0FX804b1dyAWCPKvcT4JwxWrML4YnZMffL2wwsNvj/N2DtyRtUSnUOH+/l8XEPjc83o4bqMnZ9f2qok0Ojhjo5YGqo4wfEfjjUUP6pckMpN5RyQyk3lHJDKTeUckMpN5RyQyk31EC5oZQbSrmhlBtKuaGUG0q5oZQbSrmhlBtKuaGUG0q5oZQbSrmhamNRbijlhlJuKOWGUm4o5YZSbijlhlJuKOWGUm4o5YZSbijlhlJuKOWGUm4o5YZKlBtKuaGUG0q5oZQbSrmhlBtKuaGUG0q5oZQbKrNnyik3lHJDKTeUckMpN5RyQyk3lHJDKTeUckMpN1RvDHan3FDKDaXcUMoNpdxQ9Z4W5YZSbijlhlJuKOWGUm4o5YZSbijlhlJuKOWGUm4o5YZSbijlhoqVG0q5oZQbSrmhlBtKuaGUG0q5oZQbSrmhlBtK1rxyQyk3lHJD3Sk3lHJDKTfUZ9P2HAw3VOD8eG4o8/nhcEMF7uNC+VHcUOWEHS43VOApN5RyQyk3lHJDKTeUckMpN5RyQyk3lHJDDZQbSrmhlBtKuaGUG0q5oZQbSrmhlBtKuaGUG0q5oZQbSrmhlBuqNhblhlJuKOWGUm4o5YZSbijlhlJuKOWGUm4o5YZSbijlhlJuKOWGUm4o5YZSbqhEuaGUG0q5oZQbSrmhlBtKuaGUG0q5oZQbSrmhMnumnHJDKTeUckMpN5RyQyk3lHJDKTeUckMpN5RyQ/XGYHfKDaXcUMoNpdxQyg1V72lRbijlhlJuKOWGUm4o5YZSbijlhlJuKOWGUm4o5YZSbijlhlJuqFi5oZQbSrmhlBtKuaGUG0q5oZQbSrmhlBtKuaFkzSs3lHJDKTfUnXJDKTeUckN9Nm3P4XBDBT+eGyo4OjRuqPCAuaGCB8R+QNxQR8oNpdxQyg2l3FDKDaXcUMoNpdxQyg2l3FAD5YZSbijlhlJuKOWGUm4o5YZSbijlhlJuKOWGUm4o5YZSbijlhqqNRbmhlBtKuaGUG0q5oZQbSrmhlBtKuaGUG0q5oZQbSrmhlBtKuaGUG0q5oZQbKlFuKOWGUm4o5YZSbijlhlJuKOWGUm4o5YZSbqjMnimn3FDKDaXcUMoNpdxQyg2l3FDKDaXcUMoNpdxQvTHYnXJDKTeUckMpN5RyQ9V7WpQbSrmhlBtKuaGUG0q5oZQbSrmhlBtKuaGUG0q5oZQbSrmhlBsqVm4o5YZSbijlhlJuKOWGUm4o5YZSbijlhlJuKFnzyg2l3FDKDXWn3FDKDaXcUJ9N23M43FDHP54bKgwOjRvq5IC5oY4fEPsBcUOdKjeUckMpN5RyQyk3lHJDKTeUckMpN5RyQw2UG0q5oZQbSrmhlBtKuaGUG0q5oZQbSrmhlBtKuaGUG0q5oZQbqjYW5YZSbijlhlJuKOWGUm4o5YZSbijlhlJuKOWGUm4o5YZSbijlhlJuKOWGUm6oRLmhlBtKuaGUG0q5oZQbSrmhlBtKuaGUG0q5oTJ7ppxyQyk3lHJDKTeUckMpN5RyQyk3lHJDKTeUckP1xmB3yg2l3FDKDaXcUMoNVe9pUW4o5YZSbijlhlJuKOWGUm4o5YZSbijlhlJuKOWGUm4o5YZSbqhYuaGUG0q5oZQbSrmhlBtKuaGUG0q5oZQbSrmhZM0rN5RyQyk31J1yQyk3lHJDfTZtz8FwQ4XOj+eGOnIPjBsqdB8Xyo/ihion7HC5oUJPuaGUG0q5oZQbSrmhlBtKuaGUG0q5oZQbaqDcUMoNpdxQyg2l3FDKDaXcUMoNpdxQyg2l3FDKDaXcUMoNpdxQtbEoN5RyQyk3lHJDKTeUckMpN5RyQyk3lHJDKTeUckMpN5RyQyk3lHJDKTeUckMlyg2l3FDKDaXcUMoNpdxQyg2l3FDKDaXcUMoNldkz5ZQbSrmhlBtKuaGUG0q5oZQbSrmhlBtKuaGUG6o3BrtTbijlhlJuKOWGUm6oek+LckMpN5RyQyk3lHJDKTeUckMpN5RyQyk3lHJDKTeUckMpN5RyQ8XKDaXcUMoNpdxQyg2l3FDKDaXcUMoNpdxQyg0la165oZQbSrmh7pQbSrmhlBvqs2l7DocbKuzQ9lxfZdcX5u16s32/zta3lzfD6uqriheJiY/Kvzlfrz+ai8vr7Ta/WBS4yeX9dt3kSrreL7Z/gFbpZWjezQ3JEl5H+/qbvPbm7fVmQc99vbHXbkkGf9TfzKu74m11K35n79UkZ3rh+aenafrXX+Unv5sJ8fmbV4PNZr2rWJzoyusFxMz3epA06259v0mvPyV7Q9i0vdxk1+a74z/32Z/ZIvOX43e/zX67dCbh+S+emX3MzCfVanN9c7ld/H3dGMfz64zfw/30+nKTvsdPe6+3oH16iAwqzW8WpDwb/3FGrXeiZufvyguX6Spj5Rvfb+k21+b6neiZ/9J3HT8ITrzj8OTI85wj+uyv9e3W6KHLUw+artvsscl7who2n4ZH3suwwW3mn3qddX1c/lF9WXsnXz9Fv72+XJ/Hb95d/XH5wXt96y7cIvvF/xlX9WMrtWfVn529ft1Z9d5TV3Wv6N2DX9SfGnZzTb+nm/93fXP1E61mp8lT2LeWj5yelRx8/bycvb55uxn9e+INN+e/B3/9tv7jX//tmZcPa3qcF+Erl1Z5GL184R3dbCHODb3K8Ap0ei/ff0xfvnz5dZSGm/WWNG99S29/OX0uAR/7DQF7YWkZayJ2nR5r+RwgqFfGXerC72AtPx9pPGy/Sstbt7ulFX7A8pZWtjKs8/pnD1pZetc22U8yl5/S70fNpXv63ObSfPXtekFjrohKnZOXxy1/3lY8eSjzxUr3OvcKj04bNwpcr3kjeerOjViJy0f6cr3+Idj+R+v1V6viN9cwP2wDxi9WML/trZzvqmBHPxRm/ihj95wa/iRt7cePTzWcx99HrT3PeR6lJuk0rabzfZXaMnx/gtm4O99Xl3fvS6WuKSuuv73ckvLc8hXP8XvjjSYua8PcB7Xk0UmtYaqwB7baa18598FpE9T5Nof1uXPfuVHwXB6T3m7W6239zwnvvk/WV9f4i/8H</diagram></mxfile>
\ No newline at end of file
diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/architecture_2023.png b/doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/architecture_2023.png
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diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/migration_2023.png b/doc.zih.tu-dresden.de/docs/jobs_and_resources/misc/migration_2023.png
new file mode 100644
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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 d3e9674ced87e57dc6f45ccafccd71383c86d921..20a542d3abed3cd59b299c5d6560bc451f3eead0 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
@@ -1,7 +1,7 @@
# HPC Resources and Jobs
-ZIH operates a high performance computing (HPC) system with more than 60.000 cores, 720 GPUs, and a
-flexible storage hierarchy with about 16 PB total capacity. The HPC system provides an optimal
+ZIH operates high performance computing (HPC) systems with more than 90.000 cores, 500 GPUs, and
+a flexible storage hierarchy with about 20 PB total capacity. The HPC system provides an optimal
research environment especially in the area of data analytics and machine learning as well as for
processing extremely large data sets. Moreover it is also a perfect platform for highly scalable,
data-intensive and compute-intensive applications.
@@ -58,12 +58,12 @@ automatically select a suitable partition depending on your memory and GPU requi
**MPI jobs:** For MPI jobs typically allocates one core per task. Several nodes could be allocated
if it is necessary. The batch system [Slurm](slurm.md) will automatically find suitable hardware.
-Normal compute nodes are perfect for this task.
**OpenMP jobs:** SMP-parallel applications can only run **within a node**, so it is necessary to
include the [batch system](slurm.md) options `-N 1` and `-n 1`. Using `--cpus-per-task N` Slurm will
start one task and you will have `N` CPUs. The maximum number of processors for an SMP-parallel
-program is 896 on partition `julia`, see [partitions](partitions_and_limits.md).
+program is 896 on partition `julia`, see [partitions](partitions_and_limits.md) (be aware that
+the application has to be developed with that large number of threads in mind).
Partitions with GPUs are best suited for **repetitive** and **highly-parallel** computing tasks. If
you have a task with potential [data parallelism](../software/gpu_programming.md) most likely that
@@ -71,7 +71,9 @@ you need the GPUs. Beyond video rendering, GPUs excel in tasks such as machine
simulations and risk modeling. Use the partitions `gpu2` and `ml` only if you need GPUs! Otherwise
using the x86-based partitions most likely would be more beneficial.
-**Interactive jobs:** Slurm can forward your X11 credentials to the first node (or even all) for a job
+**Interactive jobs:** An interactive job is the best choice for testing and development. See
+ [interactive-jobs](slurm.md).
+Slurm can forward your X11 credentials to the first node (or even all) for a job
with the `--x11` option. To use an interactive job you have to specify `-X` flag for the ssh login.
## Interactive vs. Batch Mode
diff --git a/doc.zih.tu-dresden.de/docs/misc/migration2023.drawio b/doc.zih.tu-dresden.de/docs/misc/migration2023.drawio
new file mode 100644
index 0000000000000000000000000000000000000000..9679fffb77fa898a7e01fb939c258ec991808b6a
--- /dev/null
+++ b/doc.zih.tu-dresden.de/docs/misc/migration2023.drawio
@@ -0,0 +1 @@
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</diagram></mxfile>
\ No newline at end of file
diff --git a/doc.zih.tu-dresden.de/docs/misc/migration2023.png b/doc.zih.tu-dresden.de/docs/misc/migration2023.png
new file mode 100644
index 0000000000000000000000000000000000000000..6f74947fa72520a8d3273a2e58ef17aeb478d745
Binary files /dev/null and b/doc.zih.tu-dresden.de/docs/misc/migration2023.png differ
diff --git a/doc.zih.tu-dresden.de/docs/software/performance_engineering_overview.md b/doc.zih.tu-dresden.de/docs/software/performance_engineering_overview.md
index 0807db9ac0b6474b9a8051639fbad6466a03df09..b8c79afa6c2ab2b224eed7361b84a1e8a57501ae 100644
--- a/doc.zih.tu-dresden.de/docs/software/performance_engineering_overview.md
+++ b/doc.zih.tu-dresden.de/docs/software/performance_engineering_overview.md
@@ -44,7 +44,6 @@ software performance engineering or application performance engineering within s
| [Perf](#perf-tools) | Produce and visualize [profile](#profile) | easy | medium | low | (no)[^2] |
| [PIKA](#pika) | Show performance [profile](#profile) and [trace](#trace) | very easy | low | very low | no |
| [Score-P](#score-p) | Create performance [trace](#trace) | complex | high | variable | yes |
-| [Slurm](#slurm-profiler) | Produce and visualize simple [trace](#trace)| easy | low | low | no |
| [Vampir](#vampir) | Visualize performance [trace](#trace) | complex | high | n.a. | n.a. |
[^2]: Re-compilation is not required. Yet, to obtain more details it is recommended to re-compile with the `-g` compiler option, which adds debugging information to the executable of an application.
@@ -248,19 +247,6 @@ Many raw data sources are supported by Score-P.
It requires some time, training, and practice to fully benefit from the tool's features.
See [Score-P](scorep.md) for further details.
-### Slurm Profiler
-
-!!! hint "Easy to use performance visualization of entire batch jobs"
-
-The [Slurm Profiler](../jobs_and_resources/slurm_profiling.md) gathers performance data from every
-task/node of a given [batch job](../jobs_and_resources/slurm.md).
-It records a coarse-grained [trace](#trace) for subsequent analysis.
-[Instrumentation](#instrumentation) of the applications under test is not needed.
-The data analysis of the given set of system metrics needs to be initiated by the user with a
-command line interface.
-The resulting performance metrics are accessible in a simple graphical front-end that provides
-time/performance graphs.
-
### Vampir
!!! hint "Complex and powerful performance data visualization of parallel applications"
diff --git a/doc.zih.tu-dresden.de/mkdocs.yml b/doc.zih.tu-dresden.de/mkdocs.yml
index 6b59050a90bdec12d51ea958b69252047bfee303..8d219134442fafb3e42ccb1804ce870043a7d6b6 100644
--- a/doc.zih.tu-dresden.de/mkdocs.yml
+++ b/doc.zih.tu-dresden.de/mkdocs.yml
@@ -93,7 +93,6 @@ nav:
- Produce Performance Overview with Perf: software/perf_tools.md
- Track Slurm Jobs with PIKA: software/pika.md
- Record Course of Events with Score-P: software/scorep.md
- - Profile Jobs with Slurm: jobs_and_resources/slurm_profiling.md
- Study Course of Events with Vampir: software/vampir.md
- Measure Energy Consumption: software/energy_measurement.md
- Compare System Performance with SPEChpc: software/spec.md
@@ -102,6 +101,10 @@ nav:
- Overview: jobs_and_resources/overview.md
- HPC Resources:
- Overview: jobs_and_resources/hardware_overview.md
+ - New Systems 2023:
+ - Architectural Re-Design 2023: jobs_and_resources/architecture_2023.md
+ - Overview 2023: jobs_and_resources/hardware_overview_2023.md
+ - Migration 2023: jobs_and_resources/migration_2023.md
- AMD Rome Nodes: jobs_and_resources/rome_nodes.md
- NVMe Storage: jobs_and_resources/nvme_storage.md
- Alpha Centauri: jobs_and_resources/alpha_centauri.md
@@ -113,7 +116,6 @@ nav:
- Partitions and Limits: jobs_and_resources/partitions_and_limits.md
- Slurm Job File Generator: jobs_and_resources/slurm_generator.md
- Checkpoint/Restart: jobs_and_resources/checkpoint_restart.md
- - Job Profiling: jobs_and_resources/slurm_profiling.md
- Binding and Distribution of Tasks: jobs_and_resources/binding_and_distribution_of_tasks.md
- User Support: support/support.md
- Archive:
@@ -126,7 +128,9 @@ nav:
- Platform LSF: archive/platform_lsf.md
- BeeGFS Filesystem on Demand: archive/beegfs_on_demand.md
- Jupyter Installation: archive/install_jupyter.md
+ - Profile Jobs with Slurm: archive/slurm_profiling.md
- Switched-Off Systems:
+ - Overview 2022: archive/hardware_overview_2022.md
- Overview: archive/systems_switched_off.md
- Migration From Deimos to Atlas: archive/migrate_to_atlas.md
- System Altix: archive/system_altix.md