Update tutorial to align with the new Aerial release (25-3)
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@@ -1,4 +1,4 @@
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# OAI 7.2 Fronthaul Interface 5G SA Tutorial
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# OAI - Aerial FAPI Split Tutorial
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**Table of Contents**
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**Table of Contents**
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@@ -14,9 +14,12 @@ The hardware on which we have tried this tutorial:
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| Dell PowerEdge R750 (Dual Intel Xeon Gold 6336Y CPU @ 2.4G, 24C/48T (185W), 512GB RDIMM, 3200MT/s) |Ubuntu 22.04.3 LTS (5.15.0-72-lowlatency)| NVIDIA Converged Accelerator A100X (24.39.2048) |
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| Dell PowerEdge R750 (Dual Intel Xeon Gold 6336Y CPU @ 2.4G, 24C/48T (185W), 512GB RDIMM, 3200MT/s) |Ubuntu 22.04.3 LTS (5.15.0-72-lowlatency)| NVIDIA Converged Accelerator A100X (24.39.2048) |
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| Supermicro Grace Hopper MGX ARS-111GL-NHR (Neoverse-V2, 3.4GHz, 72C/72T, 576GB LPDDR5) | Ubuntu 22.04.5 LTS (6.5.0-1019-nvidia-64k) |NVIDIA BlueField3 (32.41.1000)|
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| Supermicro Grace Hopper MGX ARS-111GL-NHR (Neoverse-V2, 3.4GHz, 72C/72T, 576GB LPDDR5) | Ubuntu 22.04.5 LTS (6.5.0-1019-nvidia-64k) |NVIDIA BlueField3 (32.41.1000)|
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**NOTE**:
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**Note**:
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- These are not minimum hardware requirements. This is the configuration of our servers. The NIC card should support hardware PTP time stamping.
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- These are not minimum hardware requirements. This is the configuration of our
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- Starting from tag [2025.w13](https://gitlab.eurecom.fr/oai/openairinterface5g/-/tree/2025.w13?ref_type=tags) of OAI, we are only testing with the Grace Hopper server.
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servers. The NIC card should support hardware PTP time stamping.
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- Starting from tag
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[2025.w13](https://gitlab.eurecom.fr/oai/openairinterface5g/-/tree/2025.w13?ref_type=tags)
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of OAI, we are only testing with the Grace Hopper server.
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PTP enabled switches and grandmaster clock we have tested with:
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PTP enabled switches and grandmaster clock we have tested with:
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@@ -54,10 +57,10 @@ The UEs that have been tested and confirmed working with Aerial are the followin
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To set up the L1 and install the components manually refer to this [instructions page](https://docs.nvidia.com/aerial/cuda-accelerated-ran/index.html).
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To set up the L1 and install the components manually refer to this [instructions page](https://docs.nvidia.com/aerial/cuda-accelerated-ran/index.html).
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**Note**:
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**Note**:
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- As of wk36, the L1 must be compiled with the following CMake flag: `-DSCF_FAPI_10_04_SRS=ON` , this is due to the usage
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- To configure the Gigabyte server please refer to these
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of the FAPI 10.04 version of the SRS PDU, and RX_Beamforming PDU.
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[instructions](https://gitlab.eurecom.fr/oai/openairinterface5g/-/blob/2025.w13/doc/Aerial_FAPI_Split_Tutorial.md)
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- To configure the Gigabyte server please refer to these [instructions](https://gitlab.eurecom.fr/oai/openairinterface5g/-/blob/2025.w13/doc/Aerial_FAPI_Split_Tutorial.md)
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- The last release to support the Gigabyte server is **Aerial CUDA-Accelerated
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- The last release to support the Gigabyte server is **Aerial CUDA-Accelerated RAN 24-1**.
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RAN 24-1**.
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#### CPU allocation
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#### CPU allocation
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@@ -67,21 +70,43 @@ of the FAPI 10.04 version of the SRS PDU, and RX_Beamforming PDU.
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**Grace Hopper MGX ARS-111GL-NHR**
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**Grace Hopper MGX ARS-111GL-NHR**
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| Applicative Threads | Allocated CPUs |
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| Applicative Threads | Allocated CPUs |
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|------------------------|----------------|
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|--------------------------------------|--------------------------------|
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| PTP & PHC2SYS Services | 41 |
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| `workers_ul` | 4, 5 |
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| OAI `nr-softmodem` | 13-16 |
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| `workers_dl` | 6, 7, 8 |
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| `timer_thread_config` | 9 |
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| `message_thread_config` | 9 |
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| `pcap_shm_caching_cpu_core` | 10 |
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| `pcap_file_saving_cpu_core` | 10 |
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| `dpdk_thread` | 10 |
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| `ul_pcap_capture_thread_cpu_affinity`| 10 |
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| `pcap_logger_thread_cpu_affinity` | 10 |
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| `h2d_copy_thread_cpu_affinity` | 11 |
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| `fh_stats_dump_cpu_core` | -1 |
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| `pdump_client_thread` | -1 |
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| `debug_worker` | -1 |
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| `prometheus_thread` | -1 |
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| OAI `nr-softmodem` | 13,14,15,16 |
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### PTP configuration
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**Note**:
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- `-1` indicates that no explicit CPU pinning is applied and the thread
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is scheduled by the Linux kernel.
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- core 10 is a `low_priority_core` and it is shared by all low-priority threads.
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1. You need to install the `linuxptp` debian package. It will install both ptp4l and phc2sys.
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#### PTP configuration
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1. Install the `linuxptp` debian package. It will install both
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ptp4l and phc2sys.
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```bash
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```bash
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#Ubuntu
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#Ubuntu
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sudo apt install linuxptp -y
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sudo apt install linuxptp -y
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```
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```
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Once installed you can use this configuration file for ptp4l (`/etc/ptp4l.conf`). Here the clock domain is 24 so you can adjust it according to your PTP GM clock domain
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Once installed you can use this configuration file for ptp4l
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(`/etc/ptp4l.conf`). Here the clock domain is 24 so you can adjust it according
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to your PTP GM clock domain
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```
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```
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[global]
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[global]
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@@ -94,25 +119,27 @@ tx_timestamp_timeout 30
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network_transport L2
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network_transport L2
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```
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```
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The service of ptp4l (`/lib/systemd/system/ptp4l.service`) should be configured
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as below:
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The service of ptp4l (`/lib/systemd/system/ptp4l.service`) should be configured as below:
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```
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```
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[Unit]
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[Unit] Description=Precision Time Protocol (PTP) service
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Description=Precision Time Protocol (PTP) service
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Documentation=man:ptp4l
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Documentation=man:ptp4l
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[Service]
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[Service]
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Restart=always
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Restart=always
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RestartSec=5s
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RestartSec=5s
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Type=simple
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Type=simple
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ExecStart=taskset -c 41 /usr/sbin/ptp4l -f /etc/ptp.conf
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ExecStart=/usr/sbin/ptp4l -f /etc/ptp.conf
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[Install]
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[Install]
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WantedBy=multi-user.target
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WantedBy=multi-user.target
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```
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```
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and service of phc2sys (`/lib/systemd/system/phc2sys.service`) should be configured as below:
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and service of phc2sys (`/lib/systemd/system/phc2sys.service`) should be
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configured as below:
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```
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```
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[Unit]
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[Unit]
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Description=Synchronize system clock or PTP hardware clock (PHC)
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Description=Synchronize system clock or PTP hardware clock (PHC)
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@@ -131,10 +158,25 @@ ExecStart=/usr/sbin/phc2sys -a -r -n 24
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WantedBy=multi-user.target
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WantedBy=multi-user.target
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```
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```
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**Note**: As of release 25-3 there's no need to allocate a core for PTP.
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## Prepare the L1
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- Follow these
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[instructions](https://github.com/NVIDIA/aerial-cuda-accelerated-ran) to
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clone the `aerial-cuda-accelerated-ran` repository, pull and build the cuBB
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image.
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- The CMake flags we use to compile the L1 are:
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- `-DSCF_FAPI_10_04_SRS=ON` this flag must be used as of OAI tag `2025.w36`
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and this is due to the usage of the FAPI 10.04 version of the SRS PDU, and
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RX_Beamforming PDU.
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- `-DENABLE_CONFORMANCE_TM_PDSCH_PDCCH=OFF` this option should only be
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enabled when doing conformance testing with testmac.
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## Build OAI gNB
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## Build OAI gNB
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If it's not already cloned, the first step is to clone OAI repository
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If it's not already cloned, the first step is to clone OAI repository
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```bash
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```bash
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git clone https://gitlab.eurecom.fr/oai/openairinterface5g.git ~/openairinterface5g
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git clone https://gitlab.eurecom.fr/oai/openairinterface5g.git ~/openairinterface5g
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cd ~/openairinterface5g/
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cd ~/openairinterface5g/
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@@ -142,65 +184,42 @@ cd ~/openairinterface5g/
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### Get nvIPC sources from the L1 container
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### Get nvIPC sources from the L1 container
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The library used for communication between L1 and L2 components is called nvIPC, and is developed by NVIDIA. It is not open-source and can't be freely distributed.
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The library used for communication between L1 and L2 components is called
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In order to achieve this communication, we need to obtain the nvIPC source files from the L1 container (cuBB) and place it in the gNB project directory `~/openairinterface5g`.
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nvIPC, and is developed by NVIDIA. In order to achieve this communication, we
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This allows us to build and install this library when building the L2 docker container.
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need to obtain the nvIPC source files from the L1 container (cuBB) and place it
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in the gNB project directory `~/openairinterface5g`. This allows us to build
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Check whether your L1 container is running:
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and install this library when building the L2 docker image.
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```bash
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~$ docker container ls -a
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CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
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a9681a0c4a10 14dca2002237 "/opt/nvidia/nvidia_…" 3 months ago Exited (137) 10 days ago cuBB
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```
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If it is not running, you may start it and logging into the container by running the following:
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```bash
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~$ docker start cuBB
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cuBB
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~$ docker exec -it cuBB bash
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aerial@c_aerial_aerial:/opt/nvidia/cuBB#
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```
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After logging into the container, you need to pack the nvIPC sources and copy them to the host ( the command creates a `tar.gz` file with the following name format: `nvipc_src.YYYY.MM.DD.tar.gz`)
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```bash
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~$ docker exec -it cuBB bash
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aerial@c_aerial_aerial:/opt/nvidia/cuBB# cd cuPHY-CP/gt_common_libs
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aerial@c_aerial_aerial:/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs#./pack_nvipc.sh
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nvipc_src.YYYY.MM.DD/
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...
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---------------------------------------------
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Pack nvipc source code finished:
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/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs/nvipc_src.YYYY.MM.DD.tar.gz
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aerial@c_aerial_aerial:/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs# sudo cp nvipc_src.yyyy.mm.dd.tar.gz /opt/cuBB/share/
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aerial@c_aerial_aerial:/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs# exit
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```
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The file should now be present in the `~/openairinterface5g/ci-scripts/yaml_files/sa_gnb_aerial/` directory, from where it is moved into `~/openairinterface5g`
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```bash
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~$ mv ~/openairinterface5g/ci-scripts/yaml_files/sa_gnb_aerial/nvipc_src.YYYY.MM.DD.tar.gz ~/openairinterface5g/
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```
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Alternatively, after running `./pack_nvipc.sh` , you can exit the container and copy `nvipc_src.YYYY.MM.DD.tar.gz` using `docker cp`
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```bash
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```bash
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~$ docker exec -it cuBB bash
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# Start interactive development container
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aerial@c_aerial_aerial:/opt/nvidia/cuBB# cd cuPHY-CP/gt_common_libs
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./cuPHY-CP/container/run_aerial.sh
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aerial@c_aerial_aerial:/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs#./pack_nvipc.sh
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nvipc_src.YYYY.MM.DD/
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# Pack the nvIPC sources and copy them to the host ( the command creates a `tar.gz` file with the following name format: `nvipc_src.YYYY.MM.DD.tar.gz`)
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...
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aerial@c_aerial_oaicicd:/opt/nvidia/cuBB# cd cuPHY-CP/gt_common_libs
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---------------------------------------------
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aerial@c_aerial_oaicicd:/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs#./pack_nvipc.sh
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Pack nvipc source code finished:
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nvipc_src.YYYY.MM.DD/ ... --------------------------------------------- Pack
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/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs/nvipc_src.YYYY.MM.DD.tar.gz
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nvipc source code finished:/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs/nvipc_src.YYYY.MM.DD.tar.gz
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aerial@c_aerial_aerial:/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs# exit
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~$ docker cp nv-cubb:/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs/nvipc_src.YYYY.MM.DD.tar.gz ~/openairinterface5g
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```
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```
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*Important note:* For using docker cp, make sure to copy the entire name of the created nvipc_src tar.gz file.
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Keep the interactive development container open and in another terminal use
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`docker cp` to copy the library
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```bash
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docker cp c_aerial_oaicicd:/opt/nvidia/cuBB/cuPHY-CP/gt_common_libs/nvipc_src.YYYY.MM.DD.tar.gz ~/openairinterface/
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```
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*Important note:* For using docker cp, make sure to
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copy the entire name of the created nvipc_src tar.gz file.
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You can now exit the interactive development container.
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With the nvIPC sources in the project directory, the L2 docker image can be built.
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With the nvIPC sources in the project directory, the docker image can be built.
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### Building OAI gNB docker image
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### Building OAI gNB docker image
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In order to build the target image (`oai-gnb-aerial`), first you should build a common shared image (`ran-base`)
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In order to build the target image (`oai-gnb-aerial`), first you should build a
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common shared image (`ran-base`)
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```bash
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```bash
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~$ cd ~/openairinterface5g/
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~$ cd ~/openairinterface5g/
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~/openairinterface5g$ docker build . -f docker/Dockerfile.base.ubuntu --tag ran-base:latest
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~/openairinterface5g$ docker build . -f docker/Dockerfile.base.ubuntu --tag ran-base:latest
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@@ -210,52 +229,113 @@ In order to build the target image (`oai-gnb-aerial`), first you should build a
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## Running the setup
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## Running the setup
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In order to use Docker Compose to automatically start and stop the setup, we first need to create a pre-built image of L1 after compiling the L1 software and making the necessary adjustments to its configuration files.
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The process of preparing L1 is covered in NVIDIA's documentation and falls outside the scope of this document.
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### Prepare the L1 image
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After preparing the L1 software, the container needs to be committed to create an image where L1 is ready for execution, which can later be referenced by a `docker-compose.yaml` file.
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*Note:* The default L1 configuration file is `cuphycontroller_P5G_FXN_GH.yaml`, located in `/opt/nvidia/cuBB/cuPHY-CP/cuphycontroller/config/`.
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In this file the RU MAC address needs to be specified before commiting the image.
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```bash
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~$ docker commit nv-cubb cubb-build:25-2.1
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~$ docker image ls
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..
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cubb-build 25-2.1 824156e0334c 2 weeks ago 23.9GB
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-..
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```
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### Adapt the OAI-gNB configuration file to your system/workspace
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### Adapt the OAI-gNB configuration file to your system/workspace
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Edit the sample OAI gNB configuration file and check following parameters:
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Edit the [OAI gNB configuration file](https://gitlab.eurecom.fr/oai/openairinterface5g/-/blob/develop/ci-scripts/conf_files/gnb-vnf.sa.band78.273prb.aerial.conf?ref_type=heads)
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and check the following parameters:
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* `gNBs` section
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* `gNBs` section
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* The PLMN section shall match the one defined in the AMF
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* The PLMN section shall match the one defined in the AMF
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* To calculate the `absoluteFrequencySSB` and `dl_absoluteFrequencyPointA`,
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please follow these
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[instructions](https://gitlab.eurecom.fr/oai/openairinterface5g/-/blob/develop/doc/gNB_frequency_setup.md)
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* `amf_ip_address` shall be the correct AMF IP address in your system
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* `amf_ip_address` shall be the correct AMF IP address in your system
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* `GNB_IPV4_ADDRESS_FOR_NG_AMF` shall match your DU N2 interface IP address
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* `GNB_IPV4_ADDRESS_FOR_NG_AMF` shall match your DU N2 interface IP address
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* `GNB_IPV4_ADDRESS_FOR_NGU` shall match your DU N3 interface IP address
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* `GNB_IPV4_ADDRESS_FOR_NGU` shall match your DU N3 interface IP address
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The default amf_ip_address:ipv4 value is 192.168.70.132, when installing the CN5G following [this tutorial](https://gitlab.eurecom.fr/oai/openairinterface5g/-/blob/develop/doc/NR_SA_Tutorial_OAI_CN5G.md)
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The default amf_ip_address:ipv4 value is 192.168.70.132, when installing the
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||||||
Both 'GNB_IPV4_ADDRESS_FOR_NG_AMF' and 'GNB_IPV4_ADDRESS_FOR_NGU' need to be set to the IP address of the NIC referenced previously.
|
CN5G following [this
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||||||
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tutorial](https://gitlab.eurecom.fr/oai/openairinterface5g/-/blob/develop/doc/NR_SA_Tutorial_OAI_CN5G.md)
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||||||
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Both `GNB_IPV4_ADDRESS_FOR_NG_AMF` and `GNB_IPV4_ADDRESS_FOR_NGU` need to be
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||||||
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set to the IP address of the NIC referenced previously.
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||||||
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||||||
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**Note**: If the Core Network is running on the same server, 3 cores should be
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||||||
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allocated to it. 2 for the UPF and 1 for the all the remaining services as shown
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||||||
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below.
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||||||
|
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||||||
### Running docker compose
|
```patch
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||||||
#### Aerial L1 entrypoint script
|
diff --git a/docker-compose/docker-compose-basic-nrf.yaml b/docker-compose/docker-compose-basic-nrf.yaml
|
||||||
The `aerial_l1_entrypoint` script is used by the L1 container to start the L1 software and is called in the Docker Compose file.
|
index 7fbefc9..d5ef964 100644
|
||||||
It begins by setting up environment variables, restarting NVIDIA MPS, and finally running `cuphycontroller_scf`.
|
--- a/docker-compose/docker-compose-basic-nrf.yaml
|
||||||
|
+++ b/docker-compose/docker-compose-basic-nrf.yaml
|
||||||
|
@@ -28,6 +28,7 @@ services:
|
||||||
|
- 8080/tcp
|
||||||
|
volumes:
|
||||||
|
- ./conf/basic_nrf_config.yaml:/openair-udr/etc/config.yaml
|
||||||
|
+ cpuset: "15"
|
||||||
|
environment:
|
||||||
|
- TZ=Europe/Paris
|
||||||
|
depends_on:
|
||||||
|
```
|
||||||
|
|
||||||
The L1 software is executed with an argument that specifies which configuration file to use. If not modified, the default argument is set to `P5G_FXN_GH`.
|
### Aerial L1 entrypoint script
|
||||||
|
|
||||||
After building the gNB image, and preparing the configuration file, the setup can be run with the following command:
|
The `aerial_l1_entrypoint` script is used by the L1 container to start the L1
|
||||||
|
software and is mounted in the Docker Compose file. It begins by setting up
|
||||||
|
environment variables, restarting NVIDIA MPS, and finally running
|
||||||
|
`cuphycontroller_scf`.
|
||||||
|
|
||||||
|
The L1 software is executed with an argument that specifies which configuration
|
||||||
|
file to use. If not modified, the default argument is set to `P5G_WNC_GH`.
|
||||||
|
|
||||||
|
### Aerial L1 configuration
|
||||||
|
|
||||||
|
```bash
|
||||||
|
cd ~/aerial-cuda-accelerated-ran/cuPHY-CP/cuphycontroller/config/
|
||||||
|
```
|
||||||
|
|
||||||
|
Choose the configuration file that matches your setup and make the necessary
|
||||||
|
changes. We currently use `cuphycontroller_P5G_WNC_GH.yaml`.
|
||||||
|
|
||||||
|
Make sure that the following parameters are modified:
|
||||||
|
|
||||||
|
```
|
||||||
|
dst_mac_addr:
|
||||||
|
nic:
|
||||||
|
vlan:
|
||||||
|
```
|
||||||
|
|
||||||
|
### Docker compose
|
||||||
|
|
||||||
|
We recommend the user to apply the patch below for `docker-compose.yaml`.
|
||||||
|
```patch
|
||||||
|
diff --git a/ci-scripts/yaml_files/sa_gnb_aerial/docker-compose.yaml b/ci-scripts/yaml_files/sa_gnb_aerial/docker-compose.yaml
|
||||||
|
index 985fe9a6a3..0774d826ac 100644
|
||||||
|
--- a/ci-scripts/yaml_files/sa_gnb_aerial/docker-compose.yaml
|
||||||
|
+++ b/ci-scripts/yaml_files/sa_gnb_aerial/docker-compose.yaml
|
||||||
|
@@ -15,10 +15,10 @@ services:
|
||||||
|
stdin_open: true
|
||||||
|
tty: true
|
||||||
|
volumes:
|
||||||
|
+ - ~/aerial-cuda-accelerated-ran:/opt/nvidia/cuBB/
|
||||||
|
- /lib/modules:/lib/modules
|
||||||
|
- /dev/hugepages:/dev/hugepages
|
||||||
|
- /usr/src:/usr/src
|
||||||
|
- - ./cuphycontroller_P5G_WNC_GH.yaml:/opt/nvidia/cuBB/cuPHY-CP/cuphycontroller/config/cuphycontroller_P5G_WNC_GH.yaml
|
||||||
|
- ./aerial_l1_entrypoint.sh:/opt/nvidia/cuBB/aerial_l1_entrypoint.sh
|
||||||
|
- /var/log/aerial:/var/log/aerial
|
||||||
|
- ../../../cmake_targets/share:/opt/cuBB/share
|
||||||
|
```
|
||||||
|
|
||||||
|
By applying this change, it would easier for the user to modify the L1 code or
|
||||||
|
configuration files directly from the `aerial-cuda-accelerated-ran` repository.
|
||||||
|
|
||||||
|
`ci-scripts/yaml_files/sa_gnb_aerial/docker-compose.yaml` is tailored for our
|
||||||
|
CI.
|
||||||
|
We copy the `aerial-cuda-accelerated-ran` repository inside the cuBB
|
||||||
|
docker image using `docker cp` and commit the changes using `docker commit`.
|
||||||
|
We mount the `cuphycontroller_P5G_WNC_GH.yaml` in the `nv-cubb` volumes so
|
||||||
|
that it would override some parameters depending on the setup being run on CI.
|
||||||
|
|
||||||
|
After building the gNB image, and preparing the configuration file, the setup
|
||||||
|
can be run with the following command:
|
||||||
|
|
||||||
```bash
|
```bash
|
||||||
cd ci-scripts/yaml_files/sa_gnb_aerial/
|
cd ci-scripts/yaml_files/sa_gnb_aerial/
|
||||||
docker compose up -d
|
docker compose up -d
|
||||||
|
|
||||||
```
|
```
|
||||||
This will start both containers, beginning with `nv-cubb`, and `oai-gnb-aerial` will start only after it is ready.
|
This will start both containers, beginning with `nv-cubb`, and
|
||||||
|
`oai-gnb-aerial` will start only after it is ready.
|
||||||
|
|
||||||
The logs can be followed using these commands:
|
The logs can be followed using these commands:
|
||||||
|
|
||||||
@@ -263,8 +343,13 @@ The logs can be followed using these commands:
|
|||||||
docker logs -f oai-gnb-aerial
|
docker logs -f oai-gnb-aerial
|
||||||
docker logs -f nv-cubb
|
docker logs -f nv-cubb
|
||||||
```
|
```
|
||||||
|
|
||||||
#### Running with multiple L2s
|
#### Running with multiple L2s
|
||||||
One L1 instance can support multiple L2 instances. See also the [aerial documentation](https://developer.nvidia.com/docs/gputelecom/aerial-sdk/text/cubb_quickstart/running_cubb-end-to-end.html#run-multiple-l2-instances-with-single-l1-instance) for more details.
|
|
||||||
|
One L1 instance can support multiple L2 instances. See also
|
||||||
|
the [aerial
|
||||||
|
documentation](https://docs.nvidia.com/aerial/cuda-accelerated-ran/latest/quickstart_guide/running_cubb-end-to-end.html#run-multiple-l2-instances-with-single-l1-instance)
|
||||||
|
for more details.
|
||||||
|
|
||||||
In OAI the shared memory prefix must be configured in the configuration file.
|
In OAI the shared memory prefix must be configured in the configuration file.
|
||||||
|
|
||||||
@@ -274,11 +359,12 @@ In OAI the shared memory prefix must be configured in the configuration file.
|
|||||||
```
|
```
|
||||||
|
|
||||||
|
|
||||||
### Stopping the setup
|
#### Stopping the setup
|
||||||
|
|
||||||
|
Run the following command to stop and remove both containers, leaving the
|
||||||
|
system ready to be restarted later:
|
||||||
|
|
||||||
Run the following command to stop and remove both containers, leaving the system ready to be restarted later:
|
|
||||||
```bash
|
```bash
|
||||||
cd ci-scripts/yaml_files/sa_gnb_aerial/
|
cd ci-scripts/yaml_files/sa_gnb_aerial/
|
||||||
docker compose down
|
docker compose down
|
||||||
|
|
||||||
```
|
```
|
||||||
|
|||||||
Reference in New Issue
Block a user