Generating TV and Launch Pattern Files#

Since the cuBB 22-2.2 release, the test vectors are not included in the release package. You must generate the TV files before running cuPHY examples or cuBB end-to-end test.

Note

TV generation is NOT supported on ARM because Matlab Compiler SDK doesn’t support it yet.

Using Aerial Python mcore Module#

No Matlab license is required to generate TV files using the Aerial Python mcore module. The cuBB container already has aerial_mcore installed.

To generate the test vectors required for end-to-end testing, follow these steps:

  1. Run the following inside the Aerial container. It completes in less than a minute.

    cd ${cuBB_SDK}/5GModel/aerial_mcore/examples
source ../scripts/setup.sh
../scripts/gen_e2e_ota_tvs.sh
ls -lh GPU_test_input/
cp GPU_test_input/* ${cuBB_SDK}/testVectors/

    The following is example output from the above commands:

    aerial@c_aerial_aerial:/opt/nvidia/cuBB/5GModel/aerial_mcore$ source ./scripts/setup.sh
[Aerial Python]aerial@c_aerial_aerial:/opt/nvidia/cuBB/5GModel/aerial_mcore$ ./scripts/gen_e2e_ota_tvs.sh
Finished genCuPhyChEstCoeffs
Elapsed time: 1.166473150253296 seconds
[Aerial Python]aerial@c_aerial_aerial:/opt/nvidia/cuBB/5GModel/aerial_mcore$ ls -lh ../GPU_test_input/
-rw-rw-r-- 1 aerial aerial 90K Oct 17  2023 ../cuPhyChEstCoeffs.h5

    Note

    The cuPhyChEstCoeffs.h5 file can be found in the /opt/nvidia/cuBB/testVectors directory of both the x86 and ARM containers.

  2. Copy the output to the testVectors folder.

To generate all of the TV files, including files that are not necessary for E2E testing, follow these steps:

  1. Run the following commands inside the Aerial container.

    cd ${cuBB_SDK}/5GModel/aerial_mcore/examples
source ../scripts/setup.sh
export REGRESSION_MODE=1
time python3 ./example_5GModel_regression.py allChannels
echo $?
ls -alF GPU_test_input/
du -h GPU_test_input/

    Note

    The TV generation may take a few hours on the devkit with the current isocpus parameter setting in the kernel command line. The host must have at least 64GB of memory and 430GB of available disk space. Hyperthreading must be enabled.

  2. Review the output from the above commands; an example is shown below. The “real” time takes less than one hour on a 24-core x86 host. The echo $? command shows the exit code of the process, which should be 0, while a non-zero exit code indicates a failure.

    Channel  Compliance_Test  Error   Test_Vector  Error  Performance_Test   Fail
------------------------------------------------------------------------------
SSB           37            0         42          0           0            0
PDCCH         71            0         80          0           0            0
PDSCH        274            0        286          0           0            0
CSIRS         86            0         87          0           0            0
DLMIX          0            0        1049         0           0            0
PRACH         60            0         60          0          48            0
PUCCH        469            0        469          0          96            0
PUSCH        388            0        398          0          41            0
SRS          125            0        125          0           0            0
ULMIX          0            0        576          0           0            0
BFW           58            0         58          0           0            0
------------------------------------------------------------------------------
Total       1568            0       3230          0         185            0

Total time for runRegression is 2147 seconds
Parallel pool using the 'local' profile is shutting down.

real    36m51.931s
user    585m1.704s
sys     10m28.322s

To generate the launch pattern for each test case using cubb_scripts, follow these steps:

  1. Run the following commands:

    cd $cuBB_SDK
cd cubb_scripts
python3 auto_lp.py -i ../5GModel/aerial_mcore/examples/GPU_test_input -t launch_pattern_nrSim.yaml

  2. Copy the launch pattern and TV files to the testVectors repo:

    cd $cuBB_SDK
cp ./5GModel/aerial_mcore/examples/GPU_test_input/*h5 ./testVectors/.
cp ./5GModel/aerial_mcore/examples/GPU_test_input/launch_pattern* ./testVectors/multi-cell/.`

Using Matlab#

To generate TV files using Matlab:

  1. Run the following command in Matlab:

    cd('nr_matlab'); startup; [nTC, errCnt] = runRegression({'TestVector'}, {'allChannels'}, 'compact', [0, 1] );

    All the cuPHY TVs are generated and stored under nr_matlab/GPU_test_input.

  2. Generate the launch pattern for each test case using cubb_scripts:

    cd $cuBB_SDK
cd cubb_scripts
python3 auto_lp.py -i ../5GModel/nr_matlab/GPU_test_input -t launch_pattern_nrSim.yaml

  3. Copy the launch pattern and TV files to testVectors repo.

cd $cuBB_SDK
cp ./5GModel/nr_matlab/GPU_test_input/TVnr_* ./testVectors/.
cp ./5GModel/nr_matlab/GPU_test_input/launch_pattern* ./testVectors/multi-cell/.
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