Why `gpucoder.profile` example failed?

I am trying to profile the gpu code. At first, I tried the example in gpucoder.profile. But it always gives an error with something of SIL ServerPort as below. My gpu device is NVIDIA GeForce RTX 2060 SUPER. The host system is windows10 64bits. My Matlab version is 2021a. What's wrong with my gpu device? Could anyone give me some suggestions?

At first, build a gpu_fftn function file in the current directory.

function [Y] = gpu_fftn(X)
  coder.gpu.kernelfun();
  Y = fftn(X);
end

Then ran the commands below in Matlab prompts window.

cfg = coder.gpuConfig('exe');
cfg.GpuConfig.MallocMode = 'discrete';
gpucoder.profile('gpu_fftn',{rand(2,4500,4)},'CodegenConfig',cfg, ...
'CodegenArguments','-d profilingdir','Threshold',0.001);

The error came in several minutes.

### Starting SIL execution for 'gpu_fftn'
    To terminate execution: clear gpu_fftn_sil
UnknownServerPort_Diagnostics - 0
UnknownServerPort_Diagnostics - 1
UnknownServerPort_Diagnostics - 2
Error using gpucoder.profile (line 41)
Could not parse server port number from application output:
 To manually test launching the executable run the command line:
 C:\Users\psylab706\Documents\MATLAB\ZW\GPU\coder\profilingdir\sil\gpu_fftn.exe -port 0
 -blocking 1.
 

gpuDevice

 >> gpuDevice

ans = 

  CUDADevice with properties:

                      Name: 'GeForce RTX 2060 SUPER'
                     Index: 1
         ComputeCapability: '7.5'
            SupportsDouble: 1
             DriverVersion: 11.3000
            ToolkitVersion: 11
        MaxThreadsPerBlock: 1024
          MaxShmemPerBlock: 49152
        MaxThreadBlockSize: [1024 1024 64]
               MaxGridSize: [2.1475e+09 65535 65535]
                 SIMDWidth: 32
               TotalMemory: 8.5899e+09
           AvailableMemory: 7.3862e+09
       MultiprocessorCount: 34
              ClockRateKHz: 1650000
               ComputeMode: 'Default'
      GPUOverlapsTransfers: 1
    KernelExecutionTimeout: 1
          CanMapHostMemory: 1
           DeviceSupported: 1
            DeviceSelected: 1

checkGpuInstall

gpuEnvObj = coder.gpuEnvConfig;
gpuEnvObj.GpuId = 0; % the device number is 0, no other device
gpuEnvObj.BasicCodegen = 1;
gpuEnvObj.BasicCodeexec = 1;
results = coder.checkGpuInstall(gpuEnvObj);

result of checkGpuInstall:

Compatible GPU           : PASSED 
CUDA Environment         : PASSED 
	Runtime   : PASSED 
	cuFFT     : PASSED 
	cuSOLVER  : PASSED 
	cuBLAS    : PASSED 
Basic Code Generation    : PASSED 
Basic Code Execution     : PASSED 

results = 

  struct with fields:

                 gpu: 1
                cuda: 1
               cudnn: 0
            tensorrt: 0
        basiccodegen: 1
       basiccodeexec: 1
         deepcodegen: 0
        deepcodeexec: 0
    tensorrtdatatype: 0
           profiling: 0

To enable GPU performance counters to be used by all users, I had set the options as Nvidia link.

My had update my nvidia driver to latest version.

Answer 1

[wei zhang]

I should thank Matlab team first, especially Hu Halley and Erik. It is all about cupti library including as below.

setenv('PATH', [getenv('PATH') ';cudapath\extras\CUPTI\lib64']);

[wei zhang]

For details, read this Link