Benjamin_ballintyn asked . 2021-06-01

Specifying gpuArray input for codegen

function [] = compile_easySim(N)
cfg = coder.gpuConfig('mex');
cfg.GpuConfig.CompilerFlags = '--fmad=false';
cfg.GenerateReport = true;

ARGS = cell(23,1);
ARGS{1} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % V (membrane Voltage)
ARGS{2} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % Gref (refractory conductance)
ARGS{3} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % dGref (refractory conductance change on spike)
ARGS{4} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % tau_ref (refractory time_constant)
ARGS{5} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % Vth (spike threshold)
ARGS{6} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % VsynE (excitatory synaptic reversal potential)
ARGS{7} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % VsynI (inhibitory synaptic reversal potential)
ARGS{8} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % GsynE (total excitatory synaptic conductance)
ARGS{9} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % GsynI (total inhibitory synaptic conductance)
ARGS{10} = coder.typeof(gpuArray(single(0)),[N 1], [0 0]); % maxGsynE
ARGS{11} = coder.typeof(gpuArray(single(0)),[N 1], [0 0]); % maxGsynI
ARGS{12} = coder.typeof(gpuArray(single(0)),[N N],[0 0]); % dGsyn (synaptic strength matrix)
ARGS{13} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % tau_synE (excitatory synaptic decay time constant)
ARGS{14} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % tau_synI (inhibitory synaptic decay time constant)
ARGS{15} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % Cm (membrane capacitance)
ARGS{16} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % Gl (leak conductance)
ARGS{17} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % El (leak reversal potential)
ARGS{18} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % Ek
ARGS{19} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % dth
ARGS{20} = coder.typeof(gpuArray(single(0)),[N 1],[0 0]); % Iapp
ARGS{21} = coder.typeof(single(0),[1],[0]); % dt
ARGS{22} = coder.typeof(gpuArray(false),[N 1],[0 0]); % ecells
ARGS{23} = coder.typeof(gpuArray(false),[N 1],[0 0]); % icells
codegen updateNet -args ARGS -nargout 5

However, when I do this I get the following error:

Use of CODER.TYPEOF to represent GPU inputs is supported only with GPU Coder.
Use help codegen for more information on using this command.

This confuses me since I thought I was using GPU Coder. Does GPU Coder only refer to the app GUI where you must manually specify each input?

For reference the output of coder.checkGpuInstall is:

coder.checkGpuInstall
Compatible GPU           : PASSED 
CUDA Environment         : PASSED 
	Runtime   : PASSED 
	cuFFT     : PASSED 
	cuSOLVER  : PASSED 
	cuBLAS    : PASSED 
cuDNN Environment        : FAILED (Unable to find the 'NVIDIA_CUDNN' environment variable. Set 'NVIDIA_CUDNN' to point to the root directory of a NVIDIA cuDNN installation.)
Basic Code Generation    : PASSED 
Basic Code Execution     : PASSED 
ans = 
  struct with fields:

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

The only thing that fails is cuDNN but since I'm not trying to do deep learning this shouldn't cause problems.

gpu coder , gpuarray , simulation , codegen