Specifying gpuArray input for codegen
Hi, I am trying to accelerate some simulation code I have using my GPU. I am trying to do this by first creating a bunch of gpuArrays to hold the relevant variables and then passing these arrays to a function (updateNet) which I want to turn into a mex file using GPU Coder. For different simulations, the gpuArrays will be different sizes but for a particular simulation they will all be the same size. Since GPU Coder does not support variable sized gpuArray inputs I have written a function that takes as input an integer and then specifies that as the size of all of the gpuArray inputs for this call to 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.
Kshitij Singh answered .
2025-11-20
gpucoder -script yourscript.m -tocode yourgpucoderproject.prj
coder.typeof(single(0), [N 1], 'Gpu', true)