Why gpu slower than cpu? - matlab

Question

I have gpu
>> d = gpuDevice
d =
CUDADevice with properties:
Name: 'GeForce 800M'
Index: 1
ComputeCapability: '2.1'
SupportsDouble: 1
DriverVersion: 6
ToolkitVersion: 5
MaxThreadsPerBlock: 1024
MaxShmemPerBlock: 49152
MaxThreadBlockSize: [1024 1024 64]
MaxGridSize: [65535 65535 65535]
SIMDWidth: 32
TotalMemory: 2.1475e+09
FreeMemory: 1.9886e+09
MultiprocessorCount: 1
ClockRateKHz: 1475000
ComputeMode: 'Default'
GPUOverlapsTransfers: 1
KernelExecutionTimeout: 1
CanMapHostMemory: 1
DeviceSupported: 1
DeviceSelected: 1`
I try use gpu in neuralnetwork train, but my gpu slower than cpu.
If I try use gpuArray, gpu is faster than cpu, but I haven't speed acceleration in neural network training.
For example
>> a1 = rand(1000); b1 = rand(1000); tic; c1 = a1 * b1; toc;
Elapsed time is 0.044095 seconds.
>> a2 = gpuArray(rand(1000)); b2 = gpuArray(rand(1000)); tic; c2 = a2 * b2; toc;
Elapsed time is 0.000416 seconds.
But in code
net = newff(H, F, Layers, { 'tansig' 'tansig'}, 'traingdx', 'learngdm', 'mse');
net.trainParam.epochs = Epochs;
net.trainParam.show = 500;
net.trainParam.time = 495;
net.trainParam.goal = 2.0000e-11;
net.trainParam.max_fail = 200000;
net.trainParam.min_grad = 1.0000e-050;
net.performParam.regularization = 0.05;
net.divideParam.trainRatio = 1;
net.divideParam.valRatio = 0;
net.divideParam.testRatio = 0;
net.trainParam.showWindow = 0;
net.trainParam.showCommandLine = 0;
if Gpu1 == 1
net = train(net, H, F, 'useGPU', 'yes', 'showResources','yes');
else
net = train(net, H, F, 'showResources','yes');
end;
tic; net = net_example(300, [23, 9], rand(100, 1000), rand(1, 1000), 1); toc;
Computing Resources:
GPU device #1, GeForce 800M
works slower than
tic; net = net_example(300, [23, 9], rand(100, 1000), rand(1, 1000), 0); toc;
Computing Resources:
MEX2