Why is gpuArray\knnsearch so slow?

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Markus Hillemann
Markus Hillemann 2018-1-10
回答： Hao Zhang 2018-12-13
I want to accelerate my code using the GPU. In my case, using knnsearch with a gpuArray is very slow.
Here is a code-snippet to test:
%%sample data
ptCloud = pcread('teapot.ply');
%%Option 1: CPU
points = ptCloud.Location;
k = 50;
tic
[idxCPU, distCPU] = knnsearch(points, points, 'K', k);
tCPU = toc;
disp(tCPU);
%%Option 2: GPU
pointsOnGPU = gpuArray(ptCloud.Location);
kOnGPU = gpuArray(50);
tic
[idxGPU, distGPU] = knnsearch(pointsOnGPU, pointsOnGPU,'K',kOnGPU);
wait(gpuDevice);
tGPU = toc;
disp(tGPU);
%%Option 3: ptCloud.findNearestNeighbors in a for loop
tic
ind = zeros(k, ptCloud.Count);
dists = zeros(k, ptCloud.Count);
for i=1:ptCloud.Count
[ind(:,i), dists(:,i)] = findNearestNeighbors(ptCloud, ptCloud.Location(i,:), k);
end
tOption3 = toc;
disp(tOption3);
My result:
0.4188
2.9700
5.9763
I use Matlab R2017b on Ubuntu 16.04. CPU: Intel® Core™ i7-6700HQ CPU @ 2.60GHz
gpuDevice:
CUDADevice with properties:
Name: 'Quadro M1000M'
Index: 1
ComputeCapability: '5.0'
SupportsDouble: 1
DriverVersion: 9
ToolkitVersion: 8
MaxThreadsPerBlock: 1024
MaxShmemPerBlock: 49152
MaxThreadBlockSize: [1024 1024 64]
MaxGridSize: [2.1475e+09 65535 65535]
SIMDWidth: 32
TotalMemory: 2.0978e+09
AvailableMemory: 1.5902e+09
MultiprocessorCount: 4
ClockRateKHz: 1071500
ComputeMode: 'Default'
GPUOverlapsTransfers: 1
KernelExecutionTimeout: 1
CanMapHostMemory: 1
DeviceSupported: 1
DeviceSelected: 1
I expected that Option 2 is the fastest. Can anyone explain me why this is not the case? Actually, my point cloud contains much more points and the difference is considerably greater.

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回答（1 个）

Hao Zhang
Hao Zhang 2018-12-13
Hi, the gpu version of knnsearch seems to use brute force method. you can check this by inputing a very large points cloud so that run out of memory,matlab will report error on the pdist2 function which trying to comput all pairwise distances.

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