Created
January 9, 2017 21:46
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soumith benchmarks
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require 'torch' | |
require 'cutorch' | |
local trials = 5 | |
print("----------------------------------------------------------------") | |
print("Soumith's Benchmarks (The times are the sum of", trials, "trials)") | |
print("----------------------------------------------------------------") | |
local tensors = {} | |
for i = 1, 32 do | |
table.insert(tensors, torch.CudaTensor(1, 600):uniform()) | |
end | |
local timer = torch.Timer() | |
for i = 1, trials do | |
local catted = torch.cat(tensors, 1) | |
end | |
cutorch.synchronize() | |
local sum = timer:time().real | |
print("CatArray for 32 1x600 Tensors along dim=1 took", sum / trials, "seconds") | |
local tensors = {} | |
for i = 1, 128 do | |
table.insert(tensors, torch.CudaTensor(1, 32):uniform()) | |
end | |
local timer = torch.Timer() | |
for i = 1, trials do | |
local catted = torch.cat(tensors, 1) | |
end | |
cutorch.synchronize() | |
local sum = timer:time().real | |
print("CatArray for 128 1x32 tensors along dim=1 took", sum / trials, "seconds") | |
local tensors = {} | |
for i = 1, 128 do | |
table.insert(tensors, torch.CudaTensor(1, 1024):uniform()) | |
end | |
local timer = torch.Timer() | |
for i = 1, trials do | |
local catted = torch.cat(tensors, 1) | |
end | |
cutorch.synchronize() | |
local sum = timer:time().real | |
print("CatArray for 128 1x1024 tensors along dim=1 took", sum / trials, "seconds") | |
print('done') |
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