dneuraln · August 27, 2016 01:36 · Sep 4, 2013
diff --git a/gputest.lua b/gputest.lua
@@ -0,0 +1,90 @@
+-- Max Jaderberg 4/9/13
+-- GPU Effectiveness test
+
+require 'torch'
+require 'sys'
+require 'nn'
+require 'xlua'
+
+cmd = torch.CmdLine()
+cmd:text()
+cmd:text('GPU Benchmark. Max Jaderberg.')
+cmd:text()
+cmd:text('Options:')
+cmd:option('-size', 24, 'size of images')
+cmd:option('-N', 1000, 'number of images')
+cmd:option('-threads', 2, 'number of threads')
+cmd:text()
+opt = cmd:parse(arg or {})
+
+torch.setnumthreads(opt.threads)
+
+torch.setdefaulttensortype("torch.FloatTensor")
+
+-- Input size
+sz = opt.size
+finalsize = (sz - 4)/2 --for a 5x5 filter
+Ntest = opt.N
+
+-- Test input
+x = torch.rand(Ntest, 3, sz, sz)
+
+-- Simple network
+model = nn.Sequential()
+model:add(nn.SpatialConvolution(3, 64, 5, 5))
+model:add(nn.Tanh())
+model:add(nn.SpatialLPPooling(64, 2, 2, 2, 2, 2))
+model:add(nn.Reshape(64*finalsize*finalsize))
+model:add(nn.Linear(64*finalsize*finalsize, 128))
+model:add(nn.Tanh())
+model:add(nn.Linear(128, 2))
+model:add(nn.Tanh())
+criterion = nn.MSECriterion()
+
+-- Test ouput
+y = torch.rand(Ntest, 2)
+
+
+-- Test routine
+local runtest = function() 
+  print('==> Type is '..x:type())
+
+	for i = 1,x:size(1) do
+		xlua.progress(i, x:size(1))
+
+		local yp = model:forward(x[i])
+		local err = criterion:forward(yp, y[i])
+		local df_do = criterion:backward(yp, y[i])
+		model:backward(x[i], df_do)
+	end
+end
+
+
+-- CPU TEST
+cputime0 = sys.clock()
+runtest()
+cputime1 = sys.clock()
+cputime = cputime1 - cputime0
+print('CPU Time: '.. (cputime*1000) .. 'ms')
+
+-- GPU TEST
+require 'cunn'
+x = x:cuda()
+y = y:cuda()
+model:cuda()
+criterion:cuda()
+
+gputime0 = sys.clock()
+runtest()
+gputime1 = sys.clock()
+gputime = gputime1 - gputime0
+print('GPU Time: '.. (gputime*1000) .. 'ms')
+
+print('------------------')
+print('GPU speedup: '..cputime/gputime..'x')
+
+
+
+
+
+