diff --git a/examples/dsp.py b/examples/dsp.py
index 0f22121..e620798 100644
--- a/examples/dsp.py
+++ b/examples/dsp.py
@@ -16,7 +16,7 @@
 # this folder will contain a Kerkythea model named `model.xml`
 # and the `material_a.dat`, `material_b.dat` files pertaining
 # to the materials referenced in it.
-anc = AncField('gpu', 'models/dsp')
+anc = AncField('cpu', 'models/dsp')
 
 # Place a microphone at position x=3, y=1, z=1 in meters.
 # The acoustic pressure at this point will be recorder, and
diff --git a/examples/ie224.py b/examples/ie224.py
index 0f18984..38f830b 100644
--- a/examples/ie224.py
+++ b/examples/ie224.py
@@ -36,15 +36,14 @@ def add_microphones(ancObject):
     return ancObject
 
 # We create a simulation and immeatealy add microphones to it
-anc = add_microphones(AncField('cpu', 'models/ie224'))
-    
+#
+# Trying to run this simulation on CPU failed on an i7-3770, compiling the
+# lrs_1.cl file fails. It maybe because the scene's size is too large for
+# the CPU. Compiling it for the built in integrated GPU worked though.
+anc = add_microphones(AncField('gpu', 'models/ie224'))
+
 # noise_source
 anc.AddSource([4,1.6,1.0], bandnoise([100,2000], 11*32000, 32000))
 
 anc.Visualize(1.6)
 (x,y) = anc.Run(10)
-
-#h = EstimateIr(x[0,:], y, anc.fs)
-#np.savetxt('h_'+sim+'.dat', h)
-#h = EstimateIr(x[0::4], y[6,0::4], 3*8e3, 1e-4)
-#savetxt('noise_to_reference_bottom.dat', h)
\ No newline at end of file
diff --git a/examples/room_modes.py b/examples/room_modes.py
index c0480ce..4d861d5 100644
--- a/examples/room_modes.py
+++ b/examples/room_modes.py
@@ -11,7 +11,7 @@
 from anc_field_py.ancfield import *
 from anc_field_py.ancutil import *
 
-anc = AncField('cpu', 'models/room_modes')
+anc = AncField('gpu', 'models/room_modes')
 
 anc.AddSource([0.48,0.48,0.48], 10*impulse(2000, 6*32000, 32000))
 anc.AddMic([0.5,0.2,0.3])
diff --git a/impulse-anc-py/ancutil.py b/impulse-anc-py/ancutil.py
deleted file mode 100644
index d1da801..0000000
--- a/impulse-anc-py/ancutil.py
+++ /dev/null
@@ -1,64 +0,0 @@
-from __future__ import division
-
-import numpy as np
-from scipy import signal
-
-def EstimateIr(input, output, N, mu):
-	W = np.zeros(N)	
-
-	for m in range(0,16):
-		steps = min(np.size(input, 0), np.size(output, 0))
-	#	mu = 1e-4
-	
-		x_buf = np.zeros(N)
-	
-		for k in range(0, steps):
-			x_buf = np.concatenate( (np.array([input[k]]), x_buf[0:-1]) )
-			y_est = np.dot(W, x_buf)
-			e = output[k] - y_est
-			W = W + 2*mu*e*x_buf
-
-	return W
-
-def bandnoise(bands, length, fs):
-	z = 2*np.random.rand(length)-1;
-	if len(bands) > 1 and bands[0] != 0:
-		b = signal.firwin(10000, [c/(fs/2) for c in bands], pass_zero=False)	
-	elif len(bands) > 1:
-		b = GetLpFir(bands[1], 100, fs)
-	x = signal.lfilter(b, 1, z);
-
-	return x
-	
-def impulse(bw, length, fs):
-	x = np.zeros(length)
-	x[1] = 1
-	b = GetLpFir(bw, 100, fs)
-	x = signal.lfilter(b, 1, x)
-	
-	return x
-
-def GetLpFir(cutoff, transition, fs):	
-	#------------------------------------------------
-	# Create a FIR filter and apply it to x.
-	#------------------------------------------------
-	
-	# The Nyquist rate of the signal.
-	nyq_rate = fs / 2.0
-	
-	# The desired width of the transition from pass to stop,
-	# relative to the Nyquist rate.  We'll design the filter
-	# with a 5 Hz transition width.
-	width = transition/nyq_rate
-	
-	# The desired attenuation in the stop band, in dB.
-	ripple_db = 80.0
-	
-	# Compute the order and Kaiser parameter for the FIR filter.
-	N, beta = signal.kaiserord(ripple_db, width)
-	
-	# Use firwin with a Kaiser window to create a lowpass FIR filter.
-	taps = signal.firwin(N, cutoff/nyq_rate, window=('kaiser', beta))
-	
-	return taps
-	
\ No newline at end of file