I am running a code on gpu. The code is:

```
import pennylane as qml
wires=4
dev4 = qml.device("lightning.gpu", wires=wires) # define the simulator
@qml.qnode(dev4)
def CONVCircuit(phi, wires, i=0):
"""
quantum convolution Node
"""
# parameter
theta = np.pi / 2
qml.RX(phi[0] * np.pi, wires=0)
qml.RX(phi[1] * np.pi, wires=1)
qml.RX(phi[2] * np.pi, wires=2)
qml.RX(phi[3] * np.pi, wires=3)
qml.CRZ(theta, wires=[1, 0])
qml.CRZ(theta, wires=[3, 2])
qml.CRX(theta, wires=[1, 0])
qml.CRX(theta, wires=[3, 2])
qml.CRZ(theta, wires=[2, 0])
qml.CRX(theta, wires=[2, 0])
# Expectation value
measurement = qml.expval(qml.PauliZ(wires=0))
return measurement
def QCONV1(X, image_number, image_total, step=2):
"""
quantum convolutional layer
"""
#H, W, CH = X.shape
H, W = X.shape
step2 = 2
out = np.zeros(((H//step), (W//step)))
#progress = 0
for i in range(0, W, step):
#print("processing image "+str(image_number)+"/ "+str(image_total)+": "+str(int(((i/W+1))*100))+"% ", end="\r")
print("processing image "+str(image_number)+"/ "+str(image_total)+": "+str(i)+"px ", end="\r")
for j in range(0, H, step):
# get 2x2 pixels and make them 1D array
phi = X[i:i+2, j:j+2].flatten()
# Get Measurement
measurement = CONVCircuit(phi, len(phi))
out[i//step, j//step] = measurement
return out
```

I am getting the error:

```
Error in PennyLane Lightning: the provided PTX was compiled with an unsupported toolchain.
```

I am executing the code on the NVIDIA DGX-1 server, which has 512 GB RAM, 7TB SSD, 40 CPU cores and 8 of V100(Volta) GPUs running the Ubuntu 18.04 operating system.