我只是在Google Compute Engine上设置了一个GPU实例，并按照Tensorflow主页上的说明设置了GPU的内容。
虽然我认为我已经正确完成了设置（例如安装驱动程序等以使GPU可供系统使用），但我还是觉得有些不足。
如果我启动一个使用简单MLP进行测试的小型Tensforflow Python脚本，就会发生这种情况。
这是Python代码（仅感兴趣的方法）：
def fit_model_with_nodes(self, nodes_count, X_train, Y_train, X_test, Y_test, epochs=1000, batch_size=16):
device_spec = DeviceSpec.from_string("/device:GPU:0")
with tensorflow.device(device_spec.to_string()):
model = Sequential()
model.add(Dense(nodes_count, input_dim=1, activation="relu")) #, kernel_regularizer=l2(0.001)))
model.add(Dense(1))
model.compile(optimizer="adam", loss="mean_squared_error", metrics=["mean_squared_error"])
history = model.fit(X_train, Y_train, epochs=epochs, batch_size=batch_size, validation_data=(X_test, Y_test), verbose=0)
_, mse_train = model.evaluate(X_train,Y_train, verbose=0)
_, mse_test = model.evaluate(X_test,Y_test, verbose=0)
return mse_train, mse_test, history
这是相应的输出：
python Runme.py
List of devices that can be used:
2020-05-29 11:25:29.741474: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-05-29 11:25:29.748052: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 2200000000 Hz
2020-05-29 11:25:29.748221: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fac64000b20 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-05-29 11:25:29.748271: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2020-05-29 11:25:29.750619: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2020-05-29 11:25:29.977770: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.978410: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55901c0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-05-29 11:25:29.978508: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Tesla P4, Compute Capability 6.1
2020-05-29 11:25:29.978755: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.979226: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:00:04.0 name: Tesla P4 computeCapability: 6.1
coreClock: 1.1135GHz coreCount: 20 deviceMemorySize: 7.43GiB deviceMemoryBandwidth: 178.99GiB/s
2020-05-29 11:25:29.979607: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2020-05-29 11:25:29.981465: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2020-05-29 11:25:29.983258: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2020-05-29 11:25:29.983650: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2020-05-29 11:25:29.985508: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2020-05-29 11:25:29.986609: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2020-05-29 11:25:29.990324: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-05-29 11:25:29.990513: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.990972: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.991374: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2020-05-29 11:25:29.991453: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2020-05-29 11:25:29.992513: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-05-29 11:25:29.992576: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0
2020-05-29 11:25:29.992614: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N
2020-05-29 11:25:29.992768: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.993266: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.993711: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/device:GPU:0 with 7048 MB memory) -> physical GPU (device: 0, name: Tesla P4, pci bus id: 0000:00:04.0, compute capability: 6.1)
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 8408828767664220178
, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit: 17179869184
locality {
}
incarnation: 18378745627352907163
physical_device_desc: "device: XLA_CPU device"
, name: "/device:XLA_GPU:0"
device_type: "XLA_GPU"
memory_limit: 17179869184
locality {
}
incarnation: 8817804582458048379
physical_device_desc: "device: XLA_GPU device"
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 7390920704
locality {
bus_id: 1
links {
}
}
incarnation: 10457343079077620732
physical_device_desc: "device: 0, name: Tesla P4, pci bus id: 0000:00:04.0, compute capability: 6.1"
]
Train Model with nodes_count = 768
1 /10
2020-05-29 11:25:29.995693: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.996097: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:00:04.0 name: Tesla P4 computeCapability: 6.1
coreClock: 1.1135GHz coreCount: 20 deviceMemorySize: 7.43GiB deviceMemoryBandwidth: 178.99GiB/s
2020-05-29 11:25:29.996213: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2020-05-29 11:25:29.996254: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2020-05-29 11:25:29.996292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2020-05-29 11:25:29.996330: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2020-05-29 11:25:29.996369: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2020-05-29 11:25:29.996407: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2020-05-29 11:25:29.996445: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-05-29 11:25:29.996522: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.996934: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.997307: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2020-05-29 11:25:29.997783: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.998240: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:00:04.0 name: Tesla P4 computeCapability: 6.1
coreClock: 1.1135GHz coreCount: 20 deviceMemorySize: 7.43GiB deviceMemoryBandwidth: 178.99GiB/s
2020-05-29 11:25:29.998411: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2020-05-29 11:25:29.998488: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2020-05-29 11:25:29.998541: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2020-05-29 11:25:29.998589: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2020-05-29 11:25:29.998643: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2020-05-29 11:25:29.998692: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2020-05-29 11:25:29.998738: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-05-29 11:25:29.998856: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.999324: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:29.999720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2020-05-29 11:25:29.999775: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-05-29 11:25:29.999811: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0
2020-05-29 11:25:29.999845: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N
2020-05-29 11:25:29.999949: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:30.000386: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-29 11:25:30.000811: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7048 MB memory) -> physical GPU (device: 0, name: Tesla P4, pci bus id: 0000:00:04.0, compute capability: 6.1)
2020-05-29 11:25:31.037793: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
我在理解Tensorflow的日志输出方面没有任何特别的经验，但在我看来，TF似乎已经正确识别了所有内容，并且还在使用GPU。
但是，在我的本地计算机上（2015年的旧版Macbook pro和icore 5）的速度是GPU实例的两倍。
有什么我忘记的东西还是我的设置不正确？