human_afterall

@bwasti, really good points - this is something we look forward to evaluating! Our post does indeed outline optimizations from tensorflow/serving to tensorflow/serving:* -devel [1]. The next logical improvement (given intel architecture and docs linked) is start building on top of the * -devel-mkl image.

-masroor(author)

[1] https://github.com/tensorflow/serving/tree/master/tensorflow...

Hi bwasti, the host's CPU platform is Intel Broadwell. While the CPU architecture of our production hosts are the same, the resources allocated are much higher than 4 cores. This post details an overview of the relative improvements that can be made from a vanilla setup :)

-masroor (author)

Good point - we're still in the process of migrating to >= 1.17. The gRPC connection and client stub should still translate (few semantic updates).

```

channel = grpc.insecure_channel('0.0.0.0:9000')

stub = PredictionServiceStub(channel)

```

-masroor (author)

Hey! That's super interesting - so far we went with Tensorflow's ubuntu based official Docker devel image, but a clearlinux base looks like it would definitely be worth looking into!

-masroor (author)

Hey! Author here, thanks for linking the paper. The article was from an infrastructure perspective, but we're definitely diving deeper into graph execution optimizations after this:)

For a second I thought you meant Q# - got pretty excited there :)

I love the new look UI! Looks awesome as usual from you code connect guys.