* It has an added advantage since you can you easily switch to different hardware accelerators (cpu, gpu, tpu) as per the task.
         * All you need is a good internet connection and you are all set.
      * Try to build TF from sources by changing CPU optimization flags.
   
   *Please let us know if this helps.*

        "//learning/pathways/...",
        "//learning/serving/contrib/tfrt/mlir/canonical_ops/...",
        "//learning/serving/experimental/remote_predict/...",
        "//perftools/accelerators/xprof/convert/...",
        "//perftools/accelerators/xprof/integration_tests/...",
        "//smartass/brain/configure/...",
        "//tensorflow/...",
        "//tensorflow_decision_forests/...",
        "//tensorflow_federated/...",

    - [**Node**](#node-3)
      - [**Pod API**](#pod-api)
      - [**Hardware Accelerators**](#hardware-accelerators)
      - [**Container Runtime**](#container-runtime)
      - [**Kubelet**](#kubelet)
        - [**Other**](#other-5)
    - [**OpenStack**](#openstack-2)
    - [**Scheduling**](#scheduling-2)
      - [**Hardware Accelerators**](#hardware-accelerators-1)
      - [**Other**](#other-6)
    - [**Storage**](#storage-3)

    resource availability for critical system pods.
* **[alpha]** `--experimental-nvidia-gpus` flag is replaced by `Accelerators` alpha
  feature gate along with addition of support for multiple Nvidia GPUs.
  - To use GPUs, pass `Accelerators=true` as part of `--feature-gates` flag.
  - More information [here](https://vishh.github.io/docs/user-guide/gpus/).

    * waiting for the request to be satisfied. It will continually refresh the certificate

  * Create clusters with GPUs in GCE by specifying `type=<gpu-type>,count=<gpu-count>` to NODE_ACCELERATORS environment variable. ([#45130](https://github.com/kubernetes/kubernetes/pull/45130), [@vishh](https://github.com/vishh))

by default.  The PersistentVolume NodeAffinity alpha annotation is deprecated and will be removed in a future release. ([#59391](https://github.com/kubernetes/kubernetes/pull/59391), [@msau42](https://github.com/msau42))

* The alpha Accelerators feature gate is deprecated and will be removed in v1.11. Please use device plugins ([https://github.com/kubernetes/enhancements/issues/368](https://github.com/kubernetes/enhancements/issues/368)) instead. They can be enabled using the DevicePlugins...

implementation bugs that might allow attackers to leave malicious code running
and leak or tamper with applications from other users. Please report
vulnerabilities to the vendor of the affected hardware accelerator.

## Reporting vulnerabilities

### Vulnerabilities in TensorFlow

This document covers different use cases for TensorFlow together with comments

  - [Known Issues](#known-issues)
    - [Summary API in kubelet doesn't have accelerator metrics](#summary-api-in-kubelet-doesnt-have-accelerator-metrics)
  - [Urgent Upgrade Notes](#urgent-upgrade-notes)
    - [(No, really, you MUST read this before you upgrade)](#no-really-you-must-read-this-before-you-upgrade)

        time, which may not be intended.
*   API changes under `tf.experimental.dtensor`:
    *   New API for initialization of CPU/GPU/TPU in dtensor.
        `dtensor.initialize_accelerator_system` and
        `dtensor.shutdown_accelerator_system`.
    *   The following existing API will be removed:
        `dtensor.initialize_multi_client`, `dtensor.initialize_tpu_system`, and
        `dtensor.shutdown_tpu_system`.

// (AWS) Elastic Load Balancing
// Submitted by Luke Wells <******@****.***>
// Reference: 12a3d528-1bac-4433-a359-a395867ffed2
*.elb.amazonaws.com.cn
*.elb.amazonaws.com

// AWS Global Accelerator
// Submitted by Daniel Massaguer <******@****.***>
// Reference: d916759d-a08b-4241-b536-4db887383a6a
awsglobalaccelerator.com

// eero
// Submitted by Yue Kang <******@****.***>