- Moved the CPU Manager static policy option `strict-cpu-reservation` to the GA version. ([#134388](https://github.com/kubernetes/kubernetes/pull/134388), [@psasnal](https://github.com/psasnal))

- Added a kubelet metrics to report informations about the cpu pools managed by cpumanager when the static policy is in use. ([#127506](https://github.com/kubernetes/kubernetes/pull/127506), [@ffromani](https://github.com/ffromani)) [SIG Node and Testing]

- The CPU Manager will now validate the state of the node,  enabling Kubernetes to maintain the CPU topology even if resources change. ([#66718](https://github.com/kubernetes/kubernetes/pull/66718), [@ipuustin](https://github.com/ipuustin))

- Added a new option `strict-cpu-reservation` for CPU Manager static policy. When this option is enabled, CPU cores in `reservedSystemCPUs` will be strictly used for system daemons and interrupt processing no longer available for any workload. ([#130290](https://github.com/kubernetes/kubernetes/pull/130290), [@psasnal...

 * either of these extremes, {@code Striped} allows the user to trade between required concurrency
 * and memory footprint. For example, if a set of tasks are CPU-bound, one could easily create a
 * very compact {@code Striped<Lock>} of {@code availableProcessors() * 4} stripes, instead of
 * possibly thousands of locks which could be created in a {@code Map<K, Lock>} structure.
 *

  //   have observed 12 micros on 64-bit linux systems to wake up a parked thread). So if the
  //   timeout is small we shouldn't park(). This needs to be traded off with the cpu overhead of
  //   spinning, so we use SPIN_THRESHOLD_NANOS which is what AbstractQueuedSynchronizer uses for
  //   similar purposes.
  // * We want to behave reasonably for timeouts of 0

        TF_NewOperation(host_graph_, func_name_, func_node_name_);
    for (auto input : inputs) {
      TF_AddInput(desc, input);
    }
    // Set device to CPU because some ops inside the function might not be
    // available on GPU.
    TF_SetDevice(desc, "/cpu:0");
    *op = TF_FinishOperation(desc, s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
    ASSERT_NE(*op, nullptr);
  }

  FunctionDef fdef() {

     */
    Integer getAdaptiveLoadControlAsInteger();

    /**
     * Get the value for the key 'web.load.control'. <br>
     * The value is, e.g. 100 <br>
     * comment: CPU threshold (%) for web request load control. Returns 429 when CPU &gt;= this value. (100: disabled)
     * @return The value of found property. (NotNull: if not found, exception but basically no way)
     */
    String getWebLoadControl();

    /**

* サブクラス
* 子クラス
* 兄弟クラス
* クラスメソッド

* ヘッダー
* ヘッダー（複数）
* 認可ヘッダー
* `Authorization` ヘッダー
* Forwarded ヘッダー

* 依存性注入システム
* 依存関係
* dependable
* dependant

* I/O バウンド
* CPU バウンド
* 同時実行性
* 並列性
* マルチプロセッシング

* env var
* 環境変数
* `PATH`
* `PATH` 環境変数

* 認証
* 認証プロバイダ
* 認可
* 認可フォーム
* 認可プロバイダ
* ユーザーが認証する
* システムがユーザーを認証する

* CLI

  * 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))

    * List of available GPUs - [https://cloud.google.com/compute/docs/gpus/#introduction](https://cloud.google.com/compute/docs/gpus/#introduction)