<abbr title="Central Processing Unit">CPU</abbr>
        <abbr title="too long; didn't read"><strong>TL;DR:</strong></abbr>
        »»»

    Result (German):

        «««
        <abbr title="Internet of Things – Internet der Dinge">IoT</abbr>
        <abbr title="Central Processing Unit – Zentrale Verarbeitungseinheit">CPU</abbr>

TF_CAPI_EXPORT void TF_SetXlaMinClusterSize(int size);

// Gets/Sets TF/XLA flag for whether(true) or not(false) to disable constant
// folding. This is for testing to ensure that XLA is being tested rather than
// Tensorflow's CPU implementation through constant folding.
TF_CAPI_EXPORT unsigned char TF_GetXlaConstantFoldingDisabled();
TF_CAPI_EXPORT void TF_SetXlaConstantFoldingDisabled(
    unsigned char should_enable);

 * Generally speaking, this class reduces object allocation and memory consumption at the price of
 * moderately increased constant factors of CPU. Only use this class when there is a specific reason
 * to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 * @author Jon Noack
 */
@GwtIncompatible // not worth using in GWT for now

    // we try hard to make them robust in practice.  We could additionally try to add in a system
    // load timeout multiplier.  Or we could try to use a CPU time bound instead of wall clock time
    // bound.  But these ideas are harder to implement.  We do not try to detect or handle a
    // user-specified -XX:+DisableExplicitGC.
    //
    // TODO(user): Consider using

    // we try hard to make them robust in practice.  We could additionally try to add in a system
    // load timeout multiplier.  Or we could try to use a CPU time bound instead of wall clock time
    // bound.  But these ideas are harder to implement.  We do not try to detect or handle a
    // user-specified -XX:+DisableExplicitGC.
    //
    // TODO(user): Consider using

* el header `Authorization`
* el header Forwarded

* el sistema de inyección de dependencias
* la dependencia
* el dependable
* el dependiente

* limitado por I/O
* limitado por CPU
* concurrencia
* paralelismo
* multiprocesamiento

* la variable de entorno
* la variable de entorno
* el `PATH`
* la variable `PATH`

* la autenticación
* el proveedor de autenticación

* the headers
* the authorization header
* the `Authorization` header
* the forwarded header

* the dependency injection system
* the dependency
* the dependable
* the dependant

* I/O bound
* CPU bound
* concurrency
* parallelism
* multiprocessing

* the env var
* the environment variable
* the `PATH`
* the `PATH` variable

* the authentication
* the authentication provider

このシナリオでは、清掃員 (あなたを含む) のそれぞれがプロセッサとなり、それぞれの役割を果たします。

また、実行時間のほとんどは (待機ではなく) 実際の作業に費やされ、コンピュータでの作業は<abbr title="Central Processing Unit">CPU</abbr>によって行われます。これらの問題は「CPUバウンド」と言います。

---

CPUバウンド操作の一般的な例は、複雑な数学処理が必要なものです。

例えば:

* **オーディオ** や **画像処理**。
* **コンピュータビジョン**: 画像は数百万のピクセルで構成され、各ピクセルには3つの値/色があり、通常、これらのピクセルで何かを同時に計算する必要がある処理。

	g := errgroup.WithNErrs(len(buckets))
	bucketMetas := make([]BucketMetadata, len(buckets))
	for index := range buckets {
		g.Go(func() error {
			// Sleep and stagger to avoid blocked CPU and thundering
			// herd upon start up sequence.
			time.Sleep(25*time.Millisecond + time.Duration(rand.Int63n(int64(100*time.Millisecond))))

Setting `max_sleep` to a *lower* value and setting `max_io` to a *higher* value would make heal go faster.

Each node is responsible of healing its local drives; Each drive will have multiple heal workers which is the quarter of the number of CPU cores of the node or the quarter of the configured nr_requests of the drive (https://www.kernel.org/doc/Documentation/block/queue-sysfs.txt). It is also possible to provide a custom number of workers by using this command: `mc admin config set alias/...