synchronized (sid_cache) {
            try {
                handle = DcerpcHandle.getHandle("ncacn_np:" + server + "[\\PIPE\\lsarpc]", auth);
                // NetApp doesn't like the 'generic' access mask values
                policyHandle = new LsaPolicyHandle(handle, null, 0x00000001);
                rpc = new MsrpcQueryInformationPolicy(policyHandle, (short) lsarpc.POLICY_INFO_ACCOUNT_DOMAIN, info);

        assertEquals("https://contrib.org", pom.getValue("contributors[1]/organizationUrl"));
        assertEquals("+1", pom.getValue("contributors[1]/timezone"));
        assertEquals("yes", pom.getValue("contributors[1]/properties/contributor"));
        assertEquals(1, ((List<?>) pom.getValue("contributors[1]/roles")).size());
        assertEquals("contrib", pom.getValue("contributors[1]/roles[1]"));

	}

	return prof, nil
}

// minioProfiler - minio profiler interface.
type minioProfiler interface {
	// Return recorded profiles, each profile associated with a distinct generic name.
	Records() map[string][]byte
	// Stop the profiler
	Stop() ([]byte, error)
	// Return extension of profile
	Extension() string
}

// Global profiler to be used by service go-routine.
var (

     * list of hosts found in "Network Neighborhood".
     */

    public static final String MASTER_BROWSER_NAME = "\u0001\u0002__MSBROWSE__\u0002";

    /**
     * A special generic name specified when connecting to a host for which
     * a name is not known. Not all servers respond to this name.
     */

    public static final String SMBSERVER_NAME = "*SMBSERVER     ";

    /**

- Some are corrupt (missing format.json)
- Any unrecognized disks - return failure

No read quorum
-----------------
failure for all cases.

// Pseudo code for managing `format.json`.

// Generic checks.
if (no quorum) return error
if (any disk is corrupt) return error // Always error
if (jbod inconsistent) return error // Always error.
if (disks not recognized) // Always error.

// Specific checks.

    * The body size limit does not apply to subresources like pods/proxy that proxy request content to another server.
* The apiserver, including both the kube-apiserver and apiservers built with the generic apiserver library, will now return 413 RequestEntityTooLarge error if a json patch contains more than 10,000 operations. ([#74000](https://github.com/kubernetes/kubernetes/pull/74000), [@caesarxuchao](https://github.com/caesarxuchao))

* AWS: Recognize ca-central-1 region ([#38410](https://github.com/kubernetes/kubernetes/pull/38410), [@justinsb](https://github.com/justinsb))
* Add TLS conf for Go1.7 ([#38600](https://github.com/kubernetes/kubernetes/pull/38600), [@k82cn](https://github.com/k82cn))

And as most of the execution time is taken by actual work (instead of waiting), and the work in a computer is done by a <abbr title="Central Processing Unit">CPU</abbr>, they call these problems "CPU bound".

---

Common examples of CPU bound operations are things that require complex math processing.

For example:

  <mime-type type="application/x-font-adobe-metric">
    <_comment>Adobe Font Metric</_comment>
    <glob pattern="*.afm"/>
    <glob pattern="*.acfm"/>
    <glob pattern="*.amfm"/>
    <magic priority="40">
      <match value="StartFontMetrics" type="string" offset="0"/>
    </magic>
  </mime-type>

  <mime-type type="application/x-font-printer-metric">
    <_comment>Printer Font Metric</_comment>

無論輪流執行與否（並行），你都需要相同的工時完成任務，同時需要執行相同工作量。

但是，在這種情境下，如果你可以邀請8位前收銀員/廚師（現在是清潔工）來幫忙，每個人（加上你）負責房子的某個區域，這樣你就可以 **平行** 地更快完成工作。

在這個場景中，每個清潔工（包括你）都是一個處理器，完成工作的一部分。

由於大多數的執行時間都花在實際的工作上（而不是等待），而電腦中的工作由 <abbr title="Central Processing Unit">CPU</abbr> 完成，因此這些問題被稱為「CPU 密集型」。

---

常見的 CPU 密集型操作範例包括那些需要進行複雜數學計算的任務。

例如：

* **音訊**或**圖像處理**；
* **電腦視覺**：一張圖片由數百萬個像素組成，每個像素有 3 個值/顏色，處理這些像素通常需要同時進行大量計算；