- This PR will leverage subtests on the existing table tests for the scheduler units. ([#63665](https://github.com/kubernetes/kubernetes/pull/63665), [@xchapter7x](https://github.com/xchapter7x))

			// Experiments (using IndexPeriodic) suggest
			// the cutover is about 16 byte skips.
			// TODO: if large prefixes of sep are matching
			// we should cutover at even larger average skips,
			// because Equal becomes that much more expensive.
			// This code does not take that effect into account.
			j := bytealg.IndexRabinKarp(s[i:], sep)
			if j < 0 {
				return -1
			}

     * traverse. When nodes would otherwise be changed, new nodes are created to replace them. This
     * works well for hash tables since the bin lists tend to be short. (The average length is less
     * than two.)
     *
     * Read operations can thus proceed without locking, but rely on selected uses of volatiles to

    /** The key of the message: Request Average Time/Hour */
    public static final String LABELS_searchlog_log_type_search_reqtimeavg_hour = "{labels.searchlog_log_type_search_reqtimeavg_hour}";

    /** The key of the message: Request Average Time/Day */

     * traverse. When nodes would otherwise be changed, new nodes are created to replace them. This
     * works well for hash tables since the bin lists tend to be short. (The average length is less
     * than two.)
     *
     * Read operations can thus proceed without locking, but rely on selected uses of volatiles to

- Scheduler volumebinding: leverage PreFilterResult to reduce down to only eligible node(s) for pod with bound claim(s) to local PersistentVolume(s) ([#109877](https://github.com/kubernetes/kubernetes/pull/109877), [@yibozhuang](https://github.com/yibozhuang)) [SIG Scheduling, Storage...

     * traverse. When nodes would otherwise be changed, new nodes are created to replace them. This
     * works well for hash tables since the bin lists tend to be short. (The average length is less
     * than two.)
     *
     * Read operations can thus proceed without locking, but rely on selected uses of volatiles to

            and newer CPUs.)
            *   [Example performance speedups.](https://medium.com/intel-analytics-software/leverage-intel-deep-learning-optimizations-in-tensorflow-129faa80ee07)
        *   For older CPUs, oneDNN optimizations are disabled by default.
    *   **Windows x86 package:** oneDNN optimizations are disabled by default.

     * traverse. When nodes would otherwise be changed, new nodes are created to replace them. This
     * works well for hash tables since the bin lists tend to be short. (The average length is less
     * than two.)
     *
     * Read operations can thus proceed without locking, but rely on selected uses of volatiles to

- The kubeconfig is now exposed in `the kube-scheduler` framework handle. Out-of-tree plugins can leverage that to build CRD informers easily. ([#100644](https://github.com/kubernetes/kubernetes/pull/100644), [@Huang-Wei](https://github.com/Huang-Wei))