},
                    )
                }.sortedBy { -it.totalTime }
                .filter { onlyNativeSubprojectsForIntelMacs(testCoverage, it.subProject.name) }

        return parallelize(subProjectTestClassTimes, testCoverage) { numberOfBatches ->
            when (testCoverage.os) {
                Os.LINUX -> ParallelizationMethod.TestDistribution

## Deployment Concepts { #deployment-concepts }

Here you saw how to use multiple **workers** to **parallelize** the execution of the application, take advantage of **multiple cores** in the CPU, and be able to serve **more requests**.

L'idée de code **asynchrone** décrite ci-dessus est parfois aussi appelée **"concurrence"**. Ce qui est différent du **"parallélisme"**.

La **concurrence** et le **parallélisme** sont tous deux liés à l'idée de "différentes choses arrivant plus ou moins au même moment".

Mais les détails entre la **concurrence** et le **parallélisme** diffèrent sur de nombreux points.

Pour expliquer la différence, voici une histoire de burgers :

This idea of **asynchronous** code described above is also sometimes called **"concurrency"**. It is different from **"parallelism"**.

**Concurrency** and **parallelism** both relate to "different things happening more or less at the same time".

But the details between *concurrency* and *parallelism* are quite different.

To see the difference, imagine the following story about burgers:

- Failed pods associated with a job with `parallelism = 1` are recreated by the job controller honoring exponential backoff delay again. However, for jobs with `parallelism > 1`, pods might be created without exponential backoff delay. ([#115022](https://github.com/kubernetes/kubernetes/pull/115022), [@nikhita](https://github.com/nikhita)) [SIG Apps]

    /**
     * ProjectBuilder parallelism.
     *
     * @since 4.0.0
     */
    @Config(type = "java.lang.Integer", defaultValue = "cores/2 + 1")
    public static final String MAVEN_MODEL_BUILDER_PARALLELISM = "maven.modelBuilder.parallelism";

    /**
     * User property for enabling/disabling the consumer POM feature.
     *

### Parallele Hamburger

Stellen wir uns jetzt vor, dass es sich hierbei nicht um „nebenläufige Hamburger“, sondern um „parallele Hamburger“ handelt.

Sie gehen los mit Ihrem Schwarm, um paralleles Fast Food zu bekommen.

					updates <- cache.clone()
					return
				}
				cache.replace(v.Name, v.Parent, v.Entry)
				cache.Info.LastUpdate = time.Now()
			}
		}
	}()

	// Restrict parallelism for disk usage scanner
	// upto GOMAXPROCS if GOMAXPROCS is < len(disks)
	maxProcs := runtime.GOMAXPROCS(0)
	if maxProcs < len(disks) {
		disks = disks[:maxProcs]
	}

	// Start one scanner per disk

### Feature

- Parallelize calls to conversion webhooks when watching from etcd to prevent watchcache from lagging and helps clusters with slow conversion webhooks or transformers. 

        transformations deterministic. The option will now apply the same across
        all transformations.
    *   The optimization `parallel_batch` now becomes default if not disabled by
        users, which will parallelize copying of batch elements.
    *   Added the ability for `TensorSliceDataset` to identify and handle inputs
        that are files. This enables creating hermetic SavedModels when using
        datasets created from files.