// time that should be spent in the fractional mark worker on
	// each P that isn't running a dedicated worker.
	//
	// For example, if the utilization goal is 25% and there are
	// no dedicated workers, this will be 0.25. If the goal is
	// 25%, there is one dedicated worker, and GOMAXPROCS is 5,
	// this will be 0.05 to make up the missing 5%.
	//
	// If this is zero, no fractional workers are needed.
	fractionalUtilizationGoal float64

  // Create two worker tasks, using single host server defs.
  // A single host server def contains a client and the remote host.
  // Example:
  //
  //  Worker1:
  //  cluster { job { name: "client" tasks { key: 0 value: "localhost:14525" } }
  //            job { name: "worker" tasks { key: 1 value: "localhost:14523" } }
  //          } job_name: "worker" task_index: 1 protocol: "grpc"
  //

	// and there are no more workers (note that, since this is
	// concurrent, this may be a transient state, but mark
	// termination will clean it up). Between background workers
	// and assists, we don't really know how many workers there
	// will be, so we pretend to have an arbitrarily large number
	// of workers, almost all of which are "waiting". While a
	// worker is working it decrements nwait. If nproc == nwait,

	// working is true if an update is pending or being worked by a pod worker
	// goroutine.
	working bool
	// pendingUpdate is the updated state the pod worker should observe. It is
	// cleared and moved to activeUpdate when a pod worker reads it. A new update
	// may always replace a pending update as the pod worker does not guarantee
	// that all intermediate states are synced to a worker, only the most recent.

		}
		stillWorking := false

		// ignore held workers
		w.lock.Lock()
		for uid := range w.holds {
			pausedWorkers[uid] = struct{}{}
		}
		w.lock.Unlock()

		// check for at least one still working non-paused worker
		w.w.podLock.Lock()
		for uid, worker := range w.w.podSyncStatuses {
			if _, ok := pausedWorkers[uid]; ok {
				continue
			}
			if worker.working {
				stillWorking = true
				break

					"ivy",
					"testing-native",
					"maven",
					"integ-test"
				]
			},
			{
				"parallelizationMethod":{
					"name":"TestDistribution"
				},
				"subprojects":[
					"workers",
					"model-core",
					"language-groovy",
					"build-init",
					"logging",
					"plugins-groovy",
					"kotlin-dsl",
					"plugins-java",
					"samples",
					"plugin-development",

// newBatchJobPool creates a pool of job manifest workers of specified size
func newBatchJobPool(ctx context.Context, o ObjectLayer, workers int) *BatchJobPool {
	jpool := &BatchJobPool{
		ctx:          ctx,
		objLayer:     o,
		jobCh:        make(chan *BatchJobRequest, 10000),
		workerKillCh: make(chan struct{}, workers),
		jobCancelers: make(map[string]context.CancelFunc),
	}

Gradle uses the single build worker pool to concurrently compile and link native components, by default. No special configuration is required to enable concurrent building.

[[rel5.0:worker_api]]
=== [5.0] Worker API: working directory of a worker can no longer be set

Since JDK 11 no longer supports changing the working directory of a running process, setting the working directory of a worker via its fork options is now prohibited.

All workers now use the same working directory to enable reuse.

	nodeNameKeyIndex = "spec.nodeName"
	// podUpdateWorkerSizes assumes that in most cases pod will be handled by monitorNodeHealth pass.
	// Pod update workers will only handle lagging cache pods. 4 workers should be enough.
	podUpdateWorkerSize = 4
	// nodeUpdateWorkerSize defines the size of workers for node update or/and pod update.
	nodeUpdateWorkerSize = 8

	// taintEvictionController is defined here in order to prevent imports of