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## org.encog.neural.networks.training.concurrent
Class ConcurrentTrainingManager

    java.lang.Object
      org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager

All Implemented Interfaces:
  Runnable

    public final class ConcurrentTrainingManager

extends Object
implements Runnable

Concurrent training manager. This class allows you to queue up network training tasks to be executed either by the CPU cores or OpenCL devices. This allows the CPU/GPU to train neural networks at the same time.

Method Summary
`void` | `addPerformer(ConcurrentTrainingPerformer performer)` Add a performer.
`void` | `addTrainingJob(TrainingJob job)` Add a training job.
`void` | `clearPerformers()` Clear all of the performers.
`void` | `clearQueue()` Clear the workload.
`void` | `detectPerformers()` Detect performers.
`void` | `detectPerformers(boolean splitCores)` Detect performers.
`static ConcurrentTrainingManager` | `getInstance()`
`boolean` | `isSingleThreaded()`
`void` | `jobDone(long time, ConcurrentTrainingPerformerCPU perf)` Wait for job to finish.
`void` | `join()` Wait for all tasks to finish.
`void` | `run()` Perform the training.
`void` | `setReport(StatusReportable report)` Setup the object to report status to.
`void` | `setSingleThreaded(boolean singleThreaded)`
`void` | `start()` Start the manager.
`String` | `toString()`
`ConcurrentTrainingPerformer` | `waitForFreePerformer()` Wait for a free performer.

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait`

Method Detail

### getInstance

    public static ConcurrentTrainingManager getInstance()

  Returns:
    The singleton instance.

### addPerformer

    public void addPerformer(ConcurrentTrainingPerformer performer)

  Add a performer.

  Parameters:
    `performer` - The performer to add.

### addTrainingJob

    public void addTrainingJob(TrainingJob job)

  Add a training job.

  Parameters:
    `job` - The training job to add.

### clearPerformers

    public void clearPerformers()

  Clear all of the performers.

### clearQueue

    public void clearQueue()

  Clear the workload.

### detectPerformers

    public void detectPerformers()

  Detect performers. Create one performer for each OpenCL device, and another for the CPU's. If there is an OpenCL device already for the CPU, do not create another CPU performer.

### detectPerformers

    public void detectPerformers(boolean splitCores)

  Detect performers. Create one performer for each OpenCL device, and another for the CPU's. If there is an OpenCL device already for the CPU, do not create another CPU performer.

  Parameters:
    `splitCores` - True, if a CPU performer should be created for each core.

### isSingleThreaded

    public boolean isSingleThreaded()

  Returns:
    True, if single threaded.

### jobDone

    public void jobDone(long time,
                        ConcurrentTrainingPerformerCPU perf)

  Wait for job to finish.

  Parameters:
    `time` - The time to wait.
    `perf` - The performer.

### join

    public void join()

  Wait for all tasks to finish.

### run

    public void run()

  Perform the training.

  Specified by:
    `run` in interface `Runnable`

### setReport

    public void setReport(StatusReportable report)

  Setup the object to report status to.

  Parameters:
    `report` - The object to report status to.

### setSingleThreaded

    public void setSingleThreaded(boolean singleThreaded)

### start

    public void start()

  Start the manager.

### toString

    public String toString()

  Overrides:
    `toString` in class `Object`

### waitForFreePerformer

    public ConcurrentTrainingPerformer waitForFreePerformer()

  Wait for a free performer.

  Returns:
    The free performer.

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