private static void Fork <TKey, TValue, TLocal>([NotNull] Dictionary <TKey, TValue> collection, int batchSize, int maxDegreeOfParallelism, [Pooled] Func <TLocal> initializeLocal, [Pooled] Action <KeyValuePair <TKey, TValue>, TLocal> action, [Pooled] Action <TLocal> finalizeLocal, [NotNull] BatchState state)
{
// Other threads already processed all work before this one started. ActiveWorkerCount is already 0
if (state.StartInclusive >= collection.Count)
{
state.Release();
return;
}
// This thread is now actively processing work items, meaning there might be work in progress
Interlocked.Increment(ref state.ActiveWorkerCount);
// Kick off another worker if there's any work left
if (maxDegreeOfParallelism > 1 && state.StartInclusive + batchSize < collection.Count)
{
int workToSchedule = maxDegreeOfParallelism - 1;
for (int i = 0; i < workToSchedule; i++)
{
state.AddReference();
}
ThreadPool.Instance.QueueWorkItem(() => Fork(collection, batchSize, 0, initializeLocal, action, finalizeLocal, state), workToSchedule);
}
try
{
// Process batches synchronously as long as there are any
int newStart;
while ((newStart = Interlocked.Add(ref state.StartInclusive, batchSize)) - batchSize < collection.Count)
{
try
{
// TODO: Reuse enumerator when processing multiple batches synchronously
var start = newStart - batchSize;
ExecuteBatch(collection, newStart - batchSize, Math.Min(collection.Count, newStart) - start, initializeLocal, action, finalizeLocal);
}
finally
{
if (Interlocked.Add(ref state.WorkDone, batchSize) >= collection.Count)
{
// Don't wait for other threads to wake up and signal the BatchState, release as soon as work is finished
state.Finished.Set();
}
}
}
}
catch (Exception e)
{
Interlocked.Exchange(ref state.ExceptionThrown, e);
throw;
}
finally
{
state.Release();
}
}
private static void Fork(int endExclusive, int batchSize, int maxDegreeOfParallelism, [Pooled] Action <int> action, [NotNull] BatchState state)
{
// Other threads already processed all work before this one started. ActiveWorkerCount is already 0
if (state.StartInclusive >= endExclusive)
{
state.Release();
return;
}
// This thread is now actively processing work items, meaning there might be work in progress
Interlocked.Increment(ref state.ActiveWorkerCount);
// Kick off another worker if there's any work left
if (maxDegreeOfParallelism > 1 && state.StartInclusive + batchSize < endExclusive)
{
int workToSchedule = maxDegreeOfParallelism - 1;
for (int i = 0; i < workToSchedule; i++)
{
state.AddReference();
}
ThreadPool.Instance.QueueWorkItem(() => Fork(endExclusive, batchSize, 0, action, state), workToSchedule);
}
try
{
// Process batches synchronously as long as there are any
int newStart;
while ((newStart = Interlocked.Add(ref state.StartInclusive, batchSize)) - batchSize < endExclusive)
{
try
{
ExecuteBatch(newStart - batchSize, Math.Min(endExclusive, newStart), action);
}
finally
{
if (Interlocked.Add(ref state.WorkDone, batchSize) >= endExclusive)
{
// Don't wait for other threads to wake up and signal the BatchState, release as soon as work is finished
state.Finished.Set();
}
}
}
}
catch (Exception e)
{
Interlocked.Exchange(ref state.ExceptionThrown, e);
throw;
}
finally
{
state.Release();
}
}
private static void Fork <TKey, TValue, TLocal>([NotNull] Dictionary <TKey, TValue> collection, int batchSize, int maxDegreeOfParallelism, [Pooled] Func <TLocal> initializeLocal, [Pooled] Action <KeyValuePair <TKey, TValue>, TLocal> action, [Pooled] Action <TLocal> finalizeLocal,
[NotNull] BatchState state)
{
// Other threads already processed all work before this one started. ActiveWorkerCount is already 0
if (state.StartInclusive >= collection.Count)
{
state.Release();
return;
}
// This thread is now actively processing work items, meaning there might be work in progress
Interlocked.Increment(ref state.ActiveWorkerCount);
// Kick off another worker if there's any work left
if (maxDegreeOfParallelism > 1 && state.StartInclusive + batchSize < collection.Count)
{
state.AddReference();
ThreadPool.Instance.QueueWorkItem(() => Fork(collection, batchSize, maxDegreeOfParallelism - 1, initializeLocal, action, finalizeLocal, state));
}
try
{
// Process batches synchronously as long as there are any
int newStart;
while ((newStart = Interlocked.Add(ref state.StartInclusive, batchSize)) - batchSize < collection.Count)
{
// TODO: Reuse enumerator when processing multiple batches synchronously
var start = newStart - batchSize;
ExecuteBatch(collection, newStart - batchSize, Math.Min(collection.Count, newStart) - start, initializeLocal, action, finalizeLocal);
}
}
finally
{
state.Release();
// If this was the last batch, signal
if (Interlocked.Decrement(ref state.ActiveWorkerCount) == 0)
{
state.Finished.Set();
}
}
}
private static void Fork(int endExclusive, int batchSize, int maxDegreeOfParallelism, [Pooled] Action <int> action, [NotNull] BatchState state)
{
// Other threads already processed all work before this one started. ActiveWorkerCount is already 0
if (state.StartInclusive >= endExclusive)
{
state.Release();
return;
}
// This thread is now actively processing work items, meaning there might be work in progress
Interlocked.Increment(ref state.ActiveWorkerCount);
// Kick off another worker if there's any work left
if (maxDegreeOfParallelism > 1 && state.StartInclusive + batchSize < endExclusive)
{
state.AddReference();
ThreadPool.Instance.QueueWorkItem(() => Fork(endExclusive, batchSize, maxDegreeOfParallelism - 1, action, state));
}
try
{
// Process batches synchronously as long as there are any
int newStart;
while ((newStart = Interlocked.Add(ref state.StartInclusive, batchSize)) - batchSize < endExclusive)
{
ExecuteBatch(newStart - batchSize, Math.Min(endExclusive, newStart), action);
}
}
finally
{
state.Release();
// If this was the last batch, signal
if (Interlocked.Decrement(ref state.ActiveWorkerCount) == 0)
{
state.Finished.Set();
}
}
}
