Minor optimizations for NanoScheduler

-- Reducer.maybeReleaseLatch is no longer synchronized
-- NanoScheduler only prints progress every 100 or so map calls

public/java/src/org/broadinstitute/sting/utils/nanoScheduler/NanoScheduler.java

@@ -43,7 +43,7 @@ import java.util.concurrent.*;
 public class NanoScheduler<InputType, MapType, ReduceType> {
     private final static Logger logger = Logger.getLogger(NanoScheduler.class);
     private final static boolean ALLOW_SINGLE_THREAD_FASTPATH = true;
-    private final static boolean LOG_MAP_TIMES = false;
+    protected final static int UPDATE_PROGRESS_FREQ = 100;
 
     final int bufferSize;
     final int nThreads;
@@ -243,8 +243,7 @@ public class NanoScheduler<InputType, MapType, ReduceType> {
                 // map
                 final MapType mapValue = map.apply(input);
 
-                if ( progressFunction != null )
-                    progressFunction.progress(input);
+                updateProgress(i++, input);
 
                 // reduce
                 sum = reduce.apply(mapValue, sum);
@@ -254,6 +253,16 @@ public class NanoScheduler<InputType, MapType, ReduceType> {
         return sum;
     }
 
+    /**
+     * Maybe update the progress meter (maybe because we don't want to do so so often that it costs cpu time)
+     * @param counter increasing counter to use to cut down on updates
+     * @param input the input we're currently at
+     */
+    private void updateProgress(final int counter, final InputType input) {
+        if ( progressFunction != null && counter % UPDATE_PROGRESS_FREQ == 0 )
+            progressFunction.progress(input);
+    }
+
     /**
      * Efficient parallel version of Map/Reduce
      *
@@ -453,8 +462,7 @@ public class NanoScheduler<InputType, MapType, ReduceType> {
                     // enqueue the result into the mapResultQueue
                     result = new MapResult<MapType>(mapValue, inputWrapper.getId());
 
-                    if ( progressFunction != null )
-                        progressFunction.progress(input);
+                    updateProgress(inputWrapper.getId(), input);
                 } else {
                     // if there's no input we push empty MapResults with jobIDs for synchronization with Reducer
                     result = new MapResult<MapType>(inputWrapper.getId());

public/java/src/org/broadinstitute/sting/utils/nanoScheduler/Reducer.java

@@ -117,7 +117,7 @@ class Reducer<MapType, ReduceType> {
      *
      * Appropriate means we've seen the last job, or there's only a single job id
      */
-    private synchronized void maybeReleaseLatch() {
+    private void maybeReleaseLatch() {
         if ( numJobsReduced == numSubmittedJobs ) {
             // either we've already seen the last one prevJobID == numSubmittedJobs or
             // the last job ID is -1, meaning that no jobs were ever submitted

public/java/test/org/broadinstitute/sting/utils/nanoScheduler/NanoSchedulerUnitTest.java

@@ -101,7 +101,7 @@ public class NanoSchedulerUnitTest extends BaseTest {
 
         public int nExpectedCallbacks() {
             int nElements = Math.max(end - start, 0);
-            return nElements / bufferSize;
+            return nElements / bufferSize / NanoScheduler.UPDATE_PROGRESS_FREQ;
         }
 
         public Map2x makeMap() { return addDelays ? new Map2xWithDelays() : new Map2x(); }