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211 lines
6.8 KiB
211 lines
6.8 KiB
--- src/cern/colt/matrix/linalg/SmpBlas.java.orig 2015-10-07 22:23:44.969486000 +0000
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+++ src/cern/colt/matrix/linalg/SmpBlas.java 2015-10-07 22:29:15.475486000 +0000
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@@ -10,7 +10,8 @@
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import cern.colt.matrix.DoubleMatrix1D;
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import cern.colt.matrix.DoubleMatrix2D;
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-import EDU.oswego.cs.dl.util.concurrent.FJTask;
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+
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+import java.util.concurrent.ForkJoinTask;
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/**
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Parallel implementation of the Basic Linear Algebra System for symmetric multi processing boxes.
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Currently only a few algorithms are parallelised; the others are fully functional, but run in sequential mode.
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@@ -198,7 +199,7 @@
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// set up concurrent tasks
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int span = width/noOfTasks;
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- final FJTask[] subTasks = new FJTask[noOfTasks];
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+ final ForkJoinTask[] subTasks = new ForkJoinTask[noOfTasks];
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for (int i=0; i<noOfTasks; i++) {
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final int offset = i*span;
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if (i==noOfTasks-1) span = width - span*i; // last span may be a bit larger
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@@ -217,24 +218,30 @@
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CC = C.viewPart(offset,0,span,p);
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}
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- subTasks[i] = new FJTask() {
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+ subTasks[i] = new ForkJoinTask() {
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public void run() {
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seqBlas.dgemm(transposeA,transposeB,alpha,AA,BB,beta,CC);
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//System.out.println("Hello "+offset);
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}
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+
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+ public boolean exec() { return true; }
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+ public void setRawResult(Object o) {}
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+ public Object getRawResult() {return null;}
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};
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}
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// run tasks and wait for completion
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- try {
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- this.smp.taskGroup.invoke(
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- new FJTask() {
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- public void run() {
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- coInvoke(subTasks);
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- }
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- }
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- );
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- } catch (InterruptedException exc) {}
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+ this.smp.taskGroup.invoke(
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+ new ForkJoinTask() {
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+ public void run() {
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+ invokeAll(subTasks);
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+ }
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+
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+ public boolean exec() { return true; }
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+ public void setRawResult(Object o) {}
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+ public Object getRawResult() {return null;}
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+ }
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+ );
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}
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public void dgemv(final boolean transposeA, final double alpha, DoubleMatrix2D A, final DoubleMatrix1D x, final double beta, DoubleMatrix1D y) {
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/*
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@@ -271,7 +278,7 @@
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// set up concurrent tasks
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int span = width/noOfTasks;
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- final FJTask[] subTasks = new FJTask[noOfTasks];
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+ final ForkJoinTask[] subTasks = new ForkJoinTask[noOfTasks];
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for (int i=0; i<noOfTasks; i++) {
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final int offset = i*span;
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if (i==noOfTasks-1) span = width - span*i; // last span may be a bit larger
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@@ -280,24 +287,30 @@
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final DoubleMatrix2D AA = A.viewPart(offset,0,span,n);
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final DoubleMatrix1D yy = y.viewPart(offset,span);
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- subTasks[i] = new FJTask() {
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+ subTasks[i] = new ForkJoinTask() {
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public void run() {
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seqBlas.dgemv(transposeA,alpha,AA,x,beta,yy);
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//System.out.println("Hello "+offset);
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}
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+
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+ public boolean exec() { return true; }
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+ public void setRawResult(Object o) {}
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+ public Object getRawResult() {return null;}
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};
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}
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// run tasks and wait for completion
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- try {
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- this.smp.taskGroup.invoke(
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- new FJTask() {
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- public void run() {
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- coInvoke(subTasks);
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- }
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- }
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- );
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- } catch (InterruptedException exc) {}
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+ this.smp.taskGroup.invoke(
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+ new ForkJoinTask() {
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+ public void run() {
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+ invokeAll(subTasks);
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+ }
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+
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+ public boolean exec() { return true; }
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+ public void setRawResult(Object o) {}
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+ public Object getRawResult() {return null;}
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+ }
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+ );
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}
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public void dger(double alpha, DoubleMatrix1D x, DoubleMatrix1D y, DoubleMatrix2D A) {
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seqBlas.dger(alpha,x,y,A);
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@@ -369,9 +382,6 @@
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/**
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* Prints various snapshot statistics to System.out; Simply delegates to {@link EDU.oswego.cs.dl.util.concurrent.FJTaskRunnerGroup#stats}.
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*/
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-public void stats() {
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- if (this.smp!=null) this.smp.stats();
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-}
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private double xsum(DoubleMatrix2D A) {
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double[] sums = run(A,true,
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new Matrix2DMatrix2DFunction() {
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--- src/cern/colt/matrix/linalg/Smp.java.orig 2015-10-07 21:08:19.443486000 +0000
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+++ src/cern/colt/matrix/linalg/Smp.java 2015-10-07 22:28:24.722486000 +0000
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@@ -9,12 +9,13 @@
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package cern.colt.matrix.linalg;
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import cern.colt.matrix.DoubleMatrix2D;
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-import EDU.oswego.cs.dl.util.concurrent.FJTask;
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-import EDU.oswego.cs.dl.util.concurrent.FJTaskRunnerGroup;
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+import java.util.concurrent.ForkJoinTask;
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+import java.util.concurrent.ForkJoinPool;
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+
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/*
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*/
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class Smp {
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- protected FJTaskRunnerGroup taskGroup; // a very efficient and light weight thread pool
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+ protected ForkJoinPool taskGroup; // a very efficient and light weight thread pool
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protected int maxThreads;
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/**
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@@ -24,41 +25,39 @@
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maxThreads = Math.max(1,maxThreads);
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this.maxThreads = maxThreads;
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if (maxThreads>1) {
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- this.taskGroup = new FJTaskRunnerGroup(maxThreads);
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+ this.taskGroup = new ForkJoinPool(maxThreads);
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}
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else { // avoid parallel overhead
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this.taskGroup = null;
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}
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}
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-/**
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- * Clean up deamon threads, if necessary.
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- */
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-public void finalize() {
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- if (this.taskGroup!=null) this.taskGroup.interruptAll();
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-}
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protected void run(final DoubleMatrix2D[] blocksA, final DoubleMatrix2D[] blocksB, final double[] results, final Matrix2DMatrix2DFunction function) {
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- final FJTask[] subTasks = new FJTask[blocksA.length];
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+ final ForkJoinTask[] subTasks = new ForkJoinTask[blocksA.length];
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for (int i=0; i<blocksA.length; i++) {
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final int k = i;
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- subTasks[i] = new FJTask() {
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+ subTasks[i] = new ForkJoinTask() {
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public void run() {
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double result = function.apply(blocksA[k],blocksB != null ? blocksB[k] : null);
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if (results!=null) results[k] = result;
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//System.out.print(".");
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}
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+ public boolean exec() { return true; }
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+ public void setRawResult(Object o) {}
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+ public Object getRawResult() {return null;}
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};
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}
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// run tasks and wait for completion
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- try {
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- this.taskGroup.invoke(
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- new FJTask() {
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- public void run() {
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- coInvoke(subTasks);
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- }
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- }
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- );
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- } catch (InterruptedException exc) {}
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+ this.taskGroup.invoke(
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+ new ForkJoinTask() {
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+ public void run() {
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+ invokeAll(subTasks);
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+ }
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+ public boolean exec() { return true; }
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+ public void setRawResult(Object o) {}
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+ public Object getRawResult() {return null;}
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+ }
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+ );
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}
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protected DoubleMatrix2D[] splitBlockedNN(DoubleMatrix2D A, int threshold, long flops) {
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/*
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@@ -186,10 +185,4 @@
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}
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return blocks;
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}
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-/**
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- * Prints various snapshot statistics to System.out; Simply delegates to {@link EDU.oswego.cs.dl.util.concurrent.FJTaskRunnerGroup#stats}.
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- */
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-public void stats() {
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- if (this.taskGroup!=null) this.taskGroup.stats();
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-}
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}
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