Difference between revisions of "Iterative Averaging"
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{{Parallel|public double[] iterativelyAverage(List<Slice<double[]>> slices, double[] originalArray, int iterationCount)}} | {{Parallel|public double[] iterativelyAverage(List<Slice<double[]>> slices, double[] originalArray, int iterationCount)}} | ||
− | Before you get started on this, make sure you review the [[Background]] | + | Before you get started on this, make sure you review the [[Iterative Averaging#Backgound | Background]] |
=Testing Your Solution= | =Testing Your Solution= |
Revision as of 02:47, 6 June 2018
Contents
Motivation
Iterative Averaging is the process of updating an array to so that each index becomes the average of the indices one before and one after it. After repeating this for many iterations, the array may converge to one set of numbers. For example, when given the following array, we can perform iterations of this algorithm until the array eventually converges:
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.5 | 1 |
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.25 | 0.5 | 1 |
0 | 0.1 | 0.2 | 0.3 | 0.4 | 0.5 | 0.6 | 0.7 | 0.8 | 0.9 | 1 |
Note that the ends of the array remain the same value from the previous iteration.
X10/Habanero like Phasers have been added to Java since JDK7. We will gain some experience with using Phasers in a parallel for-loop context. Phasers allow us to change the structure of our loops and reduce overhead in the algorithm.
For more information on the algorithm and how we can use Phasers to make it better, review Topic 3.5 from the RiceX course.
Background
- bulkRegister
- arriveAndAwaitAdvance
- arriveAndDeregister (note: not required for this studio, but good to know about.)
Warning: Our use of the forall loop with Phasers does not accurately convey their finicky nature. More than other features, Phasers seem to require more care to get performance improvements. |
Code to Investigate
class AbstractSwappable
- getSrc()
- getDst()
- swap()
class SwappableDoubleArrays implements AbstractSwappable
new SwappableDoubleArrays(int registrations, double[] originalData)
Sequential Iterative Averaging
class: | SequentialIterativeAverager.java | DEMO: |
methods: | iterativelyAverage | |
package: | iterativeaveraging.demo | |
source folder: | src//java |
method: public double[] iterativelyAverage(List<Slice<double[]>> slices, double[] originalArray, int iterationCount)
(sequential implementation only)
SwappableDoubleArrays data = new SwappableDoubleArrays(1, originalArray); for (int iteration = 0; iteration < iterationCount; iteration++) { double[] arrayPrev = data.getSrc(); double[] arrayNext = data.getDst(); for (Slice<double[]> slice : slices) { for (int index = slice.getMinInclusive(); index < slice.getMaxExclusive(); index++) { arrayNext[index] = (arrayPrev[index - 1] + arrayPrev[index + 1]) * 0.5; } } data.swap(); } return data.getSrc(); }
This is a demo of the Iterative Averaging algorithm done sequentially. Take a look at the code in your repo. Some important questions/notes to think about:
- What does the
SwappableDoubleArrays
do and why is it useful in this algoritm? - Why is
data.getSrc()
returned and notdata.getDst()
? - Note that none of the slices contain the indices 0 or originalArray.length. If it did, the code would throw an OutOfBoundsException
PageRank
parallel
for (int iteration : new IntegerRange(0, iterationCount)) { forall(slices, (slice) -> { PageRank[] arrayPrev = ((iteration & 1) == 0) ? a : b; PageRank[] arrayNext = ((iteration & 1) == 0) ? b : a; slice.forEachIndex((index) -> { arrayNext[index] = calculateNextRank(index, arrayPrev); }); }); }
parallel phased
Phaser phaser = new Phaser(); phaser.bulkRegister(slices.size()); forall(slices, (slice) -> { for (int iteration : new IntegerRange(0, iterationCount)) { PageRank[] arrayPrev = ((iteration & 1) == 0) ? a : b; PageRank[] arrayNext = ((iteration & 1) == 0) ? b : a; slice.forEachIndex((index) -> { arrayNext[index] = calculateNextRank(index, arrayPrev); }); phaser.arriveAndAwaitAdvance(); } // note: arriveAndDeregister not required for this application phaser.arriveAndDeregister(); });
Code to Implement
class: | ForForallIterativeAverager.java | |
methods: | iterativelyAverage | |
package: | iterativeaveraging.studio | |
source folder: | student/src/main/java |
method: public double[] iterativelyAverage(List<Slice<double[]>> slices, double[] originalArray, int iterationCount)
(parallel implementation required)
class: | ForallForPhasedIterativeAverager.java | |
methods: | iterativelyAverage | |
package: | iterativeaveraging.studio | |
source folder: | student/src/main/java |
method: public double[] iterativelyAverage(List<Slice<double[]>> slices, double[] originalArray, int iterationCount)
(parallel implementation required)
Before you get started on this, make sure you review the Background
Testing Your Solution
Correctness
class: | IterativeAveragingTestSuite.java | |
package: | iterativeaveraging.studio | |
source folder: | testing/src/test/java |
Performance
class: | IterativeAveragingTiming.java | |
package: | iterativeaveraging.studio | |
source folder: | src/main/java |