Difference between revisions of "Scan"
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One of the downsides to parallel scan requires memory. For our scans we add the additional requirement that we will not mutate the incoming array parameter. We could create log(n) arrays, one for each level but that would be wasteful. If we create two array buffers and switch which is the source to read from and which is the destination to write from at each power of two level of the scan, we should be good to go. | One of the downsides to parallel scan requires memory. For our scans we add the additional requirement that we will not mutate the incoming array parameter. We could create log(n) arrays, one for each level but that would be wasteful. If we create two array buffers and switch which is the source to read from and which is the destination to write from at each power of two level of the scan, we should be good to go. | ||
− | The table below shows which array will be passed back for each offset | + | The table below shows which array will be passed back for each offset. |
{|class="wikitable" | {|class="wikitable" | ||
! ||1|||2||4||8||16 | ! ||1|||2||4||8||16 |
Revision as of 03:07, 31 March 2020
Contents
Motivation
Scan, also known as parallel prefix, is a fundamental and useful operation in parallel programming. We will gain experience in building Hillis & Steele scan with an optional work efficient Blellock scan.
Further, the dependencies in scan:
make it seem to have little hope for parallelism. However, simple yet clever approaches can achieve critical path lengths.
While we will simply implement prefix sum, scan can be used for other associative operations.
Background
Hillis-Steele Prefix Sum
(Extra Credit) Work-efficient Blelloch Scan
Scan Primitives for Vector Computers
Prefix Sums and Their Applications
Code To Investigate
class PhasableIntArrays extends AbstractPhasable
PhasableIntArrays
One of the downsides to parallel scan requires memory. For our scans we add the additional requirement that we will not mutate the incoming array parameter. We could create log(n) arrays, one for each level but that would be wasteful. If we create two array buffers and switch which is the source to read from and which is the destination to write from at each power of two level of the scan, we should be good to go.
The table below shows which array will be passed back for each offset.
1 | 2 | 4 | 8 | 16 | |
---|---|---|---|---|---|
src: | data | a | b | a | b |
dst: | a | b | a | b | a |
NOTE: think about which array is the correct one to return from your scan method given how you write your code.
The Core Questions
- What are the tasks?
- What is the data?
- Is the data mutable?
- If so, how is it shared?
Code To Implement
Sequential Scan
class: | SequentialScan.java | |
methods: | sumScanInclusive | |
package: | scan.studio | |
source folder: | student/src/main/java |
method: public static int[] sumScanInclusive(int[] data)
(sequential implementation only)
Warning:Do NOT mutate the data parameter. Return a new array which contains the sum scan of data. |
Hillis and Steele Parallel Scan
class: | StepEfficientParallelScan.java | |
methods: | sumScanInclusive | |
package: | scan.studio | |
source folder: | student/src/main/java |
method: private static int[] sumScanInclusive(PhasableIntArrays phasable)
(parallel implementation required)
(Extra Credit) Blelloch Work Efficient Scan
class: | WorkEfficientParallelScan.java | |
methods: | sumScanExclusiveInPlace | |
package: | scan.challenge | |
source folder: | student/src/main/java |
method: public static void sumScanExclusiveInPlace(int[] data)
(parallel implementation required)
Testing Your Solution
Correctness
Required
class: | ScanTestSuite.java | |
package: | scan.studio | |
source folder: | testing/src/test/java |
Optional Work Efficient
class: | WorkEfficientScanTestSuite.java | |
package: | scan.challenge | |
source folder: | testing/src/test/java |