NDLI: Modestly faster histogram computations on GPUs

Content Provider	IEEE Xplore Digital Library
Author	Brown, S. Snoeyink, J.
Copyright Year	2012
Description	Author affiliation: UNC Chapel Hill, 201 South Columbia St, NC 27599-3175, USA (Brown, S.; Snoeyink, J.)
Abstract	We present TRISH, a 256-bin histogram method for byte data that runs up to 50% faster than previous GPU methods for random data and 2–4× faster for image data. The performance gains come from reducing total cycle counts. Reducing cycles comes from improving 1) thread level parallelism (TLP), 2) instruction level parallelism (ILP) and 3) software vector parallelism (VP). TLP is improved by increasing occupancy from 2 to 3 thread blocks, achieved by compacting “per thread” histograms in shared memory, and by using register arrays. ILP is improved by increasing independent instructions via loop unrolling by a factor of k= [1‥63] and batching operations into groups of four. VP is supported by compacting bin counts into four 8-bit quads per 32-bit element and reducing binning & accumulating instructions by working with 32-bit elements as overlapping 16-bit pairs instead of 4 individual bytes. Note that TRISH is a deterministic algorithm that avoids atomic operations and gives performance that is data independent.
Starting Page	1
Ending Page	7
File Size	1112146
Page Count	7
File Format	PDF
ISBN	9781467326322
e-ISBN	9781467326339
e-ISBN	9781467326315
DOI	10.1109/InPar.2012.6339589
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	CUDA Histogram Buildings Abstracts Throughput Parallel Processing Registers Kernel GPU
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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