2013
DOI: 10.1109/tcad.2013.2245940
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A Variant of Parallel Plane Sweep Algorithm for Multicore Systems

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Cited by 11 publications
(4 citation statements)
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“…To address these shortcomings, we developed a parallel algorithm that concurrently chrom-sweeps “chunks” of query and database intervals. Unlike previous in-memory parallel sweeping methods that uniformly partition the input [ 15 ], we define (without the need for preprocessing [ 16 ]) chunks by consecutive query intervals that meet one of two criteria: either the set reaches the “chunk size” threshold or the genomic distance to the next interval exceeds the “gap size” threshold. Restricting the chunk size creates reasonably even work among the threads to support efficient load balancing (i.e., to avoid task divergence).…”
Section: Methodsmentioning
confidence: 99%
“…To address these shortcomings, we developed a parallel algorithm that concurrently chrom-sweeps “chunks” of query and database intervals. Unlike previous in-memory parallel sweeping methods that uniformly partition the input [ 15 ], we define (without the need for preprocessing [ 16 ]) chunks by consecutive query intervals that meet one of two criteria: either the set reaches the “chunk size” threshold or the genomic distance to the next interval exceeds the “gap size” threshold. Restricting the chunk size creates reasonably even work among the threads to support efficient load balancing (i.e., to avoid task divergence).…”
Section: Methodsmentioning
confidence: 99%
“…Parallel algorithm developed by McKenney et al and their OpenMP implementation is targeted towards multicore CPUs and it is not fine-grained to exploit the SIMT parallelism in GPUs [11,8,9]. Contrary to the abovementioned parallel algorithm, our algorithm is targeted to GPU and achieves higher speedup.…”
Section: Existing Work On Parallelizing Segment Intersection Algorithmsmentioning
confidence: 99%
“…To address these shortcomings, we developed a parallel algorithm that concurrently chromsweeps "chunks" of query and database intervals. Unlike previous in-memory parallel sweeping methods that uniformly partition the input [15], we define (without the need for preprocessing [16]) chunks by consecutive query intervals that meet one of two criteria: either the set reaches the "chunk size" threshold, or the genomic distance to the next interval exceeds the "gap size" threshold. Restricting the chunk size creates reasonably even work among the threads to support efficient load balancing (i.e., to avoid task divergence).…”
Section: A Parallel Chrom-sweep Algorithmmentioning
confidence: 99%