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Staccato: Shared-memory work-stealing task scheduler with cache-aware memory management. / Kuchumov, Ruslan; Sokolov, Andrey; Korkhov, Vladimir.
в: International Journal of Web and Grid Services, Том 15, № 4, 01.01.2019, стр. 394-407.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Staccato: Shared-memory work-stealing task scheduler with cache-aware memory management
AU - Kuchumov, Ruslan
AU - Sokolov, Andrey
AU - Korkhov, Vladimir
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Work-stealing is one of the popular ways to schedule near-optimal task distribution across multiple CPU cores with low overheads on time, memory and inter-thread synchronisations. In the work-stealing strategy, workers that run out of tasks for execution start claiming tasks from other workers' queues. Double ended queues (deques) based on circular arrays proved to be an effective solution for such scenario. In this paper we investigate ways to improve performance of work-stealing schedulers based on deques by enhancing internal data handling mechanisms. Traditionally, deques are designed with an assumption that task pointers are stored within these data structures, while task objects reside in the heap memory. By modifying task queues so that they can hold task objects instead of pointers we managed to increase the performance more than 2.5 times on CPU-bound applications and decrease last-level cache misses up to 30% compared to Intel TBB and Intel/MIT Cilk work-stealing schedulers.
AB - Work-stealing is one of the popular ways to schedule near-optimal task distribution across multiple CPU cores with low overheads on time, memory and inter-thread synchronisations. In the work-stealing strategy, workers that run out of tasks for execution start claiming tasks from other workers' queues. Double ended queues (deques) based on circular arrays proved to be an effective solution for such scenario. In this paper we investigate ways to improve performance of work-stealing schedulers based on deques by enhancing internal data handling mechanisms. Traditionally, deques are designed with an assumption that task pointers are stored within these data structures, while task objects reside in the heap memory. By modifying task queues so that they can hold task objects instead of pointers we managed to increase the performance more than 2.5 times on CPU-bound applications and decrease last-level cache misses up to 30% compared to Intel TBB and Intel/MIT Cilk work-stealing schedulers.
KW - Cache locality
KW - Fork-join parallelism
KW - Lock-free data structures
KW - Work-stealing deques
KW - Work-stealing scheduler
UR - http://www.scopus.com/inward/record.url?scp=85074111740&partnerID=8YFLogxK
U2 - 10.1504/IJWGS.2019.103233
DO - 10.1504/IJWGS.2019.103233
M3 - Article
AN - SCOPUS:85074111740
VL - 15
SP - 394
EP - 407
JO - International Journal of Web and Grid Services
JF - International Journal of Web and Grid Services
SN - 1741-1106
IS - 4
ER -
ID: 51559010