Paper Info
Title
Exploiting fine-grained parallelism on cell processors
Abstract
Driven by increasing specialization, multicore integration will soon enable large-scale chip multiprocessors (CMPs) with many processing cores. In order to take advantage of increasingly parallel hardware, independent tasks must be expressed at a fine level of granularity to maximize the available parallelism and thus potential speedup. However, the efficiency of this approach depends on the runtime system, which is responsible for managing and distributing the tasks. In this paper, we present a hierarchically distributed task pool for task parallel programming on Cell processors. By storing subsets of the task pool in the local memories of the Synergistic Processing Elements (SPEs), access latency and thus overheads are greatly reduced. Our experiments show that only a worker-centric runtime system that utilizes the SPEs for both task creation and execution is suitable for exploiting fine-grained parallelism.
Year
DOI
Venue
2010
10.1007/978-3-642-15291-7_18
Euro-Par (2)
Keywords
Field
DocType
cell processor,available parallelism,independent task,fine-grained parallelism,parallel hardware,task creation,worker-centric runtime system,task pool,runtime system,task parallel programming
Load balancing (computing),Task parallelism,Computer science,Parallel computing,Chip,Data parallelism,Granularity,Multi-core processor,Distributed computing,Speedup,Runtime system
Conference
Volume
ISSN
ISBN
6272
0302-9743
3-642-15290-2
Citations 
PageRank 
References 
0
0.34
8
Authors
3
Name
Order
Citations
PageRank
Ralf Hoffmann100.34
Andreas Prell272.41
Thomas Rauber341564.60