Publication | Closed Access
Scalable aggregation on multicore processors
66
Citations
10
References
2011
Year
Unknown Venue
Cluster ComputingEngineeringScalable AggregationComputer ArchitectureMultithreading (Computer Architecture)Shared MemoryPerformance BottleneckParallel ComputingManycore ProcessorComputer EngineeringComputer ScienceScalable ComputingMulti-threaded ProgrammingParallel Performance EvaluationCloud ComputingMany-core ArchitectureMultiprocessor SystemPotential ContentionParallel ProgrammingConcurrent Data Structure
In data-intensive and multi-threaded programming, the performance bottleneck has shifted from I/O bandwidth to main memory bandwidth. The availability, size, and other properties of on-chip cache strongly influence performance. A key question is whether to allow different threads to work independently, or whether to coordinate the shared workload among the threads. The independent approach avoids synchronization overhead, but requires resources proportional to the number of threads and thus is not scalable. On the other hand, the shared method suffers from coordination overhead and potential contention.
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