Title
Accelerating Sequential Applications on CMPs Using Core Spilling
Abstract
Chip multiprocessors (CMPs) provide a scalable means of exploiting thread-level parallelism for multitasking or multithreaded applications. However, single-threaded applications will have difficulty dynamically leveraging the statically partitioned resources in a CMP. Such sequential applications may be difficult to statically decompose into threads or may simply be-a legacy code where recompilation is not possible or cost-effective. We present a novel approach to dynamically accelerate the performance of sequential application(s) on multiple cores. Execution is allowed to spill from one core to another when resources on one core have been exhausted. We propose two techniques to enable low-overhead migration between cores: prespilling and locality-based filtering. We develop and analyze an arbitration mechanism to intelligently allocate cores among a set of sequential applications on a CMP. On average, core spilling on an eight-core CMP can accelerate single-threaded performance by 35 percent. We further explore an eight-core CMP running a multiple application workload composed of the entire SPEC 2000 benchmark suite in various combinations and arrival times. Using core spilling to accelerate the current set of running applications in cases where there are idle cores, we achieve up to a 40 percent improvement in performance.
Year
DOI
Venue
2007
10.1109/TPDS.2007.1085
IEEE Trans. Parallel Distrib. Syst.
Keywords
Field
DocType
multithreaded application,idle core,core spilling,multiple application workload,current set,eight-core cmp,accelerating sequential applications,single-threaded performance,multiple core,sequential application,difficulty dynamically,acceleration,multitasking,registers,cost effectiveness,parallel processing,scheduling,thread level parallelism
Computer science,Task parallelism,Scheduling (computing),Parallel computing,Chip,Real-time computing,Thread (computing),Legacy code,Spec#,Human multitasking,Scalability
Journal
Volume
Issue
ISSN
18
8
1045-9219
Citations 
PageRank 
References 
8
0.68
30
Authors
5
Name
Order
Citations
PageRank
Jason Cong17069515.06
Han Guoling280.68
A. Jagannathan391.03
G. Reinman4211.75
K. Rutkowski581.02