Optimizing Replication, Communication, and Capacity Allocation in CMPs
Proceedings of the 32nd annual international symposium on Computer Architecture
Fast and fair: data-stream quality of service
Proceedings of the 2005 international conference on Compilers, architectures and synthesis for embedded systems
Performance implications of single thread migration on a chip multi-core
ACM SIGARCH Computer Architecture News - Special issue: dasCMP'05
Adapting application execution in CMPs using helper threads
Journal of Parallel and Distributed Computing
A cross-layer approach to heterogeneity and reliability
MEMOCODE'09 Proceedings of the 7th IEEE/ACM international conference on Formal Methods and Models for Codesign
Software data spreading: leveraging distributed caches to improve single thread performance
PLDI '10 Proceedings of the 2010 ACM SIGPLAN conference on Programming language design and implementation
Inter-core prefetching for multicore processors using migrating helper threads
Proceedings of the sixteenth international conference on Architectural support for programming languages and operating systems
Reducing OLTP instruction misses with thread migration
DaMoN '12 Proceedings of the Eighth International Workshop on Data Management on New Hardware
SLICC: Self-Assembly of Instruction Cache Collectives for OLTP Workloads
MICRO-45 Proceedings of the 2012 45th Annual IEEE/ACM International Symposium on Microarchitecture
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We propose to modify a conventional single-chip multicore so that a sequential program can migrate from one core to another automatically during execution. The goal of execution migration is to take advantage of the overall onchip cache capacity. We introduce the affinity algorithm, a method for distributing cache lines automatically on several caches. We show that on working-sets exhibiting a property called "splittability", it is possible to trade cache misses for migrations. Our experimental results indicate that the proposed method has a potential for improving the performance of certain sequential programs, without degrading significantly the performance of others.