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In the recent years virtually all processor architectures employ multiple cores per chip (CMPs). It is possible to use legacy (i.e., single-core) power saving techniques in CMPs which run either sequential applications or independent multithreaded workloads. However, new challenges arise when running parallel shared-memory applications. In the later case, sacri?cing some performance in a single core (thread) in order to be more energy-ef?cient might unintentionally delay the rest of cores (threads) due to synchronization points (locks/barriers), therefore, harming the performance of the whole application. CMPs increasingly face thermal and power-related problems during their typical use. Such problems can be solved by setting a power budget to the processor/core. This paper initially studies the behavior of different techniques to match a prede?ned power budget in a CMP processor. While legacy techniques properly work for thread independent/multi-programmed workloads, parallel workloads exhibit the problem of independently adapting the power of each core in a thread dependent scenario. In order to solve this problem we propose a novel mechanism, Power Token Balancing (PTB), aimed at accurately matching an external power constraint by balancing the power consumed among the different cores using a power tokenbased approach while optimizing the energy ef?ciency. We can use power (seen as tokens or coupons) from non-critical threads for the bene?t of critical threads. PTB runs transparent for thread independent / multiprogrammed workloads and can be also used as a spinlock detector based on power patterns. Results show that PTB matches more accurately a prede?ned power budget (total energy consumed over the budget is reduced to 8% for a 16-core CMP) than DVFS with only a 3% energy increase. Finally, we can trade accuracy on matching the power budget for energy-ef?ciency reducing the energy a 4% with a 20% of accuracy.

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