Power Token Balancing: Adapting CMPs to Power Constraints for Parallel Multithreaded Workloads

Juan M. Cebri´n, Juan L. Aragón, Stefanos Kaxiras
2011 2011 IEEE International Parallel & Distributed Processing Symposium  
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, sacrificing some performance in a single core (thread) in order to be more energy-efficient might unintentionally delay the rest of cores
more » ... eads) 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 predefined power budget in a CMP processor. While legacy techniques properly work for thread independent/multiprogrammed 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 token-based approach while optimizing the energy efficiency. We can use power (seen as tokens or coupons) from non-critical threads for the benefit 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 predefined 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-efficiency reducing the energy a 4% with a 20% of accuracy.
doi:10.1109/ipdps.2011.49 dblp:conf/ipps/CebrianAK11 fatcat:46ksfhccuzbunohrcgpklk7zg4