As feature sizes decrease, power dissipation and heat generation density exponentially increase. Thus, temperature gradients in Multiprocessor Systems on Chip (MPSoCs) can seriously impact system performance and reliability. Thermal balancing policies based on task migration have been proposed to modulate power distribution between processing cores to achieve temperature flattening. However, in the context of MPSoC for multimedia streaming computing, where timeliness is critical, the impact of migration on quality of service must be carefully analyzed. In this paper we present the design and implementation of a lightweight thermal balancing policy that reduces on-chip temperature gradients via task migration. This policy exploits run-time temperature and load information to balance the chip temperature. Moreover, we assess the effectiveness of the proposed policy for streaming computing architectures using a cycle-accurate thermal-aware emulation infrastructure. Our results using a real-life software defined radio multitask benchmark show that our policy achieves thermal balancing while keeping migration costs bounded.
Abstract-Die-temperature control to avoid hotspots is increasingly critical in multiprocessor systems-on-chip (MPSoCs) for stream computing. In this context, thermal balancing policies based on task migration are a promising approach to redistribute power dissipation and even out temperature gradients. Since stream computing applications require strict quality of service and timing constraints, the real-time performance impact of thermal balancing policies must be carefully evaluated. In this paper, we present the design of a lightweight thermal balancing policy MiGra, which bounds on-chip temperature gradients via task migration. The proposed policy exploits run-time temperature as well as workload information of streaming applications to define suitable run-time thermal migration patterns, which minimize the number of deadline misses. Furthermore, we have experimentally assessed the effectiveness of our thermal balancing policy using a complete field-programmable-gate-array-based emulation of an actual three-core MPSoC streaming platform coupled with a thermal simulator. Our results indicate that MiGra achieves significantly better thermal balancing than state-of-the-art thermal management solutions while keeping the number of migrations bounded.
Nowadays, the use of mobile applications and wearable technologies to support and encourage an active lifestyle has become widespread. Several studies put in evidence that the usage of these kinds of support has to be monitored by high-qualified figures, to favor a safe and a long-term adherence to training routines. In order to investigate the impact of these professionals, this work sets out to provide an overview and an evaluation of an e-Coaching ecosystem specifically designed for runners. The platform supports and guides people toward an active lifestyle by stimulating their motivation to exercise through the engagement provided by the interactions between users and human trainers. In this study we investigate the effectiveness of the support offered by the human trainers and the engagement of the users. The results show that the support of human qualified trainers is crucial. Users tend to be more engaged to train when their trainings are developed and remotely supervised by a human coach. This has resulted in more workout sessions performed with respect to users exercising by following standard or self-made routines without direct professional supervision. Our findings show that e-Coaching systems should develop their coaching protocols always taking into account the effectiveness of the support of qualified professionals over completely automated approaches.
As feature sizes decrease, power dissipation and heat generation density exponentially increase. Thus, temperature gradients in Multiprocessor Systems on Chip (MPSoCs) can seriously impact system performance and reliability. Thermal balancing policies based on task migration have been proposed to modulate power distribution between processing cores to achieve temperature flattening. However, in the context of MPSoC for multimedia streaming computing, where timeliness is critical, the impact of migration on quality of service must be carefully analyzed. In this paper we present the design and implementation of a lightweight thermal balancing policy that reduces on-chip temperature gradients via task migration. This policy exploits run-time temperature and load information to balance the chip temperature. Moreover, we assess the effectiveness of the proposed policy for streaming computing architectures using a cycle-accurate thermal-aware emulation infrastructure. Our results using a real-life software defined radio multitask benchmark show that our policy achieves thermal balancing while keeping migration costs bounded.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.