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- Kanduri, Anil, et al.
(författare)
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Accuracy-Aware Power Management for Many-Core Systems Running Error-Resilient Applications
- 2017
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Ingår i: IEEE Transactions on Very Large Scale Integration (vlsi) Systems. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1063-8210 .- 1557-9999. ; 25:10, s. 2749-2762
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Tidskriftsartikel (refereegranskat)abstract
- Power capping techniques based on dynamic voltage and frequency scaling (DVFS) and power gating (PG) are oriented toward power actuation, compromising on performance and energy. Inherent error resilience of emerging application domains, such as Internet-of-Things (IoT) and machine learning, provides opportunities for energy and performance gains. Leveraging accuracy-performance tradeoffs in such applications, we propose approximation (APPX) as another knob for close-looped power management, to complement power knobs with performance and energy gains. We design a power management framework, APPEND+, that can switch between accurate and approximate modes of execution subject to system throughput requirements. APPEND+ considers the sensitivity of the application to error to make disciplined alteration between levels of APPX such that performance is maximized while error is minimized. We implement a power management scheme that uses APPX, DVFS, and PG knobs hierarchically. We evaluated our proposed approach over machine learning and signal processing applications along with two case studies on IoT-early warning score system and fall detection. APPEND+ yields 1.9x higher throughput, improved latency up to five times, better performance per energy, and dark silicon mitigation compared with the state-of-the-art power management techniques over a set of applications ranging from high to no error resilience.
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| 3. |
- Kanduri, Anil, et al.
(författare)
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Approximation Knob : Power Capping Meets Energy Efficiency
- 2016
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Ingår i: 2016 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN (ICCAD). - New York, NY, USA : Institute of Electrical and Electronics Engineers (IEEE). - 9781450344661
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Konferensbidrag (refereegranskat)abstract
- Power Capping techniques are used to restrict power consumption of computer systems to a thermally safe limit. Current many-core systems employ dynamic voltage and frequency scaling (DVFS), power gating (PG) and scheduling methods as actuators for power capping. These knobs are oriented towards power actuation, while the need for performance and energy savings are increasing in the dark silicon era. To address this, we propose approximation (APPX) as another knob for close-looped power management, lending performance and energy efficiency to existing power capping techniques. We use approximation in a pro-active way for long-term performance-energy objectives, complementing the short-term reactive power objectives. We implement an approximation-enabled power management framework, APPEND, that dynamically chooses an application with appropriate level of approximation from a set of variable accuracy implementations. Subject to the system dynamics, our power manager chooses an effective combination of knobs APPX, DVFS and PG, in a hierarchical way to ensure power capping with performance and energy gains. Our proposed approach yields 1.5x higher throughput, improved latency upto 5x, better performance per energy and dark silicon mitigation compared to state-of-the-art power management techniques over a set of applications ranging from high to no error resilience.
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- Rahmani, Amir M., et al.
(författare)
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Reliability-Aware Runtime Power Management for Many-Core Systems in the Dark Silicon Era
- 2017
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Ingår i: IEEE Transactions on Very Large Scale Integration (vlsi) Systems. - : IEEE Press. - 1063-8210 .- 1557-9999. ; 25:2, s. 427-440
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Tidskriftsartikel (refereegranskat)abstract
- Power management of networked many-core systems with runtime application mapping becomes more challenging in the dark silicon era. It necessitates considering network characteristics at runtime to achieve better performance while honoring the peak power upper bound. On the other hand, power management has a direct effect on chip temperature, which is the main driver of the aging effects. Therefore, alongside performance fulfillment, the controlling mechanism must also consider the current cores' reliability in its actuator manipulation to enhance the overall system lifetime in the long term. In this paper, we propose a multiobjective dynamic power management technique that uses current power consumption and other network characteristics including the reliability of the cores as the feedback while utilizing fine-grained voltage and frequency scaling and per-core power gating as the actuators. In addition, disturbance rejecter and reliability balancer are designed to help the controller to better smooth power consumption in the short term and reliability in the long term, respectively. Simulations of dynamic workloads and mixed criticality application profiles show that our method not only is effective in honoring the power budget while considerably boosting the system throughput, but also increases the overall system lifetime by minimizing aging effects by means of power consumption balancing.
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