Algorithms for Dynamic Speed Scaling
Susanne Albers
- Vol. 9, pp 1-11
Reads0
Chats0
TLDR
This paper surveys algorithmic results on dynamic speed scaling in settings where (1) jobs have strict deadlines and (2) job flow times are to be minimized.Abstract:
Many modern microprocessors allow the speed/frequency to be set dynamically. The general goal is to execute a sequence of jobs on a variable-speed processor so as to minimize energy consumption. This paper surveys algorithmic results on dynamic speed scaling. We address settings where (1) jobs have strict deadlines and (2) job flow times are to be minimized.read more
Citations
More filters
Journal Article
Energy-efficient algorithms for flow time minimization
Susanne Albers,Hiroshi Fujiwara +1 more
TL;DR: A deterministic constant competitive online algorithm is devised and it is shown that the offline problem can be solved in polynomial time.
Proceedings ArticleDOI
POET: a portable approach to minimizing energy under soft real-time constraints
TL;DR: POET as discussed by the authors is an open-source C library and runtime system that takes a specification of the platform resources and optimizes the application execution to achieve predictable timing and energy reduction.
Proceedings ArticleDOI
Racing and Pacing to Idle: Theoretical and Empirical Analysis of Energy Optimization Heuristics
TL;DR: A geometrical framework for analyzing the energy optimality of resource allocation under performance constraints is presented and it is found that race-to-idle is near optimal on older systems, but can consume as much as 3× more energy than the optimal strategy.
Book ChapterDOI
Speed scaling on parallel processors with migration
TL;DR: In this article, the authors study the problem of scheduling a set of jobs with release dates, deadlines and processing requirements on parallel speed-scalable processors so as to minimize the total energy consumption.
Proceedings ArticleDOI
Energy Efficient Job Scheduling with DVFS for CPU-GPU Heterogeneous Systems
TL;DR: This paper proposes a heuristic algorithm for the case when processors can scale to any continuous speed, and extends this heuristic to the online case where jobs arrive over time, and shows that the proposed heuristic algorithms are effective and can achieve near-optimal performance.
References
More filters
Journal ArticleDOI
Amortized efficiency of list update and paging rules
TL;DR: This article shows that move-to-front is within a constant factor of optimum among a wide class of list maintenance rules, and analyzes the amortized complexity of LRU, showing that its efficiency differs from that of the off-line paging rule by a factor that depends on the size of fast memory.
Proceedings ArticleDOI
A scheduling model for reduced CPU energy
TL;DR: This paper proposes a simple model of job scheduling aimed at capturing some key aspects of energy minimization, and gives an off-line algorithm that computes, for any set of jobs, a minimum-energy schedule.
Journal ArticleDOI
Speed scaling to manage energy and temperature
TL;DR: The study of speed scaling to manage temperature is initiated and it is shown that the optimal temperature schedule can be computed offline in polynomial-time using the Ellipsoid algorithm and that no deterministic online algorithm can have a better competitive ratio.
Journal ArticleDOI
The Price of Performance: An Economic Case for Chip Multiprocessing
TL;DR: The high-computational demands that are inherent in most of Google’s services have led the research group to develop a deep understanding of the overall cost of computing, and continually to look for hardware/software designs that optimize performance per unit of cost.
Journal ArticleDOI
Algorithms for power savings
TL;DR: This paper examines two different mechanisms for saving power in battery-operated embedded systems and gives an off line algorithm which is within a factor of three of the optimal algorithm and an online algorithm with a constant competitive ratio.