74,330 research outputs found
Energy-Efficient Algorithms
We initiate the systematic study of the energy complexity of algorithms (in
addition to time and space complexity) based on Landauer's Principle in
physics, which gives a lower bound on the amount of energy a system must
dissipate if it destroys information. We propose energy-aware variations of
three standard models of computation: circuit RAM, word RAM, and
transdichotomous RAM. On top of these models, we build familiar high-level
primitives such as control logic, memory allocation, and garbage collection
with zero energy complexity and only constant-factor overheads in space and
time complexity, enabling simple expression of energy-efficient algorithms. We
analyze several classic algorithms in our models and develop low-energy
variations: comparison sort, insertion sort, counting sort, breadth-first
search, Bellman-Ford, Floyd-Warshall, matrix all-pairs shortest paths, AVL
trees, binary heaps, and dynamic arrays. We explore the time/space/energy
trade-off and develop several general techniques for analyzing algorithms and
reducing their energy complexity. These results lay a theoretical foundation
for a new field of semi-reversible computing and provide a new framework for
the investigation of algorithms.Comment: 40 pages, 8 pdf figures, full version of work published in ITCS 201
Synthesis and Stochastic Assessment of Cost-Optimal Schedules
We present a novel approach to synthesize good schedules for a class
of scheduling problems that is slightly more general than the
scheduling problem FJm,a|gpr,r_j,d_j|early/tardy. The idea is to prime
the schedule synthesizer with stochastic information more meaningful
than performance factors with the objective to minimize the expected
cost caused by storage or delay. The priming information is
obtained by stochastic simulation of the system environment. The generated
schedules are assessed again by simulation. The approach is
demonstrated by means of a non-trivial scheduling problem from
lacquer production. The experimental results show that our approach
achieves in all considered scenarios better results than the
extended processing times approach
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