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ABSTRACT

In this paper we investigate and contrast two techniques to maximize the performance of multi-core processors under thermal constraints. The first technique is a distributed dynamic thermal management system that maximizes the total performance without exceeding given thermal constraints. In our scheme, each core adjusts its operating parameters, i.e., frequency and voltage, according to its temperature which is measured using integrated thermal sensors. We propose a novel controller that dynamically adapts the system to simultaneously avoid timing errors and thermal violations. For comparison purposes, we implement a second technique based on a runtime centralized, optimal system that uses combinatorial optimization techniques to calculate the optimal frequencies and voltages for the different cores to maximize the total throughput under thermal constraints. To empirically validate our techniques, we put together an extensive tool chain that incorporates thermal and power consumption simulators to characterize the performance of multi-core processors for a number of configurations ranging from 2 cores at 90 nm to 16 cores at 32 nm. Our results show that both investigated techniques are capable of delivering significant improvements (about 40% for 16 cores) over standard frequency and voltage planning techniques. From the results, we outline the main advantages and disadvantages of both techniques.

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INDEX TERMS

Primary Classification:
  B. Hardware
  B.7 INTEGRATED CIRCUITS
      B.7.2 Design Aids

General Terms:
Algorithms, Design, Performance

Keywords:
dfvs, thermal management, timing