Dark silicon management: an integrated and coordinated cross-layer approach

Author:

Pagani Santiago1,Bauer Lars1,Chen Qingqing2,Glocker Elisabeth3,Hannig Frank4,Herkersdorf Andreas5,Khdr Heba1,Pathania Anuj1,Schlichtmann Ulf2,Schmitt-Landsiedel Doris3,Sagi Mark5,Sousa Éricles4,Wagner Philipp5,Wenzel Volker1,Wild Thomas5,Henkel Jörg1

Affiliation:

1. Chair for Embedded Systems (CES), Karlsruhe Institute of Technology (KIT), Haid-und-Neu-Str. 7, 76131 Karlsruhe, Germany Germany

2. Chair of Electronic Design Automation, Technical University of Munich, Arcisstr. 21, 80333 Munich, Germany Germany

3. Chair for Technical Electronics, Technical University of Munich, Arcisstr. 21, 80333 Munich, Germany Germany

4. Department of Computer Science 12 (Hardware-Software-Co-Design), University of Erlangen-Nuremberg, Cauerstr. 11, 91058 Erlangen, Germany Germany

5. Chair for Integrated Systems, Technical University of Munich, Arcisstr. 21, 80333 Munich, Germany Germany

Abstract

Abstract This paper presents an integrated and coordinated cross-layer sensing and optimization flow for distributed dark silicon management for tiled heterogeneous manycores under a critical temperature constraint. We target some of the key challenges in dark silicon for manycores, such as: directly focusing on power density/temperature instead of considering simple per-chip power constraints, considering tiled heterogeneous architectures with different types of cores and accelerators, handling the large volumes of raw sensor information, and maintaining scalability. Our solution is separated into three abstraction layers: a sensing layer (involving hardware monitors and pre-processing), a dark silicon layer (that derives thermally-safe mappings and voltage/frequency settings), and an agent layer (used for selecting the parallelism of applications and thread-to-core mapping based on alternatives/constraints from the dark silicon layer).

Publisher

Walter de Gruyter GmbH

Subject

General Computer Science

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. PkMin: Peak Power Minimization for Multi-Threaded Many-Core Applications;Journal of Low Power Electronics and Applications;2020-09-30

2. BrezeFlow: Unified Debugger for Android CPU Power Governors and Schedulers on Edge Devices;2020 57th ACM/IEEE Design Automation Conference (DAC);2020-07

3. Hybrid Mapping for Increased Security;Invasive Computing for Mapping Parallel Programs to Many-Core Architectures;2017-12-30

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