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  1. Proceedings of the 7th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and the 5th Workshop on Design Tools and Architectures For Multicore Embedded Computing Platforms (PARMA-DITAM '16)
  2. Runtime resource management for embedded and HPC systems
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Stack size estimation on machine-independent intermediate code for OpenCL kernels
Predictive modeling methodology for compiler phase-ordering
Flexible resource allocation and management for application graphs on ReNÉ MPSoC
Low communication overhead dynamic mapping of multiple HEVC video stream decoding on NoCs
Deploying and monitoring hadoop MapReduce analytics on single-chip cloud computer
Runtime resource management for embedded and HPC systems

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Runtime resource management for embedded and HPC systems

Content Provider ACM Digital Library
Author Pozzi, Gianmario Reghenzani, Federico Belluschi, Mauro Fornaciari, William Marchese, Andrea
Abstract Resource management is a well known problem in almost every computing system ranging from embedded to High Performance Computing (HPC) and is useful to optimize multiple orthogonal system metrics such as power consumption, performance and reliability. To achieve such an optimization a resource manager must suitably allocate the available system resources -- e.g. processing elements, memories and interconnect -- to the running applications. This kind of process incurs in two main problems: a) system resources are usually shared between multiple applications and this induces resource contention; and b) each application requires a different Quality of Service, making it harder for the resource manager to work in an application-agnostic mode. In this scenario, resource management represents a critical and essential component in a computing system and should act at different levels to optimize the whole system while keeping it flexible and versatile. In this paper we describe a multi-layer resource management strategy that operates at application, operating system and hardware level and tries to optimize resource allocation on embedded, desktop multi-core and HPC systems.
Starting Page 31
Ending Page 36
Page Count 6
File Format PDF
ISBN 9781450340526
DOI 10.1145/2872421.2893173
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2016-01-18
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Power management Runtime resource management
Content Type Text
Resource Type Article
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