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Scale & Cap
- Source :
- ACM Transactions on Design Automation of Electronic Systems. 22:1-22
- Publication Year :
- 2017
- Publisher :
- Association for Computing Machinery (ACM), 2017.
-
Abstract
- As the number of cores per server node increases, designing multi-threaded applications has become essential to efficiently utilize the available hardware parallelism. Many application domains have started to adopt multi-threaded programming; thus, efficient management of multi-threaded applications has become a significant research problem. Efficient execution of multi-threaded workloads on cloud environments, where applications are often consolidated by means of virtualization, relies on understanding the multi-threaded specific characteristics of the applications. Furthermore, energy cost and power delivery limitations require data center server nodes to work under power caps, which bring additional challenges to runtime management of consolidated multi-threaded applications. This article proposes a dynamic resource allocation technique for consolidated multi-threaded applications for power-constrained environments. Our technique takes into account application characteristics specific to multi-threaded applications, such as power and performance scaling, to make resource distribution decisions at runtime to improve the overall performance, while accurately tracking dynamic power caps. We implement and evaluate our technique on state-of-the-art servers and show that the proposed technique improves the application performance by up to 21% under power caps compared to a default resource manager.
- Subjects :
- 010302 applied physics
Multi-core processor
business.industry
Computer science
Cloud computing
02 engineering and technology
computer.software_genre
Virtualization
01 natural sciences
Computer Graphics and Computer-Aided Design
020202 computer hardware & architecture
Computer Science Applications
Virtual machine
Embedded system
Server
0103 physical sciences
Dynamic demand
0202 electrical engineering, electronic engineering, information engineering
Data center
Resource management
Electrical and Electronic Engineering
business
computer
Subjects
Details
- ISSN :
- 15577309 and 10844309
- Volume :
- 22
- Database :
- OpenAIRE
- Journal :
- ACM Transactions on Design Automation of Electronic Systems
- Accession number :
- edsair.doi...........ec2333f05c7fb406e1429b413c0dc328