[go: up one dir, main page]

Kuang et al., 2012 - Google Patents

Traffic-aware power optimization for network applications on multicore servers

Kuang et al., 2012

View PDF
Document ID
4696116878756557873
Author
Kuang J
Bhuyan L
Klefstad R
Publication year
Publication venue
Proceedings of the 49th Annual Design Automation Conference

External Links

Snippet

In this paper, we design, implement, and evaluate a traffic-aware and power-efficient multicore server system by translating incoming traffic rate to appropriate system operating level, which is then translated to optimal per-core frequency configuration. According to the …
Continue reading at scholar.archive.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F1/00—Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
    • G06F1/26—Power supply means, e.g. regulation thereof
    • G06F1/32—Means for saving power
    • G06F1/3203—Power Management, i.e. event-based initiation of power-saving mode
    • G06F1/3206—Monitoring a parameter, a device or an event triggering a change in power modality
    • G06F1/3209—Monitoring remote activity, e.g. over telephone line, network connection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F1/00—Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
    • G06F1/26—Power supply means, e.g. regulation thereof
    • G06F1/32—Means for saving power
    • G06F1/3203—Power Management, i.e. event-based initiation of power-saving mode
    • G06F1/3234—Action, measure or step performed to reduce power consumption
    • G06F1/3287—Power saving by switching off individual functional units in a computer system, i.e. selective power distribution
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F1/00—Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
    • G06F1/26—Power supply means, e.g. regulation thereof
    • G06F1/32—Means for saving power
    • G06F1/3203—Power Management, i.e. event-based initiation of power-saving mode
    • G06F1/3234—Action, measure or step performed to reduce power consumption
    • G06F1/324—Power saving by lowering clock frequency
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F1/00—Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
    • G06F1/26—Power supply means, e.g. regulation thereof
    • G06F1/32—Means for saving power
    • G06F1/3203—Power Management, i.e. event-based initiation of power-saving mode
    • G06F1/3234—Action, measure or step performed to reduce power consumption
    • G06F1/329—Power saving by task scheduling
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—INDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00—Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/10—Energy efficient computing
    • Y02B60/12—Reducing energy-consumption at the single machine level, e.g. processors, personal computers, peripherals, power supply
    • Y02B60/1207—Reducing energy-consumption at the single machine level, e.g. processors, personal computers, peripherals, power supply acting upon the main processing unit
    • Y02B60/1217—Frequency modification
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—INDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00—Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/10—Energy efficient computing
    • Y02B60/12—Reducing energy-consumption at the single machine level, e.g. processors, personal computers, peripherals, power supply
    • Y02B60/1278—Power management
    • Y02B60/1285—Controlling the supply voltage
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for programme control, e.g. control unit
    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5094—Allocation of resources, e.g. of the central processing unit [CPU] where the allocation takes into account power or heat criteria
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—INDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00—Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/10—Energy efficient computing
    • Y02B60/14—Reducing energy-consumption by means of multiprocessor or multiprocessing based techniques, other than acting upon the power supply
    • Y02B60/142—Resource allocation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—INDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00—Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/10—Energy efficient computing
    • Y02B60/14—Reducing energy-consumption by means of multiprocessor or multiprocessing based techniques, other than acting upon the power supply
    • Y02B60/144—Scheduling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for programme control, e.g. control unit
    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—INDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00—Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/10—Energy efficient computing
    • Y02B60/16—Reducing energy-consumption in distributed systems
    • Y02B60/167—Resource sharing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—INDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00—Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/30—Techniques for reducing energy-consumption in wire-line communication networks

Similar Documents

Publication Publication Date Title
Arshad et al. Utilizing power consumption and SLA violations using dynamic VM consolidation in cloud data centers
Mittal Power management techniques for data centers: A survey
Cho et al. On the interplay of parallelization, program performance, and energy consumption
Gu et al. Energy efficient scheduling of servers with multi-sleep modes for cloud data center
Li et al. Tapa: Temperature aware power allocation in data center with map-reduce
Tchernykh et al. Adaptive energy efficient scheduling in Peer-to-Peer desktop grids
Pagani et al. Energy efficient task partitioning based on the single frequency approximation scheme
Terzopoulos et al. Power-aware bag-of-tasks scheduling on heterogeneous platforms
Mathew et al. Energy-efficient content delivery networks using cluster shutdown
Xie et al. Schedule length minimization of parallel applications with energy consumption constraints using heuristics on heterogeneous distributed systems
Dargie et al. Analysis of the power and hardware resource consumption of servers under different load balancing policies
Orgerie et al. ERIDIS: energy-efficient reservation infrastructure for large-scale distributed systems
Terzopoulos et al. Bag-of-task scheduling on power-aware clusters using a dvfs-based mechanism
Priya et al. Energy-minimizing workload splitting and frequency selection for guaranteed performance over heterogeneous cores
Tian et al. Modeling and analyzing power management policies in server farms using stochastic petri nets
Li et al. Temperature aware power allocation: An optimization framework and case studies
Terzopoulos et al. Performance evaluation of a real-time grid system using power-saving capable processors
Kuang et al. Traffic-aware power optimization for network applications on multicore servers
Kant et al. Enhancing data center sustainability through energy-adaptive computing
Ghose et al. Energy efficient online scheduling of aperiodic real time task on large multi-threaded multiprocessor systems
Bergamaschi et al. Data center power and performance optimization through global selection of p-states and utilization rates
Nathuji et al. Providing platform heterogeneity-awareness for data center power management
Khan et al. A Game Theoretical Energy Efficient Resource Allocation Technique for Large Distributed Computing Systems.
Kant Distributed energy adaptive computing
Zhang‐Jian et al. An energy‐saving algorithm for cloud resource management using a Kalman filter