Pathania et al., 2016 - Google Patents
Distributed scheduling for many-cores using cooperative game theoryPathania et al., 2016
View PDF- Document ID
- 17130450509525982710
- Author
- Pathania A
- Venkataramani V
- Shafique M
- Mitra T
- Henkel J
- Publication year
- Publication venue
- Proceedings of the 53rd Annual Design Automation Conference
External Links
Snippet
Many-cores are envisaged to include hundreds of processing cores etched on to a single die and will execute tens of multi-threaded tasks in parallel to exploit their massive parallel processing potential. A task can be sped up by assigning it to more than one core. Moreover …
- 230000004907 flux 0 abstract description 2
Classifications
-
- 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
- G06F9/48—Programme initiating; Programme switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
- G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
-
- 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]
- G06F9/5061—Partitioning or combining of resources
-
- 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
-
- 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]
- G06F9/5083—Techniques for rebalancing the load in a distributed system
- G06F9/5088—Techniques for rebalancing the load in a distributed system involving task migration
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3409—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
- G06F2217/78—Power analysis and optimization
-
- 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
-
- 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
- Y02B60/12—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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Sarood et al. | Maximizing throughput of overprovisioned hpc data centers under a strict power budget | |
Haque et al. | Exploiting heterogeneity for tail latency and energy efficiency | |
Van Craeynest et al. | Fairness-aware scheduling on single-ISA heterogeneous multi-cores | |
Ma et al. | Scalable power control for many-core architectures running multi-threaded applications | |
Bhadauria et al. | An approach to resource-aware co-scheduling for CMPs | |
Sheikh et al. | Energy-and performance-aware scheduling of tasks on parallel and distributed systems | |
Gerards et al. | On the interplay between global DVFS and scheduling tasks with precedence constraints | |
Polo et al. | Deadline-based MapReduce workload management | |
US7689773B2 (en) | Methods and apparatus for estimating fair cache miss rates on a chip multiprocessor | |
Rapp et al. | Power-and cache-aware task mapping with dynamic power budgeting for many-cores | |
Torng et al. | Asymmetry-aware work-stealing runtimes | |
Pathania et al. | Distributed scheduling for many-cores using cooperative game theory | |
Sarma et al. | SmartBalance: A sensing-driven linux load balancer for energy efficiency of heterogeneous MPSoCs | |
Lee et al. | Reducing peak power consumption inmulti-core systems without violatingreal-time constraints | |
Zhang et al. | Energy-efficient tasks scheduling heuristics with multi-constraints in virtualized clouds | |
Qian et al. | Reducing mobile device energy consumption with computation offloading | |
Molka et al. | Flexible workload generation for HPC cluster efficiency benchmarking | |
Padoin et al. | Saving energy by exploiting residual imbalances on iterative applications | |
Ma et al. | An analytical framework for estimating scale-out and scale-up power efficiency of heterogeneous manycores | |
Etinski et al. | Utilization driven power-aware parallel job scheduling | |
Pathania et al. | Distributed fair scheduling for many-cores | |
Cuesta et al. | Adaptive task migration policies for thermal control in mpsocs | |
Paolillo et al. | Quantifying energy consumption for practical fork-join parallelism on an embedded real-time operating system | |
Arima et al. | On the convergence of malleability and the HPC PowerStack: exploiting dynamism in over-provisioned and power-constrained HPC systems | |
Sheikh et al. | Energy-efficient cache-aware scheduling on heterogeneous multicore systems |