Kiran et al., 2009 - Google Patents
Execution time prediction of imperative paradigm tasks for grid scheduling optimizationKiran et al., 2009
View PDF- Document ID
- 2397259761309465396
- Author
- Kiran M
- Hashim A
- Kuan L
- Jiun Y
- Publication year
- Publication venue
- International Journal of Computer Science and Network Security
External Links
Snippet
An efficient functioning of a complicated and dynamic grid environment requires a resource manager to monitor and identify the idling resources and to schedule users' submitted jobs (or programs) accordingly. A common problem arising in grid computing is to select the most …
- 238000005457 optimization 0 title 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
- G06F9/50—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
- 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
- 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
- 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
- G06F11/3457—Performance evaluation by simulation
-
- 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
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3604—Software analysis for verifying properties of programs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/40—Transformations of program code
- G06F8/41—Compilation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/70—Software maintenance or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Aleti et al. | Software architecture optimization methods: A systematic literature review | |
| Ganapathi et al. | Statistics-driven workload modeling for the cloud | |
| US8418137B2 (en) | Adaptive evolutionary computer software products | |
| Ardagna et al. | Performance prediction of cloud-based big data applications | |
| Gibilisco et al. | Stage aware performance modeling of dag based in memory analytic platforms | |
| Litoiu | A performance analysis method for autonomic computing systems | |
| Wu et al. | On performance modeling and prediction in support of scientific workflow optimization | |
| Kiran et al. | Execution time prediction of imperative paradigm tasks for grid scheduling optimization | |
| Alavani et al. | Predicting execution time of CUDA kernel using static analysis | |
| Singh et al. | Analytical modeling for what-if analysis in complex cloud computing applications | |
| Friese et al. | Generating performance models for irregular applications | |
| Cai et al. | AutoMan: Resource-efficient provisioning with tail latency guarantees for microservices | |
| Rak | Performance modeling using queueing Petri nets | |
| Gianniti et al. | Optimizing quality-aware big data applications in the cloud | |
| Antonescu et al. | Improving management of distributed services using correlations and predictions in SLA-driven cloud computing systems | |
| Dumke et al. | Performance engineering: state of the art and current trends | |
| Dobre et al. | New trends in large scale distributed systems simulation | |
| Alavani et al. | Performance modeling of graphics processing unit application using static and dynamic analysis | |
| Kiran et al. | A prediction module to optimize scheduling in a grid computing environment | |
| Kounev et al. | Model-based techniques for performance engineering of business information systems | |
| Ehlers | Self-adaptive performance monitoring for component-based software systems | |
| Agnihotri et al. | PDSP-Bench: A Benchmarking System for Parallel and Distributed Stream Processing | |
| Upadhyay et al. | Dependency Prediction of Long-Time Resource Uses in HPC Environment | |
| Ferro et al. | High performance computing evaluation A methodology based on scientific application requirements | |
| Yaikhom et al. | Combining measurement and stochastic modelling to enhance scheduling decisions for a parallel mean value analysis algorithm |