A Survey on Dynamic Job Scheduling in Grid Environment Based on Heuristic Algorithms
원문 초록
Computational Grids are a new trend in distributed computing systems. They allow the sharing of geographically distributed resources in an efficient way, extending the boundaries of what we perceive as distributed computing. Various sciences can benefit from the use of grids to solve CPU-intensive problems, creating potential benefits to the entire society. Job scheduling is an integrated part of parallel and distributed computing. It allows selecting correct match of resource for a particular job and thus increases the job throughput and utilization of resources. Job should be scheduled in an automatic way to make the system more reliable, accessible and less sensitive to subsystem failures. This paper provides a survey on various heuristic algorithms, used for scheduling in grid.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
ConsumerBench: Benchmarking Generative AI Applications on End-User Devices
FlashDMoE: Fast Distributed MoE in a Single Kernel
KernelOracle: Predicting the Linux Scheduler's Next Move with Deep Learning
Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets
AKG: Automatic Kernel Generation for Neural Processing Units using Polyhedral Transformations
Optimal Sensor Scheduling and Selection for Continuous-Discrete Kalman Filtering with Auxiliary Dynamics
토론
이 논문과 연결된 포럼 글이 아직 없습니다.