Essays about: "distributed scheduling"

Showing result 1 - 5 of 44 essays containing the words distributed scheduling.

  1. 1. Optimizing the instruction scheduler of high-level synthesis tool

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Zihao Xu; [2023]
    Keywords : Instruction scheduling; Scheduling algorithm; CGRA; High-level Sythnesis; SiLago; Algorithm-level Synthesis; Constraint programming; Instruktion schemaläggning; schemaläggning algoritm; CGRA; High-level Sythnesis; SiLago; Algoritm-nivå Synthesis; Constraint programmering;

    Abstract : With the increasing complexity of the chip architecture design for meeting different application requirements, the corresponding instruction scheduler of high-level synthesis tool needs to solve complex scheduling problems. Dynamically Reconfigurable Resource Array (DRRA) is a novel architecture based on Coarse-Grained Reconfigurable Architecture (CGRA) on SiLago platform, the instruction scheduler of Vesyla-II, the dedicated High-Level Synthesis (HLS) tool targets for DRRA needs to schedule the specific instruction sets designed for Distributed Two-level Control System (D2LC). READ MORE

  2. 2. Decentralized Learning over Wireless Networks with Imperfect and Constrained Communication : To broadcast, or not to broadcast, that is the question!

    University essay from Linköpings universitet/Kommunikationssystem

    Author : Martin Dahl; [2023]
    Keywords : Decentralized Stochastic Gradient Descent; Decentralized Learning; Medium Access Control; Wireless Communications; Machine Learning; Imperfect Communication; Resource-Constrained; Resource Allocation; Scheduling;

    Abstract : The ever-expanding volume of data generated by network devices such as smartphones, personal computers, and sensors has significantly contributed to the remarkable advancements in artificial intelligence (AI) and machine learning (ML) algorithms. However, effectively processing and learning from this extensive data usually requires substantial computational capabilities centralized in a server. READ MORE

  3. 3. Highly Available Task Scheduling in Distinctly Branched Directed Acyclic Graphs

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Patrik Zhong; [2023]
    Keywords : Distributed Scheduling; Fault-tolerance; Graph Partitioning; Task Graphs; Dask; Dask Distributed; Data Processing; Distribuerad Schemaläggning; Feltolerans; Grafpartitionering; Uppgiftsgrafer; Dask; Dask Distributed; Dataprocessering;

    Abstract : Big data processing frameworks utilizing distributed frameworks to parallelize the computing of datasets have become a staple part of the data engineering and data science pipelines. One of the more known frameworks is Dask, a widely utilized distributed framework used for parallelizing data processing jobs. READ MORE

  4. 4. Efficient Resource Scheduling for Distributed Infrastructures using Negotiation Capabilitie

    University essay from Uppsala universitet/Institutionen för informationsteknologi

    Author : Junjie Chu; [2022]
    Keywords : ;

    Abstract : In the past few years, the rapid development of information and internet technology has spawned massive amounts of data and information. The explosion of information drives many enterprises or individuals to seek to rent cloud computing infrastructure to put their applications in the cloud. READ MORE

  5. 5. Energy Efficient Communication Scheduling for IoT-based Waterbirds Monitoring: Decentralized Strategies

    University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Author : Otabek Sobirov; [2022]
    Keywords : TSCH; 6TiSCH; RPL; scheduling; energy consumption; COOJA; autonomous scheduling; distributed scheduling; reinforcement learning; RL-based scheduling; Q-Learning;

    Abstract : Monitoring waterbirds have several benefits, including analyzing the number of endangered species, giving a reliable indication of public health, etc. Monitoring waterbirds in their habitat is a challenging task since the location is distant, and the collection of monitoring data requires large bandwidth. READ MORE