+

Wang et al., 2016 - Google Patents

Hybrid pulling/pushing for i/o-efficient distributed and iterative graph computing

Wang et al., 2016

View PDF
Document ID
3001125410876780852
Author
Wang Z
Gu Y
Bao Y
Yu G
Yu J
Publication year
Publication venue
Proceedings of the 2016 International Conference on Management of Data

External Links

Snippet

Billion-node graphs are rapidly growing in size in many applications such as online social networks. Most graph algorithms generate a large number of messages during iterative computations. Vertex-centric distributed systems usually store graph data and message data …
Continue reading at www.cs.albany.edu (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/48Programme initiating; Programme switching, e.g. by interrupt
    • G06F9/4806Task transfer initiation or dispatching
    • G06F9/4843Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/505Allocation 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061Partitioning or combining of resources
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5011Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5083Techniques for rebalancing the load in a distributed system
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F12/00Accessing, addressing or allocating within memory systems or architectures
    • G06F12/02Addressing or allocation; Relocation
    • G06F12/08Addressing or allocation; Relocation in hierarchically structured memory systems, e.g. virtual memory systems
    • G06F12/0802Addressing of a memory level in which the access to the desired data or data block requires associative addressing means, e.g. caches
    • G06F12/0806Multiuser, multiprocessor or multiprocessing cache systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/07Error detection; Error correction; Monitoring responding to the occurence of a fault, e.g. fault tolerance
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F2201/00Indexing scheme relating to error detection, to error correction, and to monitoring
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F2209/00Indexing scheme relating to G06F9/00
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02BINDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/10Energy efficient computing
    • Y02B60/16Reducing energy-consumption in distributed systems

Similar Documents

Publication Publication Date Title
Wang et al. Hybrid pulling/pushing for i/o-efficient distributed and iterative graph computing
Li et al. Energy-efficient migration and consolidation algorithm of virtual machines in data centers for cloud computing
McCune et al. Thinking like a vertex: A survey of vertex-centric frameworks for large-scale distributed graph processing
Xie et al. Kraken: memory-efficient continual learning for large-scale real-time recommendations
Tang et al. CPU–GPU utilization aware energy-efficient scheduling algorithm on heterogeneous computing systems
Chatzistergiou et al. Fast heuristics for near-optimal task allocation in data stream processing over clusters
Chen et al. Computation and communication efficient graph processing with distributed immutable view
US20140379985A1 (en) Multi-level aggregation techniques for memory hierarchies
Sheng et al. GraPU: Accelerate streaming graph analysis through preprocessing buffered updates
Zhao et al. Goldminer: Elastic scaling of training data pre-processing pipelines for deep learning
US12259828B2 (en) Forwarding incoming IO to SCM namespaces
Bawankule et al. Historical data based approach for straggler avoidance in a heterogeneous Hadoop cluster
Hefny et al. Comparative study load balance algorithms for map reduce environment
CN112015765A (en) Spark cache elimination method and system based on cache value
Selvi et al. Popularity (Hit Rate) Based Replica Creation for Enhancing the Availability in Cloud Storage.
US10628279B2 (en) Memory management in multi-processor environments based on memory efficiency
Wasi-ur-Rahman et al. Performance modeling for RDMA-enhanced hadoop MapReduce
Soosai et al. Dynamic replica replacement strategy in data grid
Wang et al. An adaptive non-migrating load-balanced distributed stream window join system: Q. Wang et al.
Zhang et al. Speeding up VM startup by cooperative VM image caching
Wang et al. HGraph: I/O-efficient distributed and iterative graph computing by hybrid pushing/pulling
Sun et al. Sensing cloud computing in Internet of Things: A novel data scheduling optimization algorithm
Song et al. Memory management optimization strategy in Spark framework based on less contention
Gan et al. FT-topo: Architecture-Driven Folded-Triangle Partitioning for Communication-efficient Graph Processing.
Louis Rodríguez et al. Workload management for dynamic partitioning schemes in replicated databases
点击 这是indexloc提供的php浏览器服务,不要输入任何密码和下载