Nothing Special   »   [go: up one dir, main page]

Abbasi et al., 2019 - Google Patents

A calibrated asymptotic framework for analyzing packet classification algorithms on GPUs

Abbasi et al., 2019

Document ID
15046925650444611522
Author
Abbasi M
Rafiee M
Publication year
Publication venue
The Journal of Supercomputing

External Links

Snippet

Packet classification is a computationally intensive, highly parallelizable task in many advanced network systems like high-speed routers and firewalls. Recently, graphics processing units (GPUs) have been exploited as efficient accelerators for parallel …
Continue reading at link.springer.com (other versions)

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
    • G06F9/5066—Algorithms for mapping a plurality of inter-dependent sub-tasks onto a plurality of physical CPUs
    • 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
    • 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
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30943—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type
    • G06F17/30946—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type indexing structures
    • G06F17/30961—Trees
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/16—Combinations of two or more digital computers each having at least an arithmetic unit, a programme unit and a register, e.g. for a simultaneous processing of several programmes
    • G06F15/163—Interprocessor communication
    • G06F15/173—Interprocessor communication using an interconnection network, e.g. matrix, shuffle, pyramid, star, snowflake
    • 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
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30312—Storage and indexing structures; Management thereof
    • G06F17/30321—Indexing structures
    • 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
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/76—Architectures of general purpose stored programme computers
    • G06F15/78—Architectures of general purpose stored programme computers comprising a single central processing unit
    • 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
    • G06F17/10—Complex mathematical operations
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/40—Transformations of program code
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/70—Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds
    • G06F19/701—Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds for molecular modelling, e.g. calculation and theoretical details of quantum mechanics, molecular mechanics, molecular dynamics, Monte Carlo methods, conformational analysis or the like

Similar Documents

Publication Publication Date Title
Abbasi et al. A calibrated asymptotic framework for analyzing packet classification algorithms on GPUs
Karloff et al. A model of computation for MapReduce
Sarıyüce et al. Regularizing graph centrality computations
US9053067B2 (en) Distributed data scalable adaptive map-reduce framework
Liu et al. Fast synchronization‐free algorithms for parallel sparse triangular solves with multiple right‐hand sides
Li et al. A fine-grained parallel multi-objective test case prioritization on GPU
Xia et al. A high-performance cellular automata model for urban simulation based on vectorization and parallel computing technology
Abbasi et al. Enhancing the performance of the aggregated bit vector algorithm in network packet classification using GPU
Abbasi et al. Efficient flow processing in 5G-envisioned SDN-based internet of vehicles using GPUs
Canny et al. Machine learning at the limit
Stone et al. Early experiences porting the NAMD and VMD molecular simulation and analysis software to GPU-accelerated OpenPOWER platforms
Alam et al. Novel parallel algorithms for fast multi-GPU-based generation of massive scale-free networks
Shen et al. GPU‐based branch‐and‐bound method to solve large 0‐1 knapsack problems with data‐centric strategies
Abbasi et al. High-performance flow classification using hybrid clusters in software defined mobile edge computing
Li et al. Scalable Graph500 design with MPI-3 RMA
Meyer et al. Generating massive scale-free networks under resource constraints
Burchard et al. ipug: Accelerating breadth-first graph traversals using manycore graphcore ipus
Speck et al. Towards a petascale tree code: Scaling and efficiency of the PEPC library
Shirahata et al. A scalable implementation of a mapreduce-based graph processing algorithm for large-scale heterogeneous supercomputers
Lv et al. Understanding parallelism in graph traversal on multi-core clusters
Ryczkowska et al. The performance evaluation of the Java implementation of Graph500
Zhang et al. Fsgraph: fast and scalable implementation of graph traversal on gpus
Afanasyev et al. The comparison of large-scale graph processing algorithms implementation methods for Intel KNL and NVIDIA GPU
Javed et al. Performance analysis of deep learning workloads using roofline trajectories
Amestoy et al. Modeling 1D distributed-memory dense kernels for an asynchronous multifrontal sparse solver