[go: up one dir, main page]

Deprit, 1989 - Google Patents

Implementing recurrent back-propagation on the Connection Machine

Deprit, 1989

Document ID
12641491266391986133
Author
Deprit E
Publication year
Publication venue
Neural Networks

External Links

Snippet

The recurrent back-propagation algorithm for neural networks has been implemented on the Connection Machine, a massively parallel processor. Two fundamentally different graph architectures underlying the nets were tested: one based on arcs, the other on nodes …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • 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
    • G06F15/80—Architectures of general purpose stored programme computers comprising an array of processing units with common control, e.g. single instruction multiple data processors
    • G06F15/8007—Architectures of general purpose stored programme computers comprising an array of processing units with common control, e.g. single instruction multiple data processors single instruction multiple data [SIMD] multiprocessors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/04—Architectures, e.g. interconnection topology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • 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
    • G06F15/17356—Indirect interconnection networks
    • G06F15/17368—Indirect interconnection networks non hierarchical topologies
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/08—Learning methods
    • G06N3/082—Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
    • 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
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/10—Simulation on general purpose computers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/12—Computer systems based on biological models using genetic models
    • G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
    • 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
    • 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
    • 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
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring

Similar Documents

Publication Publication Date Title
Deprit Implementing recurrent back-propagation on the Connection Machine
Ghosh et al. Mapping neural networks onto message-passing multicomputers
CN106650922B (en) Hardware neural network conversion method, computing device, and software-hardware cooperation system
Lehmann et al. A generic systolic array building block for neural networks with on-chip learning
Zhang et al. The backpropagation algorithm on grid and hypercube architectures
Sitkoff et al. Implementing a genetic algorithm on a parallel custom computing machine
Tufte et al. Towards development on a silicon-based cellular computing machine
Koza et al. Evolving computer programs using rapidly reconfigurable field-programmable gate arrays and genetic programming
Jin et al. Timing for Associative Operations on the MASC Model.
Watanabe et al. Neural network simulation on a massively parallel cellular array processor: AAP-2
Sudhakar et al. Efficient mapping of backpropagation algorithm onto a network of workstations
WO2023214608A1 (en) Quantum circuit simulation hardware
WO2023214609A1 (en) Quantum circuit computation method for efficiently computing state vectors
Tomboulian Introduction to a system for implementing Neural Net connections on SIMD architectures
Saratchandran et al. Parallel Implementations of Backpropagation Neural Networks on Transputers: A Study of Training Set Parallelism
d'Acierno Back-propagation learning algorithm and parallel computers: The CLEPSYDRA mapping scheme
Deprit Implementing Recurrent Back-Propagation on the Connection Machine.
Paschke et al. Simulation of sparse random networks on a CNAPS SIMD neurocomputer
Rothstein Toward pattern-recognizing visual prostheses
Faure et al. Implementation of back-propagation on a VLSI asynchronous cellular architecture
Ghosh et al. Optically connected multiprocessors for simulating artificial neural networks
Vellasco A VLSI architecture for neural network chips
Krikelis et al. Implementing neural networks with the associative string processor
Duderstadt Topology and routing issues for partitioning neural networks on parallel MIMD computers
Downing Developmental models for emergent computation