High level neuromorphic network description apparatus and methods
First Claim
1. A computer realized method of implementing a neural network using an instruction set, the method comprising:
- providing a representation of the neural network, the representation comprising a plurality of instructions of said instruction set; and
compiling said representation into to machine executable format;
wherein the instruction set comprises a structured language configured consistent with English language structure and grammar.
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Abstract
Apparatus and methods for high-level neuromorphic network description (HLND) framework that may be configured to enable users to define neuromorphic network architectures using a unified and unambiguous representation that is both human-readable and machine-interpretable. The framework may be used to define nodes types, node-to-node connection types, instantiate node instances for different node types, and to generate instances of connection types between these nodes. To facilitate framework usage, the HLND format may provide the flexibility required by computational neuroscientists and, at the same time, provides a user-friendly interface for users with limited experience in modeling neurons. The HLND kernel may comprise an interface to Elementary Network Description (END) that is optimized for efficient representation of neuronal systems in hardware-independent manner and enables seamless translation of HLND model description into hardware instructions for execution by various processing modules.
140 Citations
33 Claims
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1. A computer realized method of implementing a neural network using an instruction set, the method comprising:
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providing a representation of the neural network, the representation comprising a plurality of instructions of said instruction set; and compiling said representation into to machine executable format; wherein the instruction set comprises a structured language configured consistent with English language structure and grammar. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A method of programming a computerized apparatus, comprising:
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representing a neural network using a plurality of instructions of an instruction set; and compiling said representation into to machine representation for execution by said computerized apparatus; wherein the instruction set comprises a structured language configured consistent with English language structure and grammar. - View Dependent Claims (16, 17, 18, 19, 20, 21)
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22. A method of operating a neuromorphic computerized apparatus comprising a nonvolatile storage medium storing an instruction set, compiling kernel, and processing module, the method comprising:
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providing a representation of a neural network to the processing module, the representation comprising a plurality of instructions of said instruction set; and encoding said representation into hardware independent format by the processing module using said kernel; wherein the instruction set comprises a structured language configured consistent with English language structure and grammar. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29, 30, 31, 32)
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33. A system configured to implement a neural network using an instruction set, the system comprising:
one or more processors configured to execute one or more computer program modules, wherein execution of individual ones of the one or more computer program modules causes the one or more processors to; provide a representation of the neural network, the representation comprising a plurality of instructions of the instruction set, the instruction set comprising a structured language configured consistent with English language structure and grammar; and compile the representation into to machine executable format.
Specification