SPIN: a sequential pipeline neurocomputer
First Claim
1. A sequential pipelined neural computer apparatus comprising:
- N Processing Elements (PEs), each including storage for a neuron value and for a PE tag, tag matching means for comparing a tag identifying a new neuron value with the PE tag, means for storing the new neuron value as the neuron value of the PE if the tag of the new neuron value matches the PE tag, and N-1 of the PEs having means for passing the new neuron value to a next one of the PEs if the tag identifying the new neuron value does not match the PE tag;
N weight storage units, each associated with a respective one of the PEs, and each storing a plurality of weight values;
N multipliers, each associated with a respective one of the weight storage units, and each for producing as an output the product of one of the weight values of said respective one of the weight storage units and the neuron value of said respective one of the PEs associated with said respective one of the weight storage units;
a summation tree for adding the outputs of the multipliers to produce a sum;
a neuron activation function generator, for receiving the sum and generating therefrom a new neuron value; and
means for communicating the generated neuron value from the generator to one of the PEs as the new neuron value.
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Abstract
A neural network architecture consisting of input weight multiplications, product summation, neural state calculations, and complete connectivity among the neuron processing elements. Neural networks are modelled using a sequential pipelined neurocomputer producing high performance with minimum hardware by sequentially processing each neuron in the completely connected network model. An N neuron network is implemented using multipliers, a pipelined adder tree structure, and activation functions. The activation functions are provided by using one activation function module and sequentially passing the N input product summations sequentially through it. One bus provides N×N communications by sequentially providing N neuron values to the multiplier registers. The neuron values are ensured of reaching corresponding multipliers through a tag compare function. The neuron information includes a source tag and a valid signal. Higher performance is provided by connecting a number of the neurocomputers in a parallel.
54 Citations
39 Claims
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1. A sequential pipelined neural computer apparatus comprising:
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N Processing Elements (PEs), each including storage for a neuron value and for a PE tag, tag matching means for comparing a tag identifying a new neuron value with the PE tag, means for storing the new neuron value as the neuron value of the PE if the tag of the new neuron value matches the PE tag, and N-1 of the PEs having means for passing the new neuron value to a next one of the PEs if the tag identifying the new neuron value does not match the PE tag; N weight storage units, each associated with a respective one of the PEs, and each storing a plurality of weight values; N multipliers, each associated with a respective one of the weight storage units, and each for producing as an output the product of one of the weight values of said respective one of the weight storage units and the neuron value of said respective one of the PEs associated with said respective one of the weight storage units; a summation tree for adding the outputs of the multipliers to produce a sum; a neuron activation function generator, for receiving the sum and generating therefrom a new neuron value; and means for communicating the generated neuron value from the generator to one of the PEs as the new neuron value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39)
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Specification