PATENT CLAIM ANALYSIS

Application Number: 15974643
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2019-11
Patent Classification: ["708", "445000"]

Abstract:
A system for block floating point computation in a neural network receives a plurality of floating point numbers. An exponent value for an exponent portion of each floating point number of the plurality of floating point numbers is identified and mantissa portions of the floating point numbers are grouped. A shared exponent value of the grouped mantissa portions is selected according to the identified exponent values and then removed from the grouped mantissa portions to define multi-tiered shared exponent block floating point numbers. One or more dot product operations are performed on the grouped mantissa portions of the multi-tiered shared exponent block floating point numbers to obtain individual results. The individual results are shifted to generate a final dot product value, which is used to implement the neural network. The shared exponent block floating point computations reduce processing time with less reduction in system accuracy.

Claim (Index 19):
The one or more computer storage media of  claim 16  having further computer-executable instructions that, upon execution by a processor, cause the processor to at least perform one or more dot product operations on only matrix-vector multiplies.

Metadata:
- Claim Count in Document: 48.0
- Percentile: 93.0
- Lexical Diversity: 2.23529
- Patent Class: 708.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15971904', '13534330', '13534552', '15592021', '13534389']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4445245178711519
- 35 USC 102 Novelty (BERT): 0.5152565186561291
- Combined Prediction Score: 0.4515977179496496
- Mean Citation Score: 263.145522
- Max Citation Score: 291.8286
- Similarity Product: 252.514225743556

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test