PATENT CLAIM ANALYSIS

Application Number: 15949150
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-10
Patent Classification: ["717", "126000"]

Abstract:
The disclosure provides a compilation method and system for heterogeneous computing platform, and a runtime method and system for supporting program execution on the heterogeneous computing platform. Inputting a trained neural network model to a Neural Network (NN) optimizing compiler to generate an NN assembly file corresponding to the neural network; inputting the NN assembly file to an NN assembler to generate an NN binary file corresponding to the neural network; compilation and assembling a neural network application developed by users in a high-level language using a host compiler toolchain to generate a corresponding host assembly file and a host binary file in sequence; and linking the NN binary file and the host binary file using a host linker to generate a single hybrid linking executable file. The technical solution of the present disclosure has the advantages such as good computing performance, strong scalability, strong compatibility and high flexibility.

Claim (Index 9):
The method of  claim 6 , wherein the first set of object codes is in the Executable and Linkable Format (ELF) format; or wherein the second set of object codes is in the ELF format.

Metadata:
- Claim Count in Document: 8.0
- Percentile: 91.0
- Lexical Diversity: 2.16216
- Patent Class: 717.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['14197576', '14931071', '12242662', '15894866', '14501873']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3951103294202024
- 35 USC 102 Novelty (BERT): 0.4885288483381877
- Combined Prediction Score: 0.404452181312001
- Mean Citation Score: 164.09254600000003
- Max Citation Score: 173.71465
- Similarity Product: 128.28075171012878

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