PATENT CLAIM ANALYSIS

Application Number: 16183603
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-03
Patent Classification: ["712", "008000"]

Abstract:
The present disclosure provides a data read-write scheduler and a reservation station for vector operations. The data read-write scheduler suspends the instruction execution by providing a read instruction cache module and a write instruction cache module and detecting conflict instructions based on the two modules. After the time is satisfied, instructions are re-executed, thereby solving the read-after-write conflict and the write-after-read conflict between instructions and guaranteeing that correct data are provided to a vector operations component. Therefore, the subject disclosure has more values for promotion and application.

Claim (Index 3):
The data write scheduler of  claim 1 , wherein the write instruction preprocessing unit is further configured to:\n select one from the one or more of the vector read instructions that overlap with the vector write instruction as the dependent vector read instruction, wherein the dependent vector read instruction is nearest to the vector write instruction in an instruction queue, and obtain an identification of the dependent vector read, and cache the vector write instruction, the first pair of the starting and ending addresses in the vector write instruction, and the identification of the dependent vector read instruction.

Metadata:
- Claim Count in Document: 3.0
- Percentile: 98.0
- Lexical Diversity: 1.64912
- Patent Class: 712.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['16183612', '16039605', '14335029', '12082971', '14575103']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6213670575059439
- 35 USC 102 Novelty (BERT): 0.571013463569624
- Combined Prediction Score: 0.6163316981123119
- Mean Citation Score: 299.440904
- Max Citation Score: 464.2825
- Similarity Product: 422.0132732379437

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

Dataset: test