PATENT CLAIM ANALYSIS

Application Number: 16071458
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2019-01
Patent Classification: ["365", "230030"]

Abstract:
The present invention is directed to the storage technical field and discloses an on-chip data partitioning read-write method, the method comprises: a data partitioning step for storing on-chip data in different areas, and storing the on-chip data in an on-chip storage medium and an off-chip storage medium respectively, based on a data partitioning strategy; a pre-operation step for performing an operational processing of an on-chip address index of the on-chip storage data in advance when implementing data splicing; and a data splicing step, for splicing the on-chip storage data and the off-chip input data to obtain a representation of the original data based on a data splicing strategy. Also provided are a corresponding on-chip data partitioning read-write system and device. Thus, read and write of repeated data can be efficiently realized, reducing memory access bandwidth requirements while providing good flexibility, thus reducing on-chip storage overhead.

Claim (Index 3):
The on-chip data partitioning read-write method according to  claim 2 , wherein the data storing step further comprising:\n indexing the on-chip storage data according to the on-chip address index; outputting indexed data to an exit; writing the data to be stored into corresponding storage positions based on writing addresses.

Metadata:
- Claim Count in Document: 38.0
- Percentile: 95.0
- Lexical Diversity: 2.07895
- Patent Class: 365.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['16070735', '11966009', '11164407', '10012257', '13876843']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7731490803327219
- 35 USC 102 Novelty (BERT): 0.4878696119143439
- Combined Prediction Score: 0.7446211334908842
- Mean Citation Score: 163.481968
- Max Citation Score: 228.38171
- Similarity Product: 160.79398165161254

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

Dataset: test