PATENT CLAIM ANALYSIS

Application Number: 15870081
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-05
Patent Classification: ["345", "419000"]

Abstract:
Techniques are disclosed relating to texture sampling operations. In some embodiments, multi-fetch sampling instructions specify a region of a texture in which multiple samples are to be performed and texture processing circuitry is configured to sample the texture multiple times within the region. In some embodiments, the locations of the samples are determined according to a formula, which may be pseudo-random. In some embodiments, the locations of the samples are jittered to produce stochastic results. In some embodiments, the locations of the samples are determined based on one or more stored sets of samples that have particular properties (e.g., blue noise, in some embodiments). In various embodiments, disclosed techniques may facilitate Monte Carlo sampling.

Claim (Index 1):
An apparatus, comprising:\n decode circuitry configured to process a graphics instruction that specifies a number of samples to be performed and includes region information that specifies a region of a texture; texture processing circuitry configured to, in response to the graphics instruction:\n determine a plurality of sample locations within the specified region of the texture; \n sample the texture at the plurality of sample locations, including, for multiple ones of the sample locations, performing filtering to determine a sample output for the sample location based on multiple texels near the sample location; and \n provide sample outputs for the sample locations for processing based on one or more other instructions in a graphics program that includes the graphics instruction.

Metadata:
- Claim Count in Document: 34.0
- Percentile: 86.0
- Lexical Diversity: 2.0
- Patent Class: 345.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15018252', '14803926', '14482828', '15388804', '15625723']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6504516304840533
- 35 USC 102 Novelty (BERT): 0.5065466050641017
- Combined Prediction Score: 0.6360611279420582
- Mean Citation Score: 199.81964
- Max Citation Score: 303.4378
- Similarity Product: 274.6634878184676

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

Dataset: test