Nvidia Corporation Patent Portfolio Statistics

Nvidia Corporation

Profile Summary

This article summarizes the perfomance of the assignee in the recent years. The overall statistics for this portfolio help to analyze the areas where the assignee is performing well. The filing trend, perfomance across the tech centers and the perfomance of the recent applications has been mentioned below. All the stats are calculated based on the perfomance in USPTO.

How does the overall patent portfolio of Nvidia Corporation look like?

Assignee Art Units
Total Applications: 4,838 1,674,220
Granted Patents: 3,702 1,055,712
Grant Index 87.31% 80.45%
Abandoned/Rejected Applications: 538 (12.69%) 256,618 (19.55%)
In-Process Applications: 574 361,890
Average Grant Time: 3.96 Years 2.84 Years
Average Office Actions: 2.51 1.58

Which Technology Area Nvidia Corporation is filing most patents in? (Last 10 years)

Art Unit Definition Total Applications
2628 Selective Visual Display Systems 435
2611 Computer Graphic Processing, 3D Animation, Display Color Attribute, Object Processing, Hardware and Memory 196
Opap Parked GAU 196
2612 Computer Graphic Processing, 3D Animation, Display Color Attribute, Object Processing, Hardware and Memory 149
2183 Computer Architecture and I/O 133

How many patents are Nvidia Corporation filing every year?

Year Total Applications Predicted
2022 0* 502
2021 129* 571
2020 356 503
2019 267 267
2018 155
2017 70
2016 72
2015 143
2014 157
2013 598

*The drop in the number of applications filed in last two years compared to previous years is because applications can take up to 18 months to get published

Recently filed patent applications of Nvidia Corporation in USPTO?

Publication number: None
Application number: 17/665,297

Abstract:


Publication date:
Applicant: Nvidia Corporation
Inventors: Saxena Siddharth


Publication number: US20220100928A1
Application number: 17/549,529

Abstract:
Modeling contact between two or more objects (such as a robotic arm placing a block on a stack of blocks) or articulations of a series of linked joints (such as modeling a backhoe) in a real-time computing application can introduce additional energy into the system or fail to resolve a constraint imposed on the system. Current techniques attempt to resolve these issues, for example, by using very small time steps. Very small time steps, however, can significantly increase computational costs of the modeling simulation. The introduced simulation techniques for rigid bodies use a time interval to reduce linearization artifacts due to the small time steps and reduce computational costs with faster solver convergence by permitting more efficient bias calculations. High mass handling can also be improved through the more efficient bias calculations.

Publication date: 2022-03-31
Applicant: Nvidia Corporation
Inventors: Fengyun Lu


Publication number: US20220189114A1
Application number: 17/548,038

Abstract:
Systems and methods are provided to perform constrained BSDF sampling in relation to various algorithms, and specifically in relation to ray tracing algorithms. In some embodiments, a method is provided to generate samples by: determining a spherical polygon on a unit hemisphere; determining, on a unit circle, a projected area corresponding to the spherical polygon on the unit hemisphere; determining a parameterization of the projected area of the spherical polygon on the unit circle; generating samples in the projected area based on the parameterization; and generating samples in the spherical polygon. The unit circle is abase of the unit hemisphere, and the projection of the projected area is along a vector perpendicular to the unit circle. The generated samples in the spherical polygon correspond to the samples in the projected area. The method may further include evaluating a rendering equation based on the generated samples in the spherical polygon.

Publication date: 2022-06-16
Applicant: Nvidia Corporation
Inventors: Aizenshtein Maksim


How are Nvidia Corporation’s applications performing in USPTO?

Application Number Title Status Art Unit Examiner
17/665,297 Distributed Digital Low-Dropout Voltage Micro Regulator Docketed New Case – Ready for Examination 3992 Bonshock, Dennis G
17/549,529 Techniques For Simulating Objects Interacting In A Real-Time Computing Application Docketed New Case – Ready for Examination OPAP Central, Docket
17/548,038 Constrained Bsdf Sampling OPAP Central, Docket
17/543,098 Video Upsampling Using One Or More Neural Networks Docketed New Case – Ready for Examination OPAP Central, Docket
17/543,075 Video Upsampling Using One Or More Neural Networks Docketed New Case – Ready for Examination OPAP Central, Docket