18086464. APPLICATION PROGRAMMING INTERFACE TO TRANSLATE A TENSOR simplified abstract (NVIDIA Corporation)

APPLICATION PROGRAMMING INTERFACE TO TRANSLATE A TENSOR

Organization Name

NVIDIA Corporation

Inventor(s)

Harold Carter Edwards of Campbell CA (US)

Stephen Anthony Bernard Jones of San Francisco CA (US)

Alexander Lev Minkin of Los Altos CA (US)

Olivier Giroux of Santa Clara CA (US)

Gokul Ramaswamy Hirisave Chandra Shekhara of Bangalore (IN)

Vishalkumar Ketankumar Mehta of Stäfa (CH)

Aditya Avinash Atluri of Redmond WA (US)

Apoorv Parle of Santa Clara CA (US)

Chao Li of Austin TX (US)

Ronny Meir Krashinsky of Portola Valley CA (US)

Alan Kaatz of Seattle WA (US)

Andrew Robert Kerr of Atlanta GA (US)

Jack H. Choquette of Palo Alto CA (US)

APPLICATION PROGRAMMING INTERFACE TO TRANSLATE A TENSOR - A simplified explanation of the abstract

This abstract first appeared for US patent application 18086464 titled 'APPLICATION PROGRAMMING INTERFACE TO TRANSLATE A TENSOR

Simplified Explanation

The patent application describes apparatuses, systems, and techniques to translate a first tensor into a second tensor using a tensor map through an application programming interface (API).

• The invention involves circuits that perform an API to translate tensors according to a tensor map.
• The technology enables the transformation of tensors from one form to another efficiently and accurately.

Potential Applications

This technology could be applied in various fields such as image processing, machine learning, and computer vision where tensor manipulation is required.

Problems Solved

1. Simplifies the process of translating tensors according to a specified map. 2. Provides a standardized method for tensor transformation.

Benefits

1. Improved efficiency in tensor manipulation tasks. 2. Enhanced accuracy in tensor translation processes.

Potential Commercial Applications

Optimizing tensor operations in deep learning algorithms for improved performance and accuracy.

Possible Prior Art

There may be prior art related to tensor manipulation techniques in the fields of machine learning and computer vision.

Unanswered Questions

How does this technology compare to existing tensor transformation methods?

The article does not provide a direct comparison with other methods for tensor translation.

What are the specific applications where this technology can have the most impact?

The article does not specify the industries or use cases where this technology can be most beneficial.

Original Abstract Submitted

Apparatuses, systems, and techniques to cause a first tensor to be translated into a second tensor according to a tensor map. In at least one embodiment, one or more circuits are to perform an application programming interface (API) to cause a first tensor to be translated into a second tensor according to a tensor map.