18399014. SYSTEMS FOR PERFORMING INSTRUCTIONS TO QUICKLY CONVERT AND USE TILES AS 1D VECTORS simplified abstract (Intel Corporation)

SYSTEMS FOR PERFORMING INSTRUCTIONS TO QUICKLY CONVERT AND USE TILES AS 1D VECTORS

Organization Name

Intel Corporation

Inventor(s)

Bret Toll of Hillsboro OR (US)

Christopher J. Hughes of Santa Clara CA (US)

Dan Baum of Haifa (IL)

Elmoustapha Ould-ahmed-vall of Gilbert AZ (US)

Raanan Sade of Portland OR (US)

Robert Valentine of Kiryat Tivon (IL)

Mark J. Charney of Lexington MA (US)

Alexander F. Heinecke of San Jose CA (US)

SYSTEMS FOR PERFORMING INSTRUCTIONS TO QUICKLY CONVERT AND USE TILES AS 1D VECTORS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18399014 titled 'SYSTEMS FOR PERFORMING INSTRUCTIONS TO QUICKLY CONVERT AND USE TILES AS 1D VECTORS

Simplified Explanation

The disclosed embodiments relate to systems for quickly converting and using matrices as one-dimensional vectors. In one example, a processor fetches an instruction with fields specifying an opcode, locations of a 2D matrix and a 1D vector, and a group of elements from the matrix. The opcode indicates a move of the specified group between the 2D matrix and the 1D vector. Decode circuitry decodes the fetched instruction, and execution circuitry moves contents of the specified 1D vector to the specified group of elements when the opcode specifies a move from 1D.

• Processor fetches instruction with opcode, matrix and vector locations, and group of elements
• Opcode indicates move of group between 2D matrix and 1D vector
• Decode circuitry decodes instruction
• Execution circuitry moves contents of 1D vector to specified group when opcode specifies move from 1D

Potential Applications

This technology could be applied in:

• Image processing
• Machine learning algorithms
• Data compression techniques

Problems Solved

This technology helps in:

• Efficiently converting and using matrices as vectors
• Streamlining data manipulation processes
• Enhancing computational performance

Benefits

The benefits of this technology include:

• Faster data processing
• Improved memory utilization
• Simplified matrix operations

Potential Commercial Applications

This technology could be commercially applied in:

• Computer vision systems
• Robotics
• Financial modeling software

Possible Prior Art

One possible prior art could be:

• Existing matrix manipulation algorithms
• Traditional methods for converting matrices to vectors

How does this technology compare to existing matrix manipulation techniques?

This technology offers a more efficient way to convert and use matrices as vectors compared to traditional methods. It streamlines the process and enhances computational performance.

What impact could this technology have on machine learning algorithms?

This technology could significantly improve the efficiency and speed of machine learning algorithms by optimizing the manipulation of matrices and vectors, leading to faster training and inference times.

Original Abstract Submitted

Disclosed embodiments relate to systems for performing instructions to quickly convert and use matrices (tiles) as one-dimensional vectors. In one example, a processor includes fetch circuitry to fetch an instruction having fields to specify an opcode, locations of a two-dimensional (2D) matrix and a one-dimensional (1D) vector, and a group of elements comprising one of a row, part of a row, multiple rows, a column, part of a column, multiple columns, and a rectangular sub-tile of the specified 2D matrix, and wherein the opcode is to indicate a move of the specified group between the 2D matrix and the 1D vector, decode circuitry to decode the fetched instruction; and execution circuitry, responsive to the decoded instruction, when the opcode specifies a move from 1D, to move contents of the specified 1D vector to the specified group of elements.