Intel corporation (20240134644). SYSTEMS, METHODS, AND APPARATUSES FOR MATRIX ADD, SUBTRACT, AND MULTIPLY simplified abstract

SYSTEMS, METHODS, AND APPARATUSES FOR MATRIX ADD, SUBTRACT, AND MULTIPLY

Organization Name

intel corporation

Inventor(s)

Robert Valentine of Kiryat Tivon (IL)

Dan Baum of Haifa (IL)

Zeev Sperber of Zichron Yaakov (IL)

Jesus Corbal of King City OR (US)

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

Bret L. Toll of Hillsboro OR (US)

Mark J. Charney of Lexington MA (US)

Barukh Ziv of Haifa (IL)

Alexander Heinecke of San Jose CA (US)

Milind Girkar of Sunnyvale CA (US)

Simon Rubanovich of Haifa (IL)

SYSTEMS, METHODS, AND APPARATUSES FOR MATRIX ADD, SUBTRACT, AND MULTIPLY - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240134644 titled 'SYSTEMS, METHODS, AND APPARATUSES FOR MATRIX ADD, SUBTRACT, AND MULTIPLY

Simplified Explanation

The abstract describes a patent application related to matrix operations, specifically focusing on support for matrix (tile) addition, subtraction, and multiplication. The circuitry detailed in the patent supports instructions for element-by-element matrix (tile) operations.

• Matrix operations circuitry for addition, subtraction, and multiplication
• Support for element-by-element matrix (tile) operations
• Decode circuitry for matrix addition instructions
• Execution circuitry for performing matrix addition at each data element position

Potential Applications

The technology described in the patent application could be applied in various fields such as:

• Image processing
• Signal processing
• Machine learning algorithms
• Scientific computing

Problems Solved

The technology addresses the following issues:

• Efficient matrix operations
• Simplified implementation of matrix addition, subtraction, and multiplication
• Improved performance in processing large datasets

Benefits

The benefits of this technology include:

• Faster computation of matrix operations
• Reduced complexity in implementing matrix operations
• Enhanced performance in handling large matrices

Potential Commercial Applications

The technology could find commercial applications in:

• High-performance computing systems
• Data centers
• Artificial intelligence hardware accelerators

Possible Prior Art

One possible prior art in this field is the use of specialized hardware for matrix operations in graphics processing units (GPUs) and application-specific integrated circuits (ASICs).

How does this technology compare to existing matrix operation implementations?

The article does not provide a direct comparison with existing matrix operation implementations. It would be helpful to understand the specific advantages and disadvantages of this technology compared to current solutions.

What impact could this technology have on the performance of machine learning algorithms?

The article does not delve into the potential impact of this technology on the performance of machine learning algorithms. Understanding how this innovation could enhance the efficiency and speed of machine learning processes would be valuable information for researchers and developers in the field.

Original Abstract Submitted

embodiments detailed herein relate to matrix operations. in particular, support for matrix (tile) addition, subtraction, and multiplication is described. for example, circuitry to support instructions for element-by-element matrix (tile) addition, subtraction, and multiplication are detailed. in some embodiments, for matrix (tile) addition, decode circuitry is to decode an instruction having fields for an opcode, a first source matrix operand identifier, a second source matrix operand identifier, and a destination matrix operand identifier; and execution circuitry is to execute the decoded instruction to, for each data element position of the identified first source matrix operand: add a first data value at that data element position to a second data value at a corresponding data element position of the identified second source matrix operand, and store a result of the addition into a corresponding data element position of the identified destination matrix operand.