Intel corporation (20240329938). MATRIX TRANSPOSE AND MULTIPLY simplified abstract

MATRIX TRANSPOSE AND MULTIPLY

Organization Name

intel corporation

Inventor(s)

Menachem Adelman of Modi'in (IL)

Robert Valentine of Kiryat Tivon (IL)

Barukh Ziv of Haifa (IL)

Amit Gradstein of Binyamina (IL)

Simon Rubanovich of Haifa (IL)

Zeev Sperber of Zichron Yackov (IL)

Mark J. Charney of Lexington MA (US)

Christopher J. Hughes of Santa Clara CA (US)

Alexander F. Heinecke of San Jose CA (US)

Evangelos Georganas of San Jose CA (US)

Binh Pham of Burlingame CA (US)

MATRIX TRANSPOSE AND MULTIPLY - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240329938 titled 'MATRIX TRANSPOSE AND MULTIPLY

Simplified Explanation

The patent application describes a method for transposing and multiplying matrices using a processor.

• The processor decodes an instruction with specific fields to identify the operation to be performed.
• It transposes one matrix, multiplies it with another matrix, and stores the result in a specified location.

Key Features and Innovation

• Processor with decoder and execution circuitry for matrix transpose and multiply operation.
• Instruction format includes opcode, destination, and source matrix locations.
• Transposes one matrix, multiplies it with another, and stores the result in a specified location.

Potential Applications

• Scientific computing
• Image processing
• Machine learning algorithms

Problems Solved

• Efficient matrix operations
• Simplified matrix manipulation
• Streamlined data processing

Benefits

• Faster matrix calculations
• Reduced computational complexity
• Improved performance in matrix-based applications

Commercial Applications

1. 1. 1. Matrix Transpose and Multiply Processor: Revolutionizing Matrix Operations in Scientific Computing

Prior Art

Research in matrix operations and parallel processing technologies could provide insights into similar methods.

Frequently Updated Research

Stay updated on advancements in matrix processing algorithms and hardware acceleration techniques.

Questions about Matrix Transpose and Multiply Operation

How does this innovation improve matrix calculations in comparison to traditional methods?

The innovation streamlines the process by combining transpose and multiply operations in a single step, reducing computational overhead.

What are the potential implications of this technology in the field of machine learning?

This technology can enhance the efficiency of matrix-based computations in machine learning algorithms, leading to faster training and inference times.

Original Abstract Submitted

embodiments for a matrix transpose and multiply operation are disclosed. in an embodiment, a processor includes a decoder and execution circuitry. the decoder is to decode an instruction having a format including an opcode field to specify an opcode, a first destination operand field to specify a destination matrix location, a first source operand field to specify a first source matrix location, and a second source operand field to specify a second source matrix location. the execution circuitry is to, in response to the decoded instruction, transpose the first source matrix to generate a transposed first source matrix, perform a matrix multiplication using the transposed first source matrix and the second source matrix to generate a result, and store the result in a destination matrix location.