Apple inc. (20240103858). Instruction Support for Matrix Multiplication simplified abstract
Contents
- 1 Instruction Support for Matrix Multiplication
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Instruction Support for Matrix Multiplication - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
Instruction Support for Matrix Multiplication
Organization Name
Inventor(s)
Ali Sazegari of Los Altos CA (US)
Matthew L. Badin of Santa Clara CA (US)
Instruction Support for Matrix Multiplication - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240103858 titled 'Instruction Support for Matrix Multiplication
Simplified Explanation
The patent application describes techniques for instruction set architecture support for matrix manipulations, including fetching and decoding matrix multiply instructions, mapping vector registers to matrix operands, and operating front-end circuitry in reduced-power mode during execution.
- Front-end circuitry fetches and decodes matrix multiply instructions.
- Datapath circuitry executes matrix multiply instructions by mapping vector registers to matrix operands.
- Power management circuitry operates front-end circuitry in reduced-power mode during instruction execution.
Potential Applications
The technology can be applied in:
- High-performance computing
- Signal processing
- Machine learning algorithms
Problems Solved
The technology addresses issues such as:
- Increasing throughput in matrix manipulations
- Reducing power consumption in instruction execution
Benefits
The benefits of this technology include:
- Improved efficiency in matrix operations
- Lower power consumption during instruction execution
Potential Commercial Applications
Potential commercial applications include:
- Data centers
- Supercomputing clusters
- Embedded systems
Possible Prior Art
One possible prior art is the use of vector operations in traditional implementations for matrix manipulations.
Unanswered Questions
How does the reduced-power mode impact overall system performance?
The article does not provide specific details on the performance impact of operating front-end circuitry in reduced-power mode during instruction execution.
Are there any limitations to the size or complexity of matrices that can be manipulated using this technology?
The article does not address any potential limitations related to the size or complexity of matrices that can be handled efficiently with this technology.
Original Abstract Submitted
techniques are disclosed relating to instruction set architecture support for matrix manipulations. in disclosed embodiments, front-end circuitry is configured to fetch and decode a matrix multiply instruction for execution, including to encode a given matrix input operand of the matrix multiply instruction to identify one or more vector registers defined according to an instruction set architecture. in some embodiments, datapath circuitry is configured to execute the matrix multiply instruction, where during execution of the instruction, the one or more vector registers corresponding to the given matrix operand are mapped within the datapath circuitry to at least two dimensions of the given matrix operand. in some embodiments, power management circuitry is configured to, during execution of the instruction, operate at least a portion of the front-end circuitry in a reduced-power mode. disclosed techniques may advantageously increase throughput and reduce power consumption, relative to traditional implementations using vector operations.
