Intel corporation (20240160443). COMPLEX NUMBER MATRIX MULTIPLICATION PROCESSORS, METHODS, SYSTEMS, AND INSTRUCTIONS simplified abstract
Contents
- 1 COMPLEX NUMBER MATRIX MULTIPLICATION PROCESSORS, METHODS, SYSTEMS, AND INSTRUCTIONS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 COMPLEX NUMBER MATRIX MULTIPLICATION PROCESSORS, METHODS, SYSTEMS, AND INSTRUCTIONS - 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
COMPLEX NUMBER MATRIX MULTIPLICATION PROCESSORS, METHODS, SYSTEMS, AND INSTRUCTIONS
Organization Name
Inventor(s)
Kenneth Daxer of Sunnyvale CA (US)
Martin Langhammer of Alderbury (GB)
COMPLEX NUMBER MATRIX MULTIPLICATION PROCESSORS, METHODS, SYSTEMS, AND INSTRUCTIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240160443 titled 'COMPLEX NUMBER MATRIX MULTIPLICATION PROCESSORS, METHODS, SYSTEMS, AND INSTRUCTIONS
Simplified Explanation
The abstract describes a processor designed to perform complex number matrix multiplication, where two source matrices of complex numbers are multiplied to generate a destination complex number matrix.
- The processor generates k complex numbers by performing k complex multiplications of corresponding elements from a row of the first source matrix and a column of the second source matrix.
- The k generated complex numbers are then combined to produce a single complex number, which is either stored in or combined with an existing element in the destination matrix.
Potential Applications
This technology can be applied in various fields such as signal processing, image processing, and scientific computing where complex number matrix operations are required.
Problems Solved
This technology solves the problem of efficiently performing complex number matrix multiplication, which is a computationally intensive task in many applications.
Benefits
The benefits of this technology include faster computation of complex number matrix multiplications, improved accuracy in numerical calculations, and increased efficiency in processing complex data sets.
Potential Commercial Applications
Potential commercial applications of this technology include software development for scientific simulations, data analysis tools, and machine learning algorithms that involve complex number matrix operations.
Possible Prior Art
Prior art in the field of matrix multiplication algorithms and complex number arithmetic may exist, but specific examples are not provided in this context.
Unanswered Questions
How does the processor handle matrix dimensions that are not compatible for multiplication?
The abstract does not mention how the processor deals with source matrices that cannot be multiplied due to incompatible dimensions.
What is the computational complexity of the processor's algorithm for complex number matrix multiplication?
The abstract does not provide information on the computational complexity of the algorithm used by the processor.
Original Abstract Submitted
a processor to perform a complex number matrix multiplication instruction indicating a first source complex number matrix having m rows by k columns of complex numbers and a second source complex number matrix having k rows by n columns of complex numbers. the processor, for each row m of the first source matrix, and for each column n of the second source matrix, to generate k complex numbers by k complex multiplications of k complex numbers of the row m of the first source matrix with k corresponding complex numbers of the column n of the second source matrix, and to combine the k generated complex numbers to generate a complex number. the generated complex number may either be stored at, or the generated complex number may be combined with a complex number at, a row m and a column n of a destination complex number matrix.
