Intel corporation (20240126506). FLOATING-POINT DECOMPOSITION CIRCUITRY WITH DYNAMIC PRECISION simplified abstract
Contents
- 1 FLOATING-POINT DECOMPOSITION CIRCUITRY WITH DYNAMIC PRECISION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 FLOATING-POINT DECOMPOSITION CIRCUITRY WITH DYNAMIC PRECISION - 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 Original Abstract Submitted
FLOATING-POINT DECOMPOSITION CIRCUITRY WITH DYNAMIC PRECISION
Organization Name
Inventor(s)
Roberto Dicecco of Toronto (CA)
Joshua Fender of East York (CA)
Shane O'connell of Toronto (CA)
FLOATING-POINT DECOMPOSITION CIRCUITRY WITH DYNAMIC PRECISION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240126506 titled 'FLOATING-POINT DECOMPOSITION CIRCUITRY WITH DYNAMIC PRECISION
Simplified Explanation
The circuitry described in the abstract decomposes block floating-point numbers into lower precision floating-point numbers by utilizing high precision storage circuit, input selectors, and a low precision block floating-point vector circuit.
- High precision storage circuit provides high precision floating-point numbers.
- Input selectors receive high precision floating-point numbers and generate corresponding lower precision floating-point components with adjusted exponents.
- Low precision block floating-point vector circuit combines the lower precision floating-point components generated by the input selectors.
- The lower precision floating-point components can be processed spatially or over multiple iterations over time.
Potential Applications
This technology can be applied in:
- Signal processing
- Image processing
- Machine learning algorithms
Problems Solved
- Efficient decomposition of block floating-point numbers
- Reduction of computational complexity
- Improved accuracy in numerical calculations
Benefits
- Higher efficiency in processing floating-point numbers
- Enhanced accuracy in computations
- Potential for faster processing speeds
Potential Commercial Applications
Optimized for:
- High-performance computing systems
- Scientific computing applications
- Data analytics platforms
Possible Prior Art
One possible prior art for this technology could be the use of fixed-point arithmetic in signal processing applications to reduce computational complexity.
What is the impact of this technology on computational efficiency in signal processing applications?
This technology significantly improves computational efficiency by decomposing block floating-point numbers into lower precision components, reducing the overall computational complexity and enhancing processing speeds in signal processing applications.
How does this innovation contribute to the accuracy of numerical calculations in machine learning algorithms?
By providing a mechanism to adjust exponents and combine lower precision floating-point components, this innovation ensures improved accuracy in numerical calculations for machine learning algorithms, leading to more reliable results and predictions.
Original Abstract Submitted
circuitry for decomposing block floating-point numbers into lower precision floating-point numbers is provided. the circuitry may include a high precision storage circuit configured to provide high precision floating-point numbers, input selectors configured to receive the high precision floating-point numbers from the high precision storage circuit and to generate corresponding lower precision floating-point components with adjusted exponents, and a low precision block floating-point vector circuit configured to combine the various lower precision floating-point components generated by the input selectors. the lower precision floating-point components may be processed spatially or over multiple iterations over time.
