Intel corporation (20240134818). PROGRAMMABLE PROCESSING ARRAY SUPPORTING MULTI-DIMENSIONAL INTERPOLATION COMPUTATIONS simplified abstract
Contents
- 1 PROGRAMMABLE PROCESSING ARRAY SUPPORTING MULTI-DIMENSIONAL INTERPOLATION COMPUTATIONS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 PROGRAMMABLE PROCESSING ARRAY SUPPORTING MULTI-DIMENSIONAL INTERPOLATION COMPUTATIONS - 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
PROGRAMMABLE PROCESSING ARRAY SUPPORTING MULTI-DIMENSIONAL INTERPOLATION COMPUTATIONS
Organization Name
Inventor(s)
Zoran Zivkovic of Hertogenbosch (NL)
Jian-Guo Chen of Basking Ridge NJ (US)
Jay Oneill of Nesquehoning PA (US)
Joseph Williams of Holmdel NJ (US)
PROGRAMMABLE PROCESSING ARRAY SUPPORTING MULTI-DIMENSIONAL INTERPOLATION COMPUTATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240134818 titled 'PROGRAMMABLE PROCESSING ARRAY SUPPORTING MULTI-DIMENSIONAL INTERPOLATION COMPUTATIONS
Simplified Explanation
The patent application describes a programmable processor architecture that enables data interpolation using a single instruction stream, multiple data streams (SIMD) instruction. The architecture iteratively processes portions of a look-up table (LUT) to map data sample values in a data array for interpolation.
- The architecture enables data interpolation by iteratively processing portions of a look-up table (LUT) in accordance with a fused single instruction stream, multiple data streams (SIMD) instruction.
- The LUT contains segment entries that correspond to the result of evaluating a function using index values, which represent an independent variable of the function.
- Index values are used to map data sample values in a data array to the segment entries in the LUT, facilitating data interpolation.
- By iteratively mapping data samples to valid segment entries in each LUT portion, the architecture can scale to support larger LUTs and enable linear interpolation on multiple dimensions.
Potential Applications
The technology could be applied in image processing, signal processing, computer graphics, and scientific computing for efficient data interpolation.
Problems Solved
This technology solves the problem of efficiently interpolating data values from a large look-up table, enabling accurate and fast calculations in various applications.
Benefits
The architecture allows for scalable and efficient data interpolation, enabling complex calculations to be performed quickly and accurately.
Potential Commercial Applications
This technology could be valuable in industries such as healthcare (medical imaging), gaming (graphics rendering), finance (algorithmic trading), and engineering (simulation software).
Possible Prior Art
One possible prior art could be the use of traditional interpolation methods that may not be as efficient or scalable as the architecture described in the patent application.
Unanswered Questions
How does this architecture compare to existing interpolation methods in terms of speed and accuracy?
The article does not provide a direct comparison between this architecture and existing interpolation methods in terms of speed and accuracy. Further research or testing would be needed to determine the performance differences.
What are the potential limitations or constraints of implementing this architecture in practical applications?
The article does not address the potential limitations or constraints of implementing this architecture in practical applications. Factors such as hardware requirements, compatibility with existing systems, and cost implications would need to be considered.
Original Abstract Submitted
techniques are disclosed for a programmable processor architecture that enables data interpolation using an architecture that iteratively processes portions of a look-up table (lut) in accordance with a fused single instruction stream, multiple data streams (simd) instruction. the lut may contain segment entries that correspond to a result of evaluating a function using a corresponding index values, which represent an independent variable of the function. the index values are used to map data sample values in a data array that is to be interpolated to the segment entries. by using an iterative process of mapping data samples to valid segment entries contained in each lut portion, the architecture advantageously facilitates scaling to support larger luts and thus may be expanded to enable linear interpolation on multiple dimensions.
