Intel corporation (20240330402). MACHINE LEARNING ARCHITECTURE SUPPORT FOR BLOCK SPARSITY simplified abstract
Contents
MACHINE LEARNING ARCHITECTURE SUPPORT FOR BLOCK SPARSITY
Organization Name
Inventor(s)
Omid Azizi of Redwood City CA (US)
MACHINE LEARNING ARCHITECTURE SUPPORT FOR BLOCK SPARSITY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240330402 titled 'MACHINE LEARNING ARCHITECTURE SUPPORT FOR BLOCK SPARSITY
Simplified Explanation: This patent application discusses accelerating matrix operations for different matrix sparsity patterns by converting matrices with one sparsity pattern to another suitable for efficient computation.
- Matrix operation accelerator designed for specific sparsity patterns
- Conversion of matrices to match accelerator requirements
- Rearranging rows and columns to optimize computation
- Enhancing efficiency of matrix operations
- Improving performance of matrix operation accelerators
Key Features and Innovation: - Customized matrix operation acceleration for different sparsity patterns - Conversion techniques to match matrix sparsity patterns with accelerator requirements - Optimization of computation by rearranging matrix rows and columns - Enhanced efficiency and performance of matrix operations - Improved utilization of matrix operation accelerators
Potential Applications: This technology can be applied in various fields such as: - Machine learning - Data analytics - Image processing - Scientific computing - Financial modeling
Problems Solved: - Inefficient matrix operations for different sparsity patterns - Suboptimal performance of matrix operation accelerators - Lack of customization for specific matrix sparsity patterns - Difficulty in optimizing computation for varying matrix structures
Benefits: - Faster matrix operations - Improved efficiency in computation - Enhanced performance of matrix operation accelerators - Customized acceleration for specific sparsity patterns - Increased productivity in data processing tasks
Commercial Applications: Accelerated matrix operations technology can have significant commercial applications in industries such as: - Artificial intelligence - Big data analytics - Financial services - Healthcare informatics - Autonomous systems development
Questions about Matrix Operation Acceleration: 1. How does this technology improve the efficiency of matrix operations? 2. What are the potential applications of customized matrix operation acceleration?
Frequently Updated Research: Stay updated on the latest advancements in matrix operation acceleration technology to ensure optimal performance and efficiency in computational tasks.
Original Abstract Submitted
this disclosure relates matrix operation acceleration for different matrix sparsity patterns. a matrix operation accelerator may be designed to perform matrix operations more efficiently for a first matrix sparsity pattern rather than for a second matrix sparsity pattern. a matrix with the second sparsity pattern may be converted to a matrix with the first sparsity pattern and provided to the matrix operation accelerator. by rearranging the rows and/or columns of the matrix, the sparsity pattern of the matrix may be converted to a sparsity pattern that is suitable for computation with the matrix operation accelerator.
