18099595. TRACKING BUFFER REDUCTION AND REUSE IN A PROCESSOR simplified abstract (Arm Limited)
TRACKING BUFFER REDUCTION AND REUSE IN A PROCESSOR
Organization Name
Inventor(s)
Jens Olson of San Jose CA (US)
Jared Corey Smolens of Santa Clara CA (US)
Dominic Hugo Symes of Cambridge (GB)
Elliot Maurice Simon Rosemarine of London (GB)
TRACKING BUFFER REDUCTION AND REUSE IN A PROCESSOR - A simplified explanation of the abstract
This abstract first appeared for US patent application 18099595 titled 'TRACKING BUFFER REDUCTION AND REUSE IN A PROCESSOR
The abstract describes a processor with a handling unit and multiple components executing functions on data in a coordinate space with N dimensions. The handling unit receives tasks, data structures, and a partially ordered set of data items associated with instructions for the components.
- The processor has a handling unit and multiple components executing functions on data in a coordinate space with N dimensions.
- The handling unit receives tasks and data structures with a partially ordered set of data items associated with instructions for the components.
- Each data item is linked to a component and indicates dimensions where changes trigger the component's function or store data for another component.
- The handling unit iterates over the coordinate space and executes tasks using the data items.
Potential Applications: - High-performance computing - Data processing in multi-dimensional spaces - Artificial intelligence and machine learning algorithms
Problems Solved: - Efficient execution of tasks in multi-dimensional coordinate spaces - Optimal utilization of components in a processor - Streamlined data processing workflows
Benefits: - Improved performance in handling complex data operations - Enhanced scalability for processing tasks in high-dimensional spaces - Increased efficiency in executing functions across multiple components
Commercial Applications: Title: "Multi-Dimensional Data Processing Processor for High-Performance Computing" This technology can be utilized in industries such as: - Scientific research - Financial modeling - Weather forecasting - Image and video processing
Questions about the technology: 1. How does this processor improve data processing efficiency in high-dimensional spaces? 2. What are the key advantages of using a partially ordered set of data items for task execution in a processor?
Frequently Updated Research: Stay updated on advancements in high-performance computing, data processing algorithms, and multi-dimensional data analysis techniques to enhance the capabilities of this processor.
Original Abstract Submitted
A processor comprising: a handling unit; a plurality of components each configured to execute a function. The handling unit can receive a task comprising operations on data in a coordinate space having N dimensions, receive a data structure describing execution of the task and comprising a partially ordered set of data items each associated with instructions usable by the plurality of components when executing the task, each data item is associated with a component among the plurality of components, each data item indicates dimensions of the coordinates space for which changes of coordinate causes the function of the associated component to execute, and dimensions of the coordinate space for which changes of coordinate causes the function of the associated component to store data ready to be used by another component. The handling unit iterates over the coordinate space and executes the task using the partially ordered set of data items.