18316602. EFFICIENT DATA PROCESSING, ARBITRATION AND PRIORITIZATION simplified abstract (Arm Limited)
Contents
- 1 EFFICIENT DATA PROCESSING, ARBITRATION AND PRIORITIZATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 EFFICIENT DATA PROCESSING, ARBITRATION AND PRIORITIZATION - A simplified explanation of the abstract
- 1.4 Potential Applications
- 1.5 Problems Solved
- 1.6 Benefits
- 1.7 Commercial Applications
- 1.8 Prior Art
- 1.9 Frequently Updated Research
- 1.10 Questions about Task Data Handling Technology
- 1.11 Original Abstract Submitted
EFFICIENT DATA PROCESSING, ARBITRATION AND PRIORITIZATION
Organization Name
Inventor(s)
Jens Olson of San Jose CA (US)
Elliot Maurice Simon Rosemarine of London (GB)
Jared Smolens of San Jose CA (US)
EFFICIENT DATA PROCESSING, ARBITRATION AND PRIORITIZATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18316602 titled 'EFFICIENT DATA PROCESSING, ARBITRATION AND PRIORITIZATION
The abstract describes a memory unit designed to handle task data that represents a directed acyclic graph of operations, where each operation corresponds to an execution unit and each connection between operations corresponds to a storage element of the execution unit. The memory unit is capable of receiving processing requests for data blocks with assigned priority values and block commands, and it arbitrates between the data blocks based on these parameters to prioritize the processing requests, which can involve writing to or reading from storage.
- The memory unit is configured to handle task data represented as a directed acyclic graph of operations.
- Each operation in the graph corresponds to an execution unit, and connections between operations map to storage elements.
- Data blocks are assigned priority values and block commands for processing requests.
- The memory unit arbitrates between data blocks based on priority values and block commands to prioritize processing requests.
- Processing requests can involve writing data to or reading data from storage.
Potential Applications
The technology could be applied in various fields such as data processing, task scheduling, and parallel computing systems.
Problems Solved
This technology addresses the efficient handling of complex task data represented as directed acyclic graphs of operations, optimizing processing requests based on priority values and block commands.
Benefits
The benefits of this technology include improved task data handling efficiency, optimized processing request prioritization, and enhanced performance in executing complex operations.
Commercial Applications
Title: Enhanced Task Data Handling Technology for Improved Efficiency This technology could be commercially utilized in data centers, cloud computing services, and high-performance computing systems to enhance task scheduling and data processing efficiency.
Prior Art
Further research can be conducted in the field of memory units designed for handling complex task data represented as directed acyclic graphs of operations to explore existing technologies and innovations.
Frequently Updated Research
Researchers are continuously exploring ways to optimize memory units for handling complex task data efficiently, improving processing request prioritization and overall system performance.
Questions about Task Data Handling Technology
What are the key features of the memory unit described in the abstract?
The memory unit is designed to handle task data represented as directed acyclic graphs of operations, with each operation mapping to an execution unit and connections between operations mapping to storage elements.
How does the memory unit prioritize processing requests?
The memory unit arbitrates between data blocks based on priority values and block commands assigned to each data block, allowing for optimized processing request prioritization.
Original Abstract Submitted
A memory unit configured for handling task data, the task data describing a task to be executed as a directed acyclic graph of operations, wherein each operation maps to a corresponding execution unit, and wherein each connection between operations in the acyclic graph maps to a corresponding storage element of the execution unit. The task data defines an operation space representing the dimensions of a multi-dimensional arrangement of the connected operations to be executed represented by the data blocks; the memory unit configured to receive a sequence of processing requests comprising the one or more data blocks with each data block assigned a priority value and comprising a block command. The memory unit is configured to arbitrate between the data blocks based upon the priority value and block command to prioritize the sequence of processing requests and wherein the processing requests include writing data to, or reading data from storage.
