Processor Buffer Tracking for N-Dimensional Data
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Solution Overview
Problem
Current data processing techniques, such as neural network processing, face inefficiencies in handling and accessing data due to repeated reading and changing dimensionality, which complicates storage and execution of tasks across multiple components.
Innovation Solution
A processor with a handling unit that receives a task with operations in a coordinate space of N=>1 dimensions, utilizing a data structure comprising a partially ordered set of data items, where each item indicates the dimensions for execution and storage, allowing efficient iteration and coordination across components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is read multiple times from storage during neural network processing, then data can be accessed by multiple components, but storage access time and complexity increase
Solution Approach 1:
The patent divides the processing system into multiple independent components (first component, second component, third component) that can process data segments in parallel. Each component has dedicated input and output buffers, allowing data to be processed by multiple components simultaneously without repeated storage access, thus reducing access time while maintaining data accessibility.
Solution Approach 2:
The patent introduces a temporal dimension to data flow by implementing multi-dimensional buffers (input buffer, intermediate buffer, output buffer) that allow data to be reused across different time steps and processing stages. This enables components to access data from buffers rather than repeatedly accessing storage, resolving the contradiction between data accessibility and access time.
2Adaptability or versatility
If data dimensionality changes during processing, then processing flexibility improves, but storage and access complexity increases
Solution Approach 1:
The patent implements dynamic buffer management where buffer dimensions and configurations can change during processing. The system dynamically allocates and configures buffers based on the specific dimensionality requirements of different processing stages, allowing flexible adaptation to changing data dimensions without requiring complex static storage structures.
Solution Approach 2:
The patent introduces intermediate buffers as mediator structures between storage and processing components. These buffers act as intermediaries that handle dimensionality transformations and data format conversions, simplifying the interface between storage and multiple processing components while maintaining processing flexibility.
3Productivity
If multiple components process data in parallel, then processing speed increases, but coordination and data flow management complexity increases
Solution Approach 1:
The patent segments the data flow into distinct channels with dedicated buffers for each processing component. The first component has its own input and intermediate buffers, the second component has separate buffers, and the third component has dedicated output buffers. This segmentation eliminates the need for complex coordination mechanisms while enabling parallel processing, as each component operates independently on its assigned data segments.
Data Source
AI summary
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.