Memory Data Matrix Layout for Lower Access Latency
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Solution Overview
Problem
Memory devices without logic for ordering information contribute to increased latency in accessing and processing data, particularly for arithmetic or matrix operations, as they require external processing resources to reorder and manipulate data.
Innovation Solution
The implementation of a memory device with an array of memory cells and a controller that directs circuitry to organize data in a matrix configuration prior to processing, reducing the need for external reordering and enhancing data throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If memory devices without logic for ordering information are used, then device complexity is reduced, but latency in accessing and processing data increases
Solution Approach 1:
The memory device performs preliminary actions by organizing data into matrix configurations before data is requested by external processors. The controller detects matrix operation requests and proactively reorganizes stored data into the required matrix format, so that when the processor needs the data, it is already in the correct configuration, eliminating latency without requiring complex external reordering logic.
Solution Approach 2:
The memory device provides self-service by incorporating an intelligent controller that can autonomously detect when matrix operations are required and automatically organize data into appropriate matrix configurations. This self-organizing capability allows the memory device to serve its own data organization needs without requiring external processing resources, reducing latency while maintaining relatively simple device architecture.
2Adaptability or versatility
If external processing resources are used to reorder data, then data can be accessed flexibly, but the number of processing steps increases
Solution Approach 1:
The invention merges the data storage function with data organization function within the same memory device. The controller integrates the ability to detect matrix operation requests and organize data into matrix configurations, combining what were previously separate functions (storage in external processors and reorganization in memory) into a unified system that improves throughput while maintaining flexibility.
Solution Approach 2:
The invention transitions from traditional linear data organization to multi-dimensional matrix configurations. By organizing data in two-dimensional matrix formats within the memory device itself, the system enables more efficient access patterns for matrix operations, reducing the number of processing steps required while maintaining data access flexibility through various matrix dimension configurations.
3Productivity
If data is organized in matrix configuration within memory device, then throughput is improved, but device complexity increases
Solution Approach 1:
The controller is designed with universal functionality that can handle multiple types of matrix operations and data organization tasks. Rather than implementing specialized hardware for each specific matrix configuration, the universal controller can adapt to different matrix dimensions and operation types through software or firmware logic, improving throughput while minimizing the increase in physical device complexity.
Data Source
AI summary
Systems, apparatuses, and methods related to organizing data to correspond to a matrix at a memory device are described. Data can be organized by circuitry coupled to an array of memory cells prior to the processing resources executing instructions on the data. The organization of data may thus occur on a memory device, rather than at an external processor. A controller coupled to the array of memory cells may direct the circuitry to organize the data in a matrix configuration to prepare the data for processing by the processing resources. The circuitry may be or include a column decode circuitry that organizes the data based on a command from the host associated with the processing resource. For example, data read in a prefetch operation may be selected to correspond to rows or columns of a matrix configuration.