Read-write system and method compatible with two-dimensional structure data

Abstract

A read-write system compatible with two-dimensional structure data comprises a random access memory selection unit which reads and writes an SRAM (Static Random Access Memory) according to a read-write demand of instruction decoding of an operation execution unit; a prediction caching unit which is used for performing prediction caching on two-dimensional data required by instruction execution; a writing strategy unit which is used for formulating a strategy for writing data into the SRAM and writing back an external memory; a Cache mark caching unit which is used for caching the value mark of the Cache and the state value of the square block; a Cache preloading unit which is used for generating a corresponding block refreshing request according to an updating flag bit of the Cache mark cache unit, and putting the corresponding block refreshing request into the DMA unit request queue to update the Cache; and a pre-reading unit which is used for analyzing the operation tasks according to preset batches and marking the tasks. According to the system provided by the invention, the operation efficiency of the system with the vector processing capability is greatly improved.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a system and method for reading and writing compatible two-dimensional structure data. Background technique [0002] In the digital logic system, in order to balance the relationship between the access of the slower storage unit and the high-speed operation processing unit, it is often necessary to introduce a Cache (caching) design. For data sources that exist in peripheral memory (DDR external memory, etc.) in two-dimensional form, such as digital images, sensor acquisition data, and neural network data stored in a similar form that can be equivalent to a large matrix, the algorithm logic often needs to be obtained one by one. A square area with m rows and n columns (or vector form, which can be regarded as the distortion of a matrix) of a two-dimensional data file or a two-dimensional graphic area of ​​other shapes is used for scientific operations such as convolution ...

AI Technical Summary

Problems solved by technology

For data sources that exist in peripheral memory (DDR external memory, etc.) in two-dimensional form, such as digital images, sensor acquisition data, and neural network data stored in a similar form that can be equivalent to a large matrix, the algorithm logic often needs to be obtained one by one. A square area with m rows and n columns (or vector form, which can be regarded as the distortion of a matrix) of a two-dimensional data file or a two-dimensional graphic area of ​​other shapes is used for scientific operations such as convolution operations and iterative operations, while This kind of unit area with multiple consecutive calculations has a certain spatial and time domain continuity that is displaced from the center point of the area to the surroundings, so the unit area will have considerable overlap between consecutive multiple operations (such as figure 1 ), intuitively, this requires that when reading data from external memory to refresh the cache, the overlapping part should be kept in the cache as long as possible, and the unit area can be acquired by the operation processing unit faster, otherwise it will slow down the system Actual operation and processing efficiency

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