Vector Index Registers for Multi-Lane Conditional Operations
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Solution Overview
Problem
Conventional scalar processors face performance limitations when accessing multiple positions of operand vectors due to the need for continuous incrementation and loading of scalar index registers, which can slow down vector operations.
Innovation Solution
The use of vector index registers with multi-lane solutions allows for the storage and access of multiple addresses simultaneously, enabling faster and more efficient execution of conditional operations by splitting address storage into even and odd positions, thereby reducing the time required for selective indexing and accessing non-sequential elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If scalar index registers are used for accessing multiple positions of operand vectors, then the processor can maintain simplicity in register design, but the processing speed decreases due to continuous incrementation and loading requirements
Solution Approach 1:
The index register is divided into multiple lanes (e.g., even lane and odd lane) that can be independently accessed. Each lane stores indices for specific positions (even or odd), allowing parallel access to multiple elements without sequential incrementation. This segmentation enables the processor to fetch multiple vector elements simultaneously, dramatically improving processing speed while maintaining reasonable register complexity through structured organization.
Solution Approach 2:
The patent introduces a new dimension to index register organization by adding lane identifiers (even/odd lanes) to the traditional single index register structure. This multi-lane structure allows the processor to access elements at different positions across multiple lanes in parallel, transforming the single-dimensional sequential access model into a multi-dimensional parallel access model, thereby improving speed without proportionally increasing complexity.
2Loss of time
If scalar index registers are incremented and loaded separately for each position, then the register structure remains simple, but the time required for selective indexing increases
Solution Approach 1:
The index register is segmented into multiple independent lanes (even lane, odd lane, etc.), where each lane can be accessed independently. This allows the processor to load and access indices for multiple positions simultaneously rather than sequentially incrementing a single register, significantly reducing indexing time while maintaining a structured but manageable register design.
Solution Approach 2:
Indices for multiple positions are pre-loaded into different lanes of the index register before the vector operation begins. This preliminary action eliminates the need for continuous incrementation and loading during execution, reducing indexing time while the multi-lane structure keeps the overall register complexity controlled through organized pre-positioning of index values.
3Productivity
If conventional scalar processors are used for vector operations, then the hardware design remains simple, but the overall processing efficiency decreases
Solution Approach 1:
The processor architecture is segmented into multiple lanes with dedicated index registers and data paths for each lane. This allows parallel processing of multiple vector elements simultaneously, dramatically improving processing efficiency. The segmentation is organized such that each lane handles specific positions (even or odd), creating an efficient parallel processing structure without excessive complexity through systematic organization.
Solution Approach 2:
The processor architecture transitions from a single-dimensional scalar processing model to a multi-dimensional vector processing model with multiple lanes. This dimensional expansion enables simultaneous access to multiple operand positions across different lanes, improving productivity while the structured multi-lane organization keeps architecture complexity manageable through regular patterns and systematic design.
Data Source
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AI summary
Disclosed herein are vector index registers for storing or loading indexes of true and/or false results of conditional operations using multiple lane processing in vector processors. Each of the vector index registers store multiple addresses for accessing multiple positions in operand vectors in various types of operations that can leverage multi-lane processing.