Vector Sorting via Comparison Matrix and Control Vector
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Solution Overview
Problem
Existing processor technologies face challenges in efficiently sorting vectors with duplicate values, leading to data loss and information loss due to the inability to handle duplicates effectively during sorting operations.
Innovation Solution
The implementation of specific hardware processor instructions and operations, such as VCONF_SQR_GT, VCONF_TRI_EQ, and VPUSH_PERM, which allow for the execution of instructions like ZMM1=VCONF_SQR_GT(ZMM_INDEX), ZMM_CONTROL=VPOPCNT(ZMM1), and ZMM_RES=VPUSH_PERM(ZMM_INDEX, ZMM_CONTROL), to handle duplicates by populating comparison matrices and control vectors, enabling stable sorting of vectors with unique and duplicate elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional sorting instructions are used, then sorting speed is improved, but data loss occurs due to inability to handle duplicate values
Solution Approach 1:
The sorting operation is divided into multiple phases: comparison phase (VCONF_SQR_GT), control vector generation phase (VPOPCNT), and permutation phase (VPUSH_PERM). Each phase handles specific aspects of sorting, with the control vector phase specifically addressing duplicate handling by counting occurrences and assigning unique positions, thus preventing data loss while maintaining high sorting speed.
Solution Approach 2:
A control vector is introduced as an intermediary data structure between the comparison results and the final permutation. The control vector stores information about duplicate elements and their positions, acting as a mediator that translates comparison results into accurate permutation instructions, thereby preventing data loss while maintaining sorting efficiency.
2Reliability
If duplicate handling is added to sorting operations, then information loss is prevented, but device complexity increases
Solution Approach 1:
Multiple sorting-related operations are merged into a unified instruction set with consistent semantics. The VCONF_SQR_GT, VPOPCNT, and VPUSH_PERM instructions work together as an integrated system, where each instruction builds upon the previous one, reducing overall complexity compared to having separate independent operations for comparison, counting, and permutation.
Solution Approach 2:
The sorting instruction set is designed to handle both unique and duplicate values using the same instruction sequence. The control vector mechanism is universal and works regardless of whether duplicates are present, eliminating the need for separate handling paths and reducing complexity.
3Stability of the object's composition
If stable sorting is implemented, then order preservation is improved, but sorting efficiency decreases
Solution Approach 1:
The comparison phase (VCONF_SQR_GT) performs preliminary actions by establishing the complete ordering relationship between all elements before the final permutation. This preliminary comparison and control vector generation enables the subsequent VPUSH_PERM operation to directly implement stable sorting without requiring additional comparison passes, thus maintaining efficiency while ensuring order preservation.
Data Source
AI summary
Systems, methods, and apparatuses relating to element sorting of vectors are described. In one embodiment, a processor includes a decoder to decode an instruction into a decoded instruction; and an execution unit to execute the decoded instruction to: provide storage for a comparison matrix to store a comparison value for each element of an input vector compared against the other elements of the input vector, perform a comparison operation on elements of the input vector corresponding to storage of comparison values above a main diagonal of the comparison matrix, perform a different operation on elements of the input vector corresponding to storage of comparison values below the main diagonal of the comparison matrix, and store results of the comparison operation and the different operation in the comparison matrix.