Processor Instruction for Weighted Fair Queuing Minimum Value Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing processor instructions for determining the minimum or maximum value in priority queues, such as heap data structures, are inefficient, requiring numerous cycles and instructions, which hampers processing efficiency in applications like Weighted Fair Queuing (WFQ) and Generalized Processor Scheduling.
Innovation Solution
A new processor instruction set that compares and determines the minimum or maximum value of two source registers in a single cycle, along with their indices, using a combination of comparison and concatenation operations, reducing the number of processor cycles required compared to traditional methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional processor instructions (compare and jump) are used to determine minimum value in priority queues, then the minimum value can be identified, but the processing time increases significantly requiring 2n instructions for n values
Solution Approach 1:
The patent combines the compare and jump operations into a single integrated processor instruction. The new instruction performs both the comparison of values and the conditional selection (jump logic) atomically in one cycle, eliminating the need for separate compare and jump instructions that traditionally required 2n cycles for n values.
Solution Approach 2:
The patent changes the operational parameters of the processor by introducing a new instruction type that operates differently from traditional compare-jump sequences. This new instruction uses a unified comparison mechanism that directly outputs the minimum value index without requiring separate control flow operations, fundamentally changing how minimum value detection is performed.
2Ease of operation
If heap data structures are used to maintain sorted order for O(1) minimum extraction, then the minimum value is readily available, but insertion and modification operations require O(log n) steps consuming considerable processing cycles
Solution Approach 1:
The patent segments the heap maintenance operations by providing specialized instructions for different operations (insertion, deletion, modification) that operate more efficiently than general-purpose implementations. Each segmented operation is optimized to reduce the overhead of maintaining heap properties while achieving the required O(log n) complexity with fewer actual cycles.
Solution Approach 2:
The patent replaces the mechanical sequence of compare-jump operations with a unified comparison instruction that directly determines minimum values. This substitution eliminates the need for complex control flow management in heap operations, reducing the instructional overhead while maintaining the O(log n) complexity for insertion and modification.
3Measurement precision
If sequential comparison methods are used to find minimum of n values, then all values can be compared systematically, but the number of steps required is O(n) which is inefficient for large datasets
Solution Approach 1:
The patent applies preliminary action by maintaining heap data structures that are pre-organized in sorted order. This preliminary organization allows the minimum value to be immediately available at the root of the heap without requiring O(n) sequential comparisons, while insertion and modification operations efficiently maintain this pre-organized state.
Data Source
AI summary
The present invention provides techniques for efficiently determining a minimum or maximum of a plurality of values and the index of the minimum using registers of a processor. The present invention also provides for various processor instructions for determining the minimum/maximum and index of two or more values. The present invention finds particular benefit in implementing heaps and in systems utilizing Weighted Fair Queuing (WFQ).