Processor Vector Comparison Logic for Middle Value Extraction
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Solution Overview
Problem
Existing processor architectures face inefficiencies in performing blend and compare operations on multiple vectors, particularly in determining middle, lowest, and highest values, due to data dependencies and high latency.
Innovation Solution
The introduction of specialized instructions and logic circuitry within the processor that allow for parallel execution of comparisons and blend operations, utilizing pre-defined tables and control functions to compute intermediate bit results, reducing latency and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional sequential comparison methods are used to determine middle, lowest, or highest values of three vectors, then the operations can be performed with existing processor instructions, but the process suffers from high latency and data dependencies that reduce efficiency
Solution Approach 1:
The patent segments the comparison operation into independent parallel comparisons. Instead of sequentially comparing vectors to find middle, lowest, or highest values, the system performs multiple comparison operations simultaneously using separate comparison units, each handling different vector pairs independently. This eliminates data dependencies and reduces overall latency.
Solution Approach 2:
The patent introduces a new dimensional approach by adding specialized blend and compare instruction capabilities that operate in parallel dimensions. The processor executes multiple comparison operations across different vector pairs simultaneously, transforming the traditional single-threaded sequential comparison into a multi-dimensional parallel operation space.
2Use of energy by moving object
If specialized instructions and logic circuitry are introduced to enable parallel execution of comparisons and blend operations, then latency is reduced and energy efficiency improves, but the device complexity increases
Solution Approach 1:
The patent implements universal blend and compare logic circuitry that can handle multiple comparison scenarios (middle value, lowest value, highest value) through a single unified instruction set. The same hardware resources perform different comparison functions by interpreting different control parameters, eliminating the need for separate dedicated circuits for each comparison type and reducing overall complexity.
Solution Approach 2:
The patent uses parameter changes to control the behavior of the blend and compare operations. By modifying control parameters in the instruction set, the same hardware circuitry can dynamically switch between different comparison modes (finding middle, lowest, or highest values), enabling flexible functionality without increasing physical hardware complexity.
3Adaptability or versatility
If multiple comparison operations are executed sequentially to determine middle, lowest, and highest values, then the processor can use existing instruction sets, but the productivity is reduced due to data dependencies
Solution Approach 1:
The patent performs preliminary parallel comparisons of all vector pairs before the final blend operation. By pre-computing comparison results for all possible vector pairs (A>B, A>C, B>C) simultaneously, the system eliminates data dependencies that would otherwise require sequential execution, enabling the final blend operation to proceed independently and immediately.
Data Source
AI summary
Systems, methods, and apparatuses relating to multiple source blend operations are described. In one embodiment, a processor is to execute an instruction to: receive a first input operand of a first input vector, a second input operand of a second input vector, and a third input operand of a third input vector, compare each element from the first input vector to each corresponding element of the second input vector to produce a first comparison vector, compare each element from the first input vector to each corresponding element of the third input vector to produce a second comparison vector, compare each element from the second input vector to each corresponding element of the third input vector to produce a third comparison vector, determine a middle value for each element position of the input vectors from the comparison vectors, and output the middle values into same element positions in an output vector.