Dynamic Instruction Simulation Model Selection
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Solution Overview
Problem
Timing and power simulation of system execution of instructions have not been as well researched as functional simulation, leading to unsatisfactory solutions in these areas.
Innovation Solution
A system with a simulation component and computer-readable medium that employs multiple simulation models to simulate execution of instructions, dynamically determining the most important phases and adapting models based on instruction characteristics to provide accurate and efficient timing and power simulation results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If timing simulation and power simulation are performed with high accuracy, then the simulation results are more reliable, but the simulation time and computational resources increase significantly
Solution Approach 1:
The patent segments the simulation process into multiple phases (fetch, decode, execute, write-back) and implements phase-based sampling where not all phases are simulated with full detail at all times. This segmentation allows the system to achieve acceptable accuracy while reducing overall simulation time by selectively applying detailed modeling only when necessary.
Solution Approach 2:
The patent applies partial action by using simplified models for certain simulation aspects and full-detail models for others. The system dynamically adjusts the level of simulation detail based on the specific instructions being executed, applying comprehensive timing and power modeling only when needed rather than uniformly across all instructions, thus balancing accuracy with computational efficiency.
2Adaptability or versatility
If multiple simulation models are used to cover different instruction characteristics, then the adaptability and accuracy improve, but the device complexity increases
Solution Approach 1:
The patent implements a universal simulation framework that can handle multiple instruction types and characteristics through a single integrated system. The simulation component is designed to dynamically select and apply appropriate modeling approaches based on instruction characteristics, making the system versatile without requiring separate dedicated models for each instruction type.
Solution Approach 2:
The patent employs dynamic model selection where the simulation system adjusts its complexity and detail level based on the specific instructions being executed. The simulation component analyzes instruction characteristics in real-time and adapts the simulation approach accordingly, transitioning between simplified and detailed models as needed rather than using a fixed complex model for all cases.
3Productivity
If dynamic model adaptation is implemented based on instruction characteristics, then the simulation efficiency improves, but the difficulty of detecting and measuring instruction importance increases
Solution Approach 1:
The patent applies preliminary action by pre-defining categories of instruction phases (fetch, decode, execute, write-back) and their typical characteristics. Rather than analyzing each instruction from scratch to determine its importance, the system has pre-established knowledge about phase characteristics that guides the simulation approach, reducing the computational burden of real-time analysis while maintaining effectiveness.
Data Source
AI summary
Instructions to be executed on a system are simulated. Representative simulation phases of the instructions, which most affect simulation results of the instructions to be executed on the system, are dynamically determined. For each representative simulation phase of the instructions, a model is selected from a number of models that provides specified accuracy with a minimal amount of simulation time, and the representative simulation phase is simulated using the model selected. The simulation results for the instructions to be executed on the system are then output.