Speculation Throttling Circuitry for Energy-Aware Execution
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Solution Overview
Problem
Speculative execution in data processing leads to unnecessary energy consumption due to mispredictions, which is undesirable when the cost or risk is high.
Innovation Solution
Implement throttle circuitry to control the extent of speculation based on the availability of instructions, using various throttling policies that adjust speculation based on factors like decode queue occupancy, prediction success rates, and type of predictors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If speculative execution is performed to increase performance, then execution speed is improved, but energy consumption increases due to mispredictions
Solution Approach 1:
The patent implements dynamic speculation throttling by monitoring instruction availability metrics (such as decode queue occupancy) and adjusting the speculation rate accordingly. When instruction availability is low, speculation is throttled to reduce energy consumption; when availability is high, speculation is permitted to maintain performance. This dynamic adjustment resolves the contradiction by making speculation adaptive rather than static.
Solution Approach 2:
The system employs feedback mechanisms where the performance of speculation is continuously monitored through metrics like branch prediction accuracy and instruction availability. Based on this feedback, the speculation throttling mechanism adjusts the degree of speculation performed. This closed-loop control ensures that speculation continues only when beneficial, resolving the energy-performance tradeoff.
2Productivity
If speculation is increased to improve performance, then productivity is improved, but unnecessary speculation occurs when instruction availability is high
Solution Approach 1:
The patent changes the operational parameters of speculation based on system state. By monitoring parameters such as decode queue occupancy, instruction fetch rate, and branch prediction accuracy, the system dynamically adjusts the speculation threshold and rate. This parameter-based control ensures speculation is performed only when it contributes to productivity, eliminating unnecessary speculation that would waste energy.
3Loss of energy
If speculation throttling is implemented to reduce energy consumption, then energy efficiency is improved, but complexity of the system increases
Solution Approach 1:
The speculation throttling mechanism is integrated into the existing pipeline control structures, allowing the same control logic to serve multiple functions: managing speculation rate, monitoring instruction availability, and coordinating with branch prediction units. This multi-functionality reduces the need for separate dedicated circuits, thereby limiting the increase in system complexity while achieving energy savings.
4Loss of energy
If dynamic throttling control is applied to optimize energy efficiency, then energy efficiency is improved, but difficulty of control increases
Solution Approach 1:
The speculation throttling system uses self-service principles by automatically monitoring its own performance metrics and adjusting its behavior without external intervention. The control logic is embedded within the execution pipeline, allowing the system to self-regulate speculation based on real-time conditions. This autonomous control reduces the burden on external control systems and simplifies the overall control architecture.
Data Source
AI summary
A data processing apparatus includes execution circuitry that executes a plurality of instructions using speculation. Throttle circuitry throttles an extent to which the speculation is performed and the throttle circuitry controls throttling speculation based on an availability of the instructions.