Speculative Execution Throttle Control Circuitry
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Solution Overview
Problem
In out-of-order processors, sophisticated branch prediction is required to minimize wasted processing and power on mispredicted branches, but this complexity and potential for high speculation costs lead to inefficiencies in speculative execution.
Innovation Solution
The introduction of path speculation cost calculation and throttle control circuitry to adjust the rate of instruction issuance based on the likelihood of branch misprediction, using confidence levels and speculation cost metrics to manage the number of in-flight instructions and reduce wasted power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sophisticated branch prediction is used to improve speculative execution accuracy, then the reliability of branch prediction improves, but the device complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where the processor monitors the accuracy of branch predictions and adjusts its behavior accordingly. When misprediction rates exceed thresholds, the system feeds back control signals to throttle instruction issuance, creating a closed-loop control system that adapts to actual prediction performance without requiring increasingly complex prediction hardware.
Solution Approach 2:
The system uses its own performance data (misprediction rates, instruction flush counts) to automatically regulate its operation. The processor self-adjusts the instruction issuance rate based on internally monitored metrics, eliminating the need for external control or more complex prediction logic to achieve adaptive behavior.
2Productivity
If speculative execution is performed to improve processing throughput, then the productivity increases, but the loss of energy increases due to wasted processing on mispredicted paths
Solution Approach 1:
The system dynamically adjusts the instruction issuance rate based on real-time monitoring of misprediction metrics. Rather than static speculation control, the processor continuously adapts the throughput of speculative instructions by varying the issuance rate according to current prediction accuracy, optimizing the balance between productivity and energy waste.
Solution Approach 2:
The patent applies partial action by issuing instructions at a controlled rate rather than maximum throughput. When misprediction indicators are detected, the system deliberately limits (throttles) the instruction issuance to avoid excessive speculative execution that would waste energy, performing only the necessary partial amount of speculative work.
3Speed
If the instruction issuance rate is increased to improve processing speed, then the speed increases, but the loss of time increases due to instruction flushing when mispredictions occur
Solution Approach 1:
The system monitors instruction flush events and uses this feedback to adjust the issuance rate. When flushes occur indicating mispredictions, the feedback loop reduces the issuance rate to prevent future flushes, thereby reducing the time lost to re-execution and maintaining more steady progress through the instruction stream.
Solution Approach 2:
The system prepares for potential mispredictions by throttling the instruction issuance rate in advance when early indicators of misprediction are detected. This cushioning approach prevents the processor from issuing too many instructions that would subsequently need to be flushed, thereby cushioning against the time loss that would result from mass flushing events.
Data Source
AI summary
Apparatuses for data processing and methods of data processing are provided. A data processing apparatus performs data processing operations in response to a sequence of instructions including performing speculative execution of at least some of the sequence of instructions. In response to a branch instruction the data processing apparatus predicts whether or not the branch is taken or not taken further speculative instruction execution is based on that prediction. A path speculation cost is calculated in dependence on a number of recently flushed instructions and a rate at which speculatively executed instructions are issued may be modified based on the path speculation cost.