Predictor Types and Accuracy: Inputs and Outputs

Inputs and outputs contract

Inputs and Outputs for Predictor Types and Accuracy centers on global prediction accuracy, MPKI, and confidence calibration error. Tie every claim to a measurable artifact and an owner-controlled action.

INPUTS
  - workload definition and target KPI
  - binary/compile flags/runtime/firmware metadata
  - microarchitecture and silicon assumptions
  - correctness and regression gates

OUTPUTS
  - evidence-backed bottleneck classification
  - owner-signed fix proposal
  - validation matrix with rollback thresholds

Ownership split

CPU OWNERSHIP LAYERS - Predictor Types and Accuracy

artifact area     owner
----------------  ----------------------------
architecture    branch predictor architect
RTL/microarch   predictor RTL owner
software/tools  perf modeling lead

Rule: every regressed metric must map to an explicit owner and closure artifact.

CPU deep dive

Speculation helps only when wrong-path cost and recovery bandwidth are tightly controlled.

Concept diagram

SPECULATION LOOP

predict direction/target -> speculative fetch/decode -> resolve -> flush/recover

Metric graph

SPECULATION COST MIX

wrong-path decode work  █████
flush recovery delay    ████
refill starvation       ███

Reports and artifacts

• branch accuracy by workload

• BTB/RAS pressure report

• mispredict recovery timeline

• bad-speculation CPI share

Mini case study

Indirect branch aliasing in one service raised wrong-path work enough to dominate total CPI despite high ALU utilization.

Debug branches

• Break down mispredicts by branch family and code region

• Measure flush depth and refill bandwidth separately

• Validate predictor changes under security mitigation settings

Senior review question

Ask: which CPI/latency evidence proves this topic is truly closed beyond synthetic benchmarks?

Key takeaways

• Always connect microarchitectural counter changes to product workload outcomes.

• Lock binary, compiler, firmware, and thermal metadata before comparing CPU traces.

Common pitfalls

• Treating average IPC as sufficient proof while ignoring latency tails and outliers.

• Applying predictor or prefetch tweaks without first-failing-stage attribution.

• Declaring closure without reproducible perf, correctness, and power gates.

Handoff explanation

Inputs are broader than knob settings. CPU analysis inputs include workload mix, branch entropy, memory footprint, compiler revision, OS affinity policy, DVFS state, thermal envelope, and stepping.

Outputs must support action: global prediction accuracy, MPKI, and confidence calibration error, artifact packet (predictor-type comparison matrix, accuracy-by-workload plot, and confidence histogram), bottleneck class, owner, expected effect, and rollback scope. "Performance improved" without this packet is not closure-ready.

The safest handoff is before/after evidence: environment tags, counters, traces, hypothesis, chosen change, rejected alternatives, and regression criteria.