Compare Arm Neoverse and Intel x86 top-down performance analysis with PMU counters
Introduction
Analyze Intel x86 and Arm Neoverse top-down performance methodologies
Understand Intel x86 multi-level hierarchical top-down analysis
Understand Arm Neoverse top-down analysis
Evaluate cross-platform PMU counter differences
Measure cross-platform performance with topdown-tool and Perf PMU counters
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Contrast Intel and Arm Neoverse implementation approaches

After understanding each architecture’s methodology individually, you can now examine how they differ in implementation while achieving equivalent analysis capabilities. Both architectures implement the same fundamental approach with architecture-specific adaptations:

  • Slot-based accounting: pipeline utilization measured in issue or rename slots
  • Hierarchical analysis: broad classification followed by drill-down into dominant bottlenecks
  • Resource attribution: map performance issues to specific CPU micro-architectural components

Compare multi-level hierarchical and resource groups methodologies

AspectIntel x86Arm Neoverse
Hierarchy ModelMulti-level tree (Level 1 → Level 2 → Level 3+)Two-stage: Topdown Level 1 + Resource Groups
Slot Width4 issue slots per cycle (typical)8 rename slots per cycle (Neoverse V1)
Formula BasisMicro-operation (uop) centricOperation and cycle centric
Event NamingIntel-specific mnemonicsArm-specific mnemonics
Drill-down StrategyStrict hierarchical descentExploration by resource groups

Map equivalent PMU counters across architectures

Performance Questionx86 Intel EventsArm Neoverse Events
Frontend bound?IDQ_UOPS_NOT_DELIVERED.*STALL_SLOT_FRONTEND
Bad speculation?BR_MISP_RETIRED.*BR_MIS_PRED_RETIRED
Memory bound?CYCLE_ACTIVITY.STALLS_L3_MISSL1D_CACHE_REFILL, L2D_CACHE_REFILL
Cache effectiveness?MEM_LOAD_RETIRED.L3_MISS_PSCache refill metrics / Cache access metrics

While PMU counter names and calculation formulas differ significantly between Intel x86 and Arm Neoverse architectures, both provide equivalent top-down analysis capabilities. Understanding these methodological differences enables effective cross-platform performance optimization:

  • Intel x86: Use perf stat --topdown for Level 1 analysis, then drill down through hierarchical levels
  • Arm Neoverse: Use topdown-tool -m Cycle_Accounting for Stage 1, then explore resource effectiveness groups
  • Cross-platform strategy: Focus on the four common categories while adapting tools and counter interpretations to each architecture

Continue to the next step to see practical examples comparing both methodologies.

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