Merge pull request #3087 from madeline-underwood/topd

Topd

Author: jasonrandrews

content/learning-paths/cross-platform/topdown-compare/1c-compare-arch.md

@@ -62,7 +62,7 @@ On Arm Neoverse V2, equivalent lost work appears under Bad Speculation through `
 | Frontend vs Backend Balance | Measured by slot distribution from `IDQ_UOPS_NOT_DELIVERED` and `CYCLE_ACTIVITY` counters | Measured using `STALL_SLOT_FRONTEND` and `STALL_SLOT_BACKEND` |
 | Speculative Execution Impact | Explicit "Bad Speculation" slot fraction + `MACHINE_CLEARS.*` | Derived from `BR_MIS_PRED`, `BR_MIS_PRED_RETIRED`, and `OP_SPEC/OP_RETIRED` ratios |
 | Cache and Memory Hierarchy | Layered: L1 → L2 → L3 → DRAM via `CYCLE_ACTIVITY` events | Effectiveness groups: L1I/L1D/L2/LL with MPKI and hit/miss ratios |
-| Stall Accounting Granularity | Strict hierarchical attribution (single bottleneck per slot) | Flexible overlap across groups—multiple concurrent stall sources possible |
+| Stall Accounting Granularity | Strict hierarchical attribution (single bottleneck per slot) | Flexible overlap across groups - multiple concurrent stall sources possible |
 | Metric Normalization | All metrics normalized to total slots = machine_width × CPU cycles | All metrics normalized to total slots = CPU cycles × 8 (rename width) |
 
 ## Practical cross-platform guidance

content/learning-paths/cross-platform/topdown-compare/_index.md

@@ -3,6 +3,8 @@ title: Compare Arm Neoverse and Intel x86 top-down performance analysis with PMU
 
 minutes_to_complete: 30
 
+description: Learn how to compare Arm Neoverse and Intel x86 top-down performance analysis methodologies using PMU counters, Linux Perf, and topdown-tool to identify bottlenecks across architectures.
+
 who_is_this_for: This is an advanced topic for software developers and performance engineers who want to understand the similarities and differences between Arm Neoverse and Intel x86 top-down performance analysis using PMU counters, Linux Perf, and the topdown-tool. 
 
 learning_objectives: