Systolic Mesh Basics: Reports and Metrics

Reports and metrics

Reports and Metrics for Systolic Mesh Basics is anchored on Sustained MAC utilization versus theoretical peak under target GEMM shapes and memory-feed constraints.. Convert measurements into mechanism-backed decisions with clear owner accountability.

A useful report explains why movement happened, not only that movement happened.

Evidence matrix

EVIDENCE MATRIX - Systolic Mesh Basics

+-----------------------------+--------------------------------+--------------------------------+---------------------------+
| Evidence                    | Tells you                      | Does not prove                 | Next action               |
+-----------------------------+--------------------------------+--------------------------------+---------------------------+
| occupancy + timeline traces | where utilization is lost      | precise root cause             | map to memory and schedule|
| cache/SRAM/bandwidth stats  | data movement pressure         | model-level quality impact     | correlate with quality run|
| counter + profile alignment | bottleneck class confidence    | rollout safety                 | run full regression matrix|
| thermal/power telemetry     | sustained operating envelope   | correctness closure            | pair with verification    |
| before/after scenario pack  | mitigation movement            | long-tail stability            | execute guardrail replay  |
+-----------------------------+--------------------------------+--------------------------------+---------------------------+

• Track Sustained MAC utilization versus theoretical peak under target GEMM shapes and memory-feed constraints. on representative production workloads.

• Include build/runtime metadata in every report header.

• Correlate throughput, latency, and quality before rollout decisions.

• Call out contradictory evidence explicitly.

AI accelerator deep dive

Systolic efficiency is governed by feed quality, tile fit, and bubble control.

Concept diagram

SYSTOLIC WAVEFLOW

operand stream -> wavefront launch -> PE mesh compute -> reduction/writeback
                         ^ bubbles and feed stalls reduce realized throughput

Metric graph

UTILIZATION LOSSES

tile mismatch      ███████
feed stalls        █████████
sync bubbles       █████

Metrics and artifacts to collect

• mesh occupancy timeline

• fill-drain overhead

• tile mismatch histogram

• DRAM stall attribution

Mini case study

Increasing mesh size did not help until scheduling and tile alignment removed persistent wavefront bubbles.

Debug branches

• Measure bubble source first

• Classify compute vs memory starvation

• Tune tile policy before frequency changes

Senior review question

Ask: which first-principles bottleneck class explains the symptom, and what artifact proves it reproducibly?

Key takeaways

• Tie every accelerator claim to a reproducible workload slice and one primary metric trend.

• Prefer bounded fixes with clear owner and rollback boundary over broad tuning bundles.

Common pitfalls

• Optimizing synthetic kernels without production-shape validation.

• Reading average latency while ignoring p95 and p99 behavior.

• Declaring sparse or precision wins without fallback and quality evidence.

Report interpretation

A systolic array spatially maps multiply-accumulate work onto a grid of processing elements (PEs) where activations and weights move rhythmically between neighbors. Instead of repeatedly fetching operands from global memory, data is reused as it flows across rows and columns, while partial sums propagate along deterministic paths. This regular communication pattern simplifies timing closure, routing, and control relative to highly dynamic fabrics, but requires careful launch scheduling so wavefronts arrive in lockstep. Practical performance therefore depends on matching tile dimensions, operand streaming cadence, and pipeline latency balancing across the mesh. A useful explanation always ties observed symptom to a repeatable path where useful work was blocked, delayed, or diluted by overhead.

Use Sustained MAC utilization versus theoretical peak under target GEMM shapes and memory-feed constraints. as an alarm, then anchor action using hard evidence such as Wavefront timing worksheet with PE occupancy trace and per-tile feed/drain schedule..

Systolic performance is primarily a data-delivery and mapping discipline problem. Senior reviews expect a chain of proof: workload intent -> mapping -> hardware behavior -> product impact.

For Systolic Mesh Basics, reports should explain why Sustained MAC utilization versus theoretical peak under target GEMM shapes and memory-feed constraints. moved and which path consumed budget first.