Post-Silicon Accelerator Debug: Inputs and Outputs

Inputs and outputs contract

Inputs and Outputs for Post-Silicon Accelerator Debug is anchored on Mean time to isolate root cause from lab failure to actionable fix across hardware, firmware, and compiler layers.. Convert measurements into mechanism-backed decisions with clear owner accountability.

INPUTS
  - workload profile and SLA target
  - model precision and quality thresholds
  - compiler/runtime/firmware metadata
  - hardware operating envelope assumptions

OUTPUTS
  - evidence-backed bottleneck classification
  - owner-signed mitigation proposal
  - validation matrix with rollback triggers
  - release recommendation

Ownership split

OWNERSHIP LAYERS - Post-Silicon Accelerator Debug

+----------------------+--------------------------------+--------------------------------+
| Team                 | Primary responsibility         | Closure artifact               |
+----------------------+--------------------------------+--------------------------------+
| post-silicon validation lead | mechanism and architecture intent| design rationale + tradeoffs   |
| debug tools engineer | mapping, runtime, and execution   | profile traces + bottleneck map|
| firmware lead | correctness, risk, and signoff    | test report + closure memo     |
+----------------------+--------------------------------+--------------------------------+

AI accelerator deep dive

Bring-up speed and correctness depend on designed-in observability and replayable debug flow.

Concept diagram

BRING-UP EVIDENCE LOOP

failure symptom -> trace packet -> replay -> isolate root cause -> bounded fix

Metric graph

OBSERVABILITY VALUE

directed tests only      ██████████
plus counters            ███████
plus trace and replay    ███

Metrics and artifacts to collect

• counter completeness

• trace trigger coverage

• replay success rate

• escape-risk trend

Mini case study

A silicon-only regression closed quickly because trace identity and counter alignment were planned before tapeout.

Debug branches

• Start from first failing trace window

• Align software and hardware timestamps

• Demand reversible owner fix before signoff

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.

Handoff explanation

Inputs should include workload profile, model revision, compiler/runtime versions, and platform power mode.

Outputs must include actionable interpretation of Mean time to isolate root cause from lab failure to actionable fix across hardware, firmware, and compiler layers., required artifacts (Bring-up debug runbook with triage checklist, trace requirements, and escalation paths.), owner, and validation scope.

The ideal handoff packet is reproducible: fixed seeds, explicit baseline, and rejected alternatives.