Routing and Flow Control — Silicon & PPA Impact

Silicon, power, area, and timing impact

Links, buffers, arbiters, and clock crossings consume area, power, and timing margin.

Area drivers

• Buffers/tables/SRAM

• Bypass and issue width wiring

• Coherency metadata

Power drivers

• Activity factor

• SRAM energy

• Wake-up bursts

Timing and frequency impact

• Critical path movement

• Macro distance

• Frequency pressure

PD and floorplan consequences

• Place hot structures near consumers

• Macro placement constraints

• NoC congestion

Verification burden

• More states/policies

• Ordering regressions

• Traceable workload proof

PPA — Routing and Flow Control
area/power/timing/verif all workload-dependent

Key takeaways

• No architecture signoff without PPA statement

• PD latency budget can force architecture change

Architecture deep dive

NoC is a queueing system — bandwidth, latency, and deadlock are coupled.

Concept diagram

NoC TOPOLOGY SKETCH

CPU0 ──┐      ┌── LLC0 ── DRAM0
       R0 ─── R1
CPU1 ──┘      │
              R2 ─── R3 ── GPU/DMA
              │      │
             NPU    LLC1 ── DRAM1

Look for: hot links, cyclic dependencies, VC starvation, and tail latency.

Metric graph

LATENCY DISTRIBUTION

p50    ██████  32 ns
p90    ████████████  71 ns
p99    ████████████████████████  210 ns
p99.9  █████████████████████████████████  480 ns

Averages hide QoS failures.

Metrics and artifacts

• link utilization

• average latency by master

• retry/backpressure counts

• QoS violation log

Mini case study

Average latency looks fine but tail latency spikes for CPU coherent reads when GPU DMA runs. QoS and separate VCs fix the starvation without doubling link width.

Debug branches

• If deadlock, check credit loops and routing restrictions first.

• If latency tail long, inspect arbitration and buffer depth.

Senior review question

Ask: what single metric would prove this concept is working or failing on your workload?

Key takeaways

• Connect every architecture claim to a workload and measurable metric.

• State verification and PPA impact before proposing design changes.

Common pitfalls

• Feature-driven design without MPKI/IPC/bandwidth evidence.

• Ignoring coherency and NoC traffic in cache and accelerator sizing.

Study notes

Re-read this topic with one concrete workload.