Bandwidth & Latency Budgeting: Reports & Metrics

Reports and metrics

Reports & Metrics for Bandwidth & Latency Budgeting focuses on sustained bandwidth, p99 latency, utilization, head-of-line blocking. The goal is to connect the observable symptom to protocol mechanism, ownership, and regression risk.

The job of a report is to turn sustained bandwidth, p99 latency, utilization, head-of-line blocking into a decision. A single average number is almost never enough; you need the distribution, the traffic class breakdown, and a clear gap between legal maximum and product target.

Metric movement

METRIC GRAPH — sustained bandwidth, p99 latency, utilization, head-of-line blocking

throughput / success
  ^
  |                         target
  |                       - - - - - - -
  |                  o after bounded fix
  |              o
  |         o baseline
  |    o failing run
  +--------------------------------------> experiment
    config A     isolated root cause     accepted change

Readout:
  - compare identical payload, clock, reset, traffic seed, and firmware setup
  - separate headline bandwidth from useful payload bandwidth
  - explain why the protocol mechanism moved the metric

Latency distribution

LATENCY HISTOGRAM — Bandwidth & Latency Budgeting

count
  |               ███
  |             ███████
  |          █████████████
  |        █████████████████        <- long tail = the real complaint
  |      ████████████████████████████
  +------------------------------------> latency
   p50      p90    p95       p99  (watch p99, not the average)

Average hides the tail; product pain lives at p95/p99.

• Track sustained bandwidth, p99 latency, utilization, head-of-line blocking by traffic class, payload size, and clock/reset mode.

• Report p50/p95/p99 latency when user-visible stalls matter.

• Include legal maximums and product targets; they are not the same thing.

• Always store the metric next to the artifact that produced it.

Protocol deep dive

Before naming AXI or PCIe, engineers must master layering, handshakes, ordering, and bandwidth math. These four ideas explain 80% of integration bugs.

Concept diagram

FUNDAMENTALS STACK

software intent
     |
transaction (ID, addr, len, attr, order)
     |
link/channel (handshake, credit, retry)
     |
physical (clock, reset, lanes, PHY)

Debug golden rule: never change layers without carrying transaction identity.

Metric graph

STALL BREAKDOWN EXAMPLE

ready stalls      ████████████████  42%
credit wait       ██████████        26%
ordering block    ██████            16%
reset/config      ████              10%
other             ██                6%

If ready stalls dominate, widening the bus will not help.

Metrics and artifacts to collect

• transaction latency by class

• ready stall cycles

• outstanding depth utilization

• payload efficiency vs headline width

• retry and error rate

Mini case study

A team widened a 64-bit interface to 128-bit but throughput rose only 8% because ready stalls from a slow slave dominated. Fixing slave acceptance and FIFO depth moved the metric; width did not.

Debug branches

• If latency spikes but bandwidth flat, check outstanding limits and ordering.

• If throughput collapses at high load, draw the knee curve — you are past queue stability.

• If intermittent, compare reset release order and clock domain boundaries.

Senior review question

Ask: what is the first transaction that deviates, and which spec rule does it test?

Key takeaways

• Connect every protocol claim to a transaction identity and measurable metric.

• Store the artifact (waveform, log, counter) next to every signoff decision.

Common pitfalls

• Debugging timeouts without finding the first bad transaction.

• Quoting peak bus width without payload efficiency and retry overhead.

• Treating VIP compliance as a substitute for system integration replay.

How to read the numbers

sustained bandwidth, p99 latency, utilization, head-of-line blocking must be split by traffic class, payload size, and reset mode.