Interface Protocols · All levels
DDR Controller / PHY Split: Reports & Metrics
Reports & Metrics for DDR Controller / PHY Split.
Reports and metrics
Reports & Metrics for DDR Controller / PHY Split focuses on command efficiency, PHY training pass rate, read/write turnaround loss. The goal is to connect the observable symptom to protocol mechanism, ownership, and regression risk.
The job of a report is to turn command efficiency, PHY training pass rate, read/write turnaround loss 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 — command efficiency, PHY training pass rate, read/write turnaround loss
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 metricLatency distribution
LATENCY HISTOGRAM — DDR Controller / PHY Split
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 command efficiency, PHY training pass rate, read/write turnaround loss 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
DDR bandwidth is scheduler + PHY: rows, banks, refresh, and turnarounds eat headline data rate.
Concept diagram
MEMORY PATH
masters -> controller scheduler -> PHY -> DRAM banks
| |
refresh/QoS training/margin
Scheduler sees transactions; PHY sees picoseconds.Metric graph
BANDWIDTH LOSS WATERFALL
peak ████████████████████████
refresh █████████████████████
turnaround ██████████████████
row miss ██████████████
effective ██████████████
Quote the bottom bar in reviews.Metrics and artifacts to collect
effective BW
row hit rate
refresh stall %
training margin
ECC error log
Mini case study
Video workload lost half effective bandwidth after firmware enabled aggressive low-power refresh. Scheduler and firmware QoS had to be co-designed.
Debug branches
If ECC errors, check training margin and address interleave first.
If BW low with high row hit, suspect port arbitration not DRAM.
If boot fail, stop at training step in transcript.
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
command efficiency, PHY training pass rate, read/write turnaround loss must be split by traffic class, payload size, and reset mode.