Applying Brendan Gregg's USE Method to a Marine Chartplotter's Android MFD

Posted Jul 18, 2026 Updated Jul 18, 2026

By Fang Zhang

7 min read

Applying Brendan Gregg’s USE Method to a Marine Chartplotter’s Android MFD

Most marine multifunction displays (MFDs) — including the Android-based ones now common on recreational boats — run a full Android stack underneath the chartplotter UI: a Linux kernel, cgroups, a Dalvik/ART runtime, and a pile of vendor services for GPS, NMEA2000/CAN bridges, sonar, and AIS. When one of these units feels “laggy” — slow chart redraw, sluggish touch response, dropped AIS targets, stutter when overlaying radar — it’s tempting to guess. Brendan Gregg, who wrote Systems Performance and built much of the modern Linux/BPF tracing toolchain, has spent his career arguing against guessing. His USE Method gives a fast, structured way to find the real bottleneck before touching a single setting.

This article maps his methodology onto a generic Android marine MFD, and lists the concrete tools you can actually run against a locked-down head unit — most of which don’t require root.

Why a marine MFD is a good USE Method candidate

A boat MFD is a constrained embedded Android device: fixed CPU/RAM/storage, running one demanding foreground app (the chart/plotter app) plus background services (NMEA sentence parsing, Wi-Fi/Bluetooth for autopilot or radar, GPS fix updates, sometimes video decode for FLIR/thermal cameras). That’s exactly the kind of bounded, resource-constrained system the USE Method was designed for — it was originally built for servers, but Gregg has repeatedly shown it generalizes to “any system,” including consumer hardware, precisely because the method starts from resources and their limits, not from a fixed toolset.

The method, in one line

For every resource, check Utilization, Saturation, and Errors.

The USE Method: for every resource, check utilization, saturation, and errors before touching a single setting.

Utilization — percentage of time the resource was busy (CPU busy %, storage I/O busy %).
Saturation — the degree of extra queued work the resource can’t service (run-queue length, I/O wait queue, memory pressure/swapping).
Errors — error events (dropped packets, storage I/O errors, OOM kills).

Gregg’s insight worth remembering for a boat MFD specifically: a resource that looks fine on a 5-minute average can still saturate in short bursts — e.g., CPU pinned at 100% for two seconds while re-rendering a chart tile — and that burst is exactly what causes the “stutter” or “input lag” you actually feel. Averages hide this; you need per-second (or better) sampling.

Building your MFD’s USE checklist

The resource list for a boat MFD, adapted from Gregg’s generic hardware list:

Resource	Utilization	Saturation	Errors
CPU (cores)	% busy per core	run-queue length / scheduling latency	thermal throttling events
Memory	used vs total RAM	swap activity, low-memory killer (LMK) events	failed allocations, app OOM kills
Internal storage (eMMC/UFS)	% busy, IOPS	I/O wait queue depth	I/O errors, remount-ro events
GPU	frame render time / vsync budget	dropped frames, “janky” frames	GPU driver errors
Wi-Fi/Bluetooth radio	throughput vs link rate	retransmits, connection drops	radio errors, disconnect events
NMEA2000/CAN or serial bus	bus load % (if exposed)	buffer overruns	checksum/parse errors, dropped sentences
GPS/GNSS	fix update rate	fix latency, satellites-in-view drop	fix loss events
Battery/thermal	current draw / thermal headroom	throttling under sustained load	brownout/undervoltage resets

The bus/GPS/thermal rows are boat-specific extensions beyond the standard USE hardware list — MFDs live in a hot, vibrating, power-fluctuating environment that a rack-mounted server doesn’t, so it’s worth treating thermal and power as first-class resources here.

Tools that actually work on a locked-down MFD (no root required)

Marine MFDs typically ship as locked, non-rootable Android builds. The good news: Android’s own developer tooling — reachable over ADB via USB or Wi-Fi debugging — covers most of the USE checklist without root, and is the same instrumentation Google documents for regular app performance work.

Enable ADB access. Most Android MFDs have a hidden developer-options or engineering menu (varies by vendor — commonly reached by tapping the version/build number a few times in Settings, or a manufacturer service menu). Enable USB debugging, connect via adb over USB, or over Wi-Fi with adb tcpip 5555 once the first USB pairing is done.
CPU utilization and saturation — adb shell top -d 1 for a live per-process view; adb shell dumpsys cpuinfo for a load snapshot. For saturation specifically (run-queue/scheduling latency), adb shell cat /proc/loadavg gives you the classic load-average numbers.
Memory — adb shell dumpsys meminfo <package> for a specific app’s Java/native heap, or dumpsys meminfo system-wide. Watch /proc/meminfo’s MemFree, and look at logcat for lowmemorykiller / Low on memory lines — that’s your saturation signal for memory.
Storage I/O — adb shell dumpsys iostats gives an app-centric view; for raw device stats, /proc/diskstats if accessible, otherwise adb shell cat /sys/block/*/stat.
GPU/frame performance — this is usually the actual complaint (“chart redraw is choppy”). adb shell dumpsys gfxinfo <package> framestats reports per-frame timing against the 16.6ms (60fps) or 33ms (30fps) budget — a direct saturation metric for the render pipeline. Android’s Perfetto system trace (record via the on-device Developer Options “System Tracing” tool, or adb shell perfetto) gives a full timeline across CPU scheduling, frame rendering, and binder calls, viewable in the Perfetto UI (ui.perfetto.dev) without needing the device attached afterward.
CPU profiling (deeper drill-down) — simpleperf is AOSP’s non-rootable equivalent of Linux perf, and is what Gregg’s own profiling techniques (CPU flame graphs) rely on upstream. simpleperf record/report works on a debuggable app process without root and can generate the same kind of CPU flame graph Gregg popularized, letting you see exactly which function is burning CPU during a chart repaint.
Network/radio — adb shell dumpsys wifi for link rate/retries, adb shell dumpsys bluetooth_manager for BT link state — useful if your complaint is autopilot/radar/AIS-over-Wi-Fi lag rather than the chart UI itself.
Errors, broadly — adb logcat filtered for ANR, FATAL EXCEPTION, lowmemorykiller, Watchdog, thermal throttling strings — this is your catch-all errors column across every resource row.

None of this requires root; it’s the same toolchain Android app developers use for normal performance work, just pointed at whichever chart-plotter app and system services are running on the MFD.

A practical workflow

Find the bottleneck first, then investigate root cause, then fix — never guess.

Reproduce the “laggy” scenario deliberately (e.g., zoom/pan while radar overlay + AIS + autopilot data are all live) while running top -d 1 and dumpsys gfxinfo <pkg> framestats in two terminals.
Capture a Perfetto system trace across the same window — this gives you the full picture (scheduling, frames, binder IPC) in one place rather than stitching together individual tool outputs.
Apply the checklist: is the CPU pegged (utilization) or just queued (saturation) at the moment of the stutter? Is a specific frame’s render time blowing the 16.6/33ms budget? Any lowmemorykiller or ANR lines in logcat at that timestamp?
Once you’ve localized the resource, drill down: if CPU-bound, simpleperf record during the same scenario and generate a flame graph of exactly what’s consuming cycles.
Only after the systemic bottleneck is identified do you look at fixes — this ordering (find the bottleneck first, then investigate root cause, then fix) is the entire point of Gregg’s method: it prevents the “random change” and “streetlight” anti-patterns he explicitly warns against, where you tune settings that feel obviously wrong without evidence they’re actually the bottleneck.

Where this could go for an application

A natural next step, given everything above, is a small on-device (or companion, ADB-driven) tool that:

Polls /proc/loadavg, dumpsys meminfo, dumpsys gfxinfo framestats, and logcat error patterns on an interval,
Presents them as a live USE-style dashboard (utilization/saturation/errors per resource row, matching the table above),
Flags threshold breaches (e.g., frame time > 16.6ms, load average > core count, lowmemorykiller events) as the USE Method checklist made continuous instead of manual.

That’s effectively a purpose-built USE dashboard for marine MFDs — the same idea Gregg cites others (e.g., Circonus) having built for servers, just retargeted at boat electronics.