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Denshin Team reduced the time its PixiJS map displayed the “RENDERING MAP” overlay from 33.9 seconds to 3.0 seconds, and cut total time until the map was up from 38.7 seconds to 7.8 seconds. In the team’s production-build test, throttled to 1.6 Mbps and 6× CPU slowdown, bytes transferred before the first frame fell from 6.9 MB to 1.0 MB. The biggest change was not a rendering trick: it was keeping oversized, nonessential images out of the work that had to finish before the first frame, then controlling how deferred assets arrived.
These are results reported by Denshin Team for its DENSHIN live city map, not an independently reproduced benchmark. The distinction between the overlay time and total time matters: the map appeared sooner, while additional content continued loading afterward.
What was slowing the first frame?
The DENSHIN map is a 10 × 10 city grid with roads, vehicles, planes, and other players, built with PixiJS v8. In an earlier production load, the team reported 35.7 seconds before the map appeared, with 203.7 MB transferred across 309 requests. Of that transfer, 196.1 MB came from 62 PNG block images included in the awaited Assets.load() path.
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How did the team reduce bytes before drawing?
Resize and re-encode block art
The team resized block images for their displayed size, re-encoded opaque art as WebP, and prepared a smaller 512-pixel image set for phones. It reported that the desktop set was reduced to 16.6 MB from the original image set, while the phone set was 4.6 MB. Those are asset-set sizes, not the bytes required before the first frame: the block images were registered but removed from the bulk load that the map awaited.
To avoid an empty-looking city while the real block art streamed in, the team used a shared blurred placeholder of 494 bytes. This let the initial map draw without waiting for each detailed block image.
Remove assets that cannot contribute to the initial view
Some bytes were not just too large; they were unnecessary. The team found 2.7 MB of asphalt debris was being downloaded for renderers disabled on phones. It also found that an eager import.meta.glob included assets behind a disabled code path. One unused block set added 70 MB across 337 files to the distribution. A build flag did not remove those imported files in this setup, so the team removed the eager inclusion rather than relying on the flag.
It also removed manhole-cover images around 1,000 pixels wide even though they appeared at only 6–9 pixels on screen. The practical check is to compare an asset’s source dimensions and transfer cost with its actual on-screen use—and verify that disabled features are not still pulling their assets into the bundle or load path.
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Why did deferred loading need an order?
Moving assets out of the initial awaited load was not enough. When the team first deferred the nonessential work, it competed with visible content for bandwidth. Denshin Team then organized the work into sequential waves, starting each after the previous wave completed:
- Essential road markings and overlays: await 324 KB so the city can be drawn.
- Traffic and population assets: load 1.1 MB of cars, planes, players, and related content.
- Block art: stream images with blocks nearest the screen prioritized.
- Desktop debris: load 2.7 MB of asphalt debris.
With this sequencing, the team reported that traffic finished at 11.7 seconds instead of 21.8 seconds under the same 1.6 Mbps throttle. Population loading was started without making initialization wait for all four waves. The implementation waited two animation frames before starting deferred work, checked that the page was still active before applying late results, and gave the art wave a 45-second deadline. These are choices from this implementation, not PixiJS requirements.
Prioritize nearby art without flooding the device
The block streamer sorted pending images by distance from the screen center, checked for work every 140 ms, and capped concurrent loads at four on desktop and two on phones. After 2.5 seconds, it removed the viewport-only filter and continued loading outward. This put likely-to-be-seen detail first while limiting concurrent work; other maps should tune such limits against their own network, device, and visual priorities.
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What did the reported before-and-after measure?
Denshin Team’s headline improvement refers to the duration of the “RENDERING MAP” overlay, not the time until every desired asset had loaded. The team’s production-build test used 1.6 Mbps network throttling and 6× CPU slowdown. The measurements are attributed to Denshin Team (2026); they are not an independent benchmark.
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| Measure | Before | After | What it represents |
|---|---|---|---|
| “RENDERING MAP” overlay duration | 33.9 seconds | 3.0 seconds | Time associated with the map-rendering overlay in the team’s stated test. |
| Total time until the map was up | 38.7 seconds | 7.8 seconds | The broader time-to-map figure reported by the team. |
| Bytes before the first frame | 6.9 MB | 1.0 MB | Transfer required before the first frame in the stated test. |
| Traffic completion after changing load order | 21.8 seconds | 11.7 seconds | Team-reported result under the same 1.6 Mbps throttle. |
These figures describe different stages and should not be collapsed into a single “load time.” A useful comparison records both first visible output and when the desired content is present, along with bytes and requests awaited before first paint versus total transfer afterward.
How did the team avoid texture and GPU-memory failures?
Do not unload a texture and assume its alias can safely reload
An earlier version called Assets.unload() when a block left view. On return, loading the same alias could produce a cached texture object whose GPU source had already been destroyed; the team saw a batcher crash involving a null alphaMode. It removed that eviction behavior and added a check for a missing or destroyed texture source. Its approach was to control memory through texture size and count rather than unloading and reusing those texture objects.
Estimate render-target cost before creating world-sized textures
The team reported mobile tab termination after creating world-sized render textures of roughly 14,848 × 14,848 pixels. Using its four-bytes-per-pixel estimate, that is about 0.8 GB per target and about 2.5 GB for three targets combined. This is approximate accounting for the described render targets, not a universal measurement of actual GPU memory use.
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How should device capability affect quality?
Denshin Team’s low-power tier used reported navigator.deviceMemory when available, together with a coarse pointer and short-screen-side condition. In that implementation, the tier selected smaller block art, avoided mipmaps, applied a matching zoom cap, and skipped world-sized bakes.
The team learned not to use that tier to remove visible features. It had previously disabled headlight beams and locked-block effects on phones, and users reported the missing effects as bugs. The revised distinction was to let capability select lighter assets, while measured frame time—not a broad device label—governed performance-driven changes to effects.
Use sustained frame-time evidence for effects
In interleaved mobile-emulation runs at 4× CPU slowdown, the team reported that beams raised p95 frame time from 18.5 ms to about 32 ms; at 1× CPU slowdown it saw no cost. It kept the beams. For locked-block effects, it now steps down only when median frame time stays above 24 ms for three seconds.
An earlier rule triggered when p95 exceeded 14 ms, which the team found happened in every session despite a reported healthy session with p50 of 16.7 ms and p95 of 17.6 ms. The case illustrates why a threshold must match the statistic and behavior it is meant to detect: an always-triggering threshold cannot distinguish a real sustained slowdown from normal frame-time variation.
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Which apparent loading bugs were not network bottlenecks?
Mipmap configuration caused a texture re-upload
Setting a mipmap option after Assets.load() had resolved triggered a full re-upload of a live 1,152-square texture. The team fixed it by passing upload options with the asset source, rather than changing the option afterward.
A blur filter clipped content while panning
A half-resolution blur filter without an explicit filterArea clipped part of a locked block during panning. The team isolated the cause by inspecting bounds and disabling the mask, overlay, and blur in turn. When visible content is clipped, checking filter bounds and isolating rendering layers can be more useful than assuming the asset failed to load.
Repeated map fragments created too many WebGL contexts
The landing page had eight live map fragments, each creating a WebGL context. In an emulated iPhone 13 scroll-down-and-back test, the team reported 51 contexts and a JavaScript heap of 254 MB, after which iOS began killing tabs. It kept the hero live and replaced the other seven fragments with still images generated from the same renderer and seed; the described scroll then created three contexts. These are observations from the team’s emulation setup, not measurements from a set of physical phones.
How should you validate a similar optimization?
The team recommends testing a production build with network and CPU throttling: localhost can hide transfer time and latency-related memory behavior. It also reported that its test rig could drift by as much as 2× between batches, so it interleaved frame-time runs rather than trusting separate batches as directly comparable. No raw dataset, independent replication, or controlled comparison across named physical phones is included in the reported account.
Quick Recap
- Separate milestones: record time to first visible map and time until the intended content is present.
- Separate transfer categories: track bytes and requests awaited before first paint as well as total bytes eventually downloaded.
- Separate bottlenecks: test network-constrained loading and CPU-constrained frame time independently.
- Account for graphics memory: estimate texture and render-target cost from dimensions and count before creating large targets.
- Check feature parity: confirm that device tiers change asset cost without silently removing expected visible behavior.
- Use the right frame-time signal: distinguish sustained median slowdown from tail spikes before stepping down effects.
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