acdream/docs/plans/2026-05-10-perf-tiers-2-3-roadmap.md

Performance Tiers 2 + 3 — Future Roadmap

Created: 2026-05-10 during Phase A.5 polish. Status: Future planning — not for current execution. Context: A.5 shipped two-tier streaming with the entity dispatcher landing at ~3.5ms median (post-Bug-A and Bug-B fixes). Tier 1 (entity-classification cache) lands as A.5 polish and brings the dispatcher inside the 2.0ms spec budget. Tiers 2 + 3 are the "next big perf wins" beyond Tier 1.

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Background — why this exists

Discussion captured 2026-05-10: user observed 200-240 FPS at radius=12 on a Radeon 9070 XT @ 1440p and asked why an "old game like AC" doesn't deliver Unreal-level (1000+ FPS) on this hardware.

The honest answer: the bottleneck is architectural, not hardware. The CPU is single-threaded and rebuilds the entire draw plan from scratch every frame. Modern engines pre-bake static-world batches at content-cook time and rebuild only what changes.

AC's design — server-spawned per-entity world streamed at runtime — doesn't naturally batch the way Unreal's pre-cooked content does. Closing the gap requires backporting modern techniques while preserving AC's data model. Tiers 2 and 3 are that backporting work.

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Tier 2 — Static/dynamic split with persistent groups

Estimated effort: ~10-15 days (2-week phase). Estimated win: entity dispatcher ~3.5ms → ~0.5-1ms median at radius=12. Total frame time: ~4-5ms → ~2-3ms = 400-600 FPS at standstill.

The core idea

Today, WbDrawDispatcher._groups (the dictionary of "(mesh + texture + blend) → list of instances to draw") is cleared and rebuilt from scratch every frame.

For trees, rocks, buildings, and other static entities (~95% of the world), the answer is identical every frame forever. Tier 2 makes the static-group instance buffers persistent GPU-resident data, just like Unreal's pre-baked world. The CPU only orchestrates "which groups are visible" per frame.

Architectural shift

class StaticInstancedGroup
{
    public GroupKey Key;
    public Matrix4x4[] Matrices;          // grown as entities spawn
    public BitArray ActiveSlots;          // for free-list reuse
    public bool NeedsGpuUpload;           // dirty flag for delta upload
    public Dictionary<uint, int> EntityToSlot;   // for despawn lookup
    public uint InstanceBufferOffset;     // start of group's slice in global SSBO
}

On entity spawn (atlas-tier static): allocate a slot in each relevant group, write the matrix, mark dirty.

On entity despawn: free the slot, mark dirty.

Per frame:

• Static groups: LB-cull each group (cheap). For visible groups, flag for draw. No matrix copy. No list rebuild.
• Dynamic entities (~50 NPCs/players): today's per-frame walk-and-classify. Keeps the existing slow path for things that legitimately change every frame.
• Upload only the dirty groups' matrix slices (delta upload, not full reupload).
• Issue 2 multi-draw-indirect calls.

Sub-decisions

Frustum cull granularity at the group level: at group level you can't reject individual instances; you draw the whole group or none of it. Two strategies:

• Per-LB subgroups: split each group into per-landblock subgroups. LB-frustum-culls reject subgroups whose LB is invisible. ~2K groups × ~5 LBs per group on average = ~10K subgroups. Each subgroup AABB cull is ~0.3 µs → ~3 ms per frame. Roughly a wash with today's per-entity cull.
• Per-instance GPU cull (Tier 3): compute pre-pass on the GPU writes which instances are visible to a draw-indirect buffer. ~0.05ms CPU. The right long-term answer.

For Tier 2 alone, per-LB subgroups are the recommended approach — keep CPU culling, just at coarser granularity than per-entity.

Dynamic entities crossing LB boundaries: when an NPC walks across a landblock boundary, it stays in the same group key but its "spatial bucket" changes. Solution: dynamic entities are tracked in a single global "dynamic group" outside the per-LB structure; they don't need spatial bucketing because there are only ~50 of them.

Palette override invalidation: server event swaps an NPC's clothing color → group key changes. Treat as despawn-from-old + spawn-into-new. NPCs are dynamic so this just rebuckets them.

Animation overrides on static entities: static entities don't animate. Trees don't bend (foliage wave is a vertex shader effect, not a group-key change). Buildings don't move. So the static path never invalidates.

EnvCell visibility: dungeon entities are gated by per-cell visibility state. Need to track which group instances are tied to which cell, and during visibility cull, gate per-cell. Keep using existing ParentCellId field on WorldEntity.

Streaming load/unload integration: when an LB unloads, all its static entity matrices need to be removed from their groups. Free-list management. Matches existing LandblockSpawnAdapter lifecycle.

Effort breakdown

Task	Days
Design + invariants document	2
Spawn-time slot allocator + free-list	3
Per-frame visibility + dirty-flag delta upload	2
Dynamic entity path (NPCs, projectiles)	2
Invalidation (palette/ObjDesc events)	2
EnvCell visibility integration	1
Streaming load/unload integration	1
Conformance testing	2-3
Total	~10-15 days

Risks

• Slot management bugs = double-frees or leaks (entities draw at random positions — visible).
• Invalidation bugs = stale matrices (entity teleports back to spawn point when palette changes).
• Dynamic entity tracking adds complexity around the static/dynamic boundary.

Mitigations

• Conformance test: render a fixed scene through both pipelines, compare draw output. Adds CI infrastructure.
• Per-frame validation in debug: walk all groups, assert no orphan slots.
• Hash invariant test: static entities should produce stable group keys frame-over-frame. Add a debug assertion that fires once per frame in Debug builds.

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Tier 3 — GPU-side culling (compute pre-pass)

Estimated effort: ~1 month (longer phase). Estimated win: entity dispatcher ~0.5-1ms (post-Tier-2) → ~0.05ms median. Total frame time: ~2-3ms → ~1.5-2ms = 600-1000+ FPS at standstill.

The core idea

Today (and after Tier 2), the CPU does per-LB or per-subgroup frustum culling and tells the GPU which groups to draw.

Tier 3 moves per-instance frustum cull to the GPU via a compute shader pre-pass. The CPU just uploads "here are all 1M instance matrices" once; the GPU compute shader writes which ones are visible to a draw-indirect buffer; the rasterizer draws only those.

This is the level Unreal is at. With this, per-frame CPU work for the entity dispatcher becomes essentially "tell the GPU what to do" + a tiny scratch upload.

Why Tier 3 needs Tier 2 first

Without Tier 2's persistent group structure, GPU culling has nothing stable to operate on. The compute shader needs an addressable "here are the static instances" buffer to read from; that buffer only exists after Tier 2.

Sub-decisions to be made

Compute shader API: OpenGL 4.3+ compute shaders are sufficient. We're already at GL 4.3+ for bindless. No additional capability requirement.

Indirect draw command generation: the compute shader writes a DrawElementsIndirectCommand[] buffer per pass. Render thread issues glMultiDrawElementsIndirect reading from that buffer. No CPU readback.

LOD selection: opportunity to add per-instance LOD selection in the compute shader (distance-based mesh detail). Not needed for A.5's scope; could be a Tier 4 follow-up.

Per-light shadow map culling: if shadows ship, GPU culling extends naturally to per-light frustum cull. Significant win for shadow rendering.

Effort breakdown

Task	Days
Compute shader design + GLSL implementation	4
Buffer layout coordination with Tier 2	2
Silk.NET compute dispatch integration	3
Indirect command compaction logic	4
LOD selection (optional, ~stretch)	4
Validation: per-instance cull matches CPU cull within epsilon	3
Conformance + regression testing	5
Total	~21-25 days, ~1 month

Risks

• GPU stalls if the compute shader takes longer than expected (esp. on lower-end GPUs).
• Sync overhead between compute pre-pass and rasterizer pass.
• Debugging difficulty — GPU compute bugs are harder to diagnose than CPU bugs.

Mitigations

• Profile-driven design: measure compute shader runtime on target hardware before committing.
• Fallback path: keep CPU cull as a runtime-toggleable option (env var) so we can A/B compare.
• GPU debugging tools: RenderDoc captures + frame-by-frame compute shader inspection.

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When to schedule these

Tier 2:

• Best fit: dedicated 2-week phase after a SHIP cycle. Treat it like a Phase B/C/N (i.e., name it Phase A.6 or N.7).
• Trigger: user wants to push radius beyond 12 (e.g., to 15 or 20 for true continent-scale horizon).
• Trigger: user wants to add 100+ active NPCs in a city without dropping below 240Hz.

Tier 3:

• Best fit: after Tier 2 has been live and stable for at least one cycle.
• Trigger: shadow map work begins (GPU cull + shadow cull share the same compute pre-pass infrastructure).
• Trigger: user wants 500+ FPS sustained for very-high-refresh scenarios (360Hz monitors, future hardware).

Both:

• Don't bundle with other phases. These are dedicated perf phases with their own brainstorm + spec + plan + SHIP cycles.

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What's "free" or smaller (out of Tier 1/2/3 scope but worth noting)

• Plumb JobKind properly through BuildLandblockForStreaming (~30 min). Today's Bug A patch wastes worker-thread CPU on hydration that gets thrown away for far-tier. Cleaner code, slight CPU savings on worker.
• Eliminate ToEntries adapter allocation in Draw (~15 min). Tiny win (~25 KB / frame). Could fold into Tier 1.
• Persistent-mapped indirect buffer (~2 days). Today's glBufferData per frame becomes a pre-mapped persistent buffer. Marginal win on RDNA 4; meaningful on lower-end GPUs.
• Multi-thread mesh-build worker pool (~1 day). 2.7s first-traversal horizon-fill drops to 0.7s with 4 workers. UX win on first walk-into-region.

These are good candidates for a "perf polish" mini-phase or to backfill into Tier 2.

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The architectural ceiling

Even with all three tiers, a faithful AC client written in C# with bindless OpenGL tops out around 800-1500 FPS at radius=12 on RDNA 4 hardware. Beyond that requires:

• Native C++ rendering core (eliminate .NET GC + JIT overhead)
• DX12/Vulkan API (eliminate driver state validation)
• Offline content cooking (eliminate runtime mesh/texture decode)

Each of those is a several-month undertaking and represents "becoming a different engine." The realistic target for acdream is 240-500 FPS at the user's monitor refresh, comfortably ahead of the visible-stutter threshold. Tier 1 + Tier 2 alone should deliver that for radius=12-15.

For "Unreal-level FPS at full quality," that's a different project.