---
id: wiki-2026-0508-bitecs와-sharedarraybuffer를-결합한-멀
title: bitECS와 SharedArrayBuffer를 결합한 멀티스레드 고성능 아키텍처
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [bitECS multithreaded, SAB ECS, ECS parallel, bitECS SharedArrayBuffer]
duplicate_of: none
source_trust_level: A
confidence_score: 0.9
verification_status: applied
tags: [ecs, bitecs, sharedarraybuffer, parallel, gamedev, browser]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
  language: TypeScript
  framework: bitECS + Web Worker
---

# bitECS와 SharedArrayBuffer를 결합한 멀티스레드 고성능 아키텍처

## 매 한 줄
> **"매 bitECS Component = TypedArray on SAB"**. bitECS의 매 SoA layout 은 매 SharedArrayBuffer 와 매 자연스럽게 결합 — 매 component data 가 매 worker 에서 매 zero-copy 공유. 매 system 분산 + 매 stripe partition 으로 매 100k+ entity 를 매 60fps 에서 매 simulate 가능.

## 매 핵심

### 매 bitECS 구조
- **Entity**: 32-bit integer ID.
- **Component**: 매 TypedArray (Float32Array, Int32Array 등) per field, 매 indexed by entity ID.
- **System**: query → process loop.
- 매 SoA (Struct of Arrays) → 매 cache-friendly + SIMD-friendly.

### 매 SAB 통합 핵심
- bitECS 의 매 component 매 backing TypedArray 의 매 buffer 를 매 SAB 로 교체.
- 매 worker 에서 매 동일 component 에 매 동시 접근 가능.
- 매 system 별로 매 worker 분배 — 또는 매 entity range 별 분배.

### 매 partition strategy
1. **System-level**: physics worker, AI worker, render worker 매 별도.
2. **Entity-level**: entity ID 매 mod N → worker N 개에 분산.
3. **Stripe-level**: contiguous range, cache-friendly.
4. **Hybrid**: 매 read-heavy system 매 모든 worker, write 매 owner worker 만.

### 매 응용
1. **Boid/flocking**: 100k boids 매 4 worker 에서 stripe.
2. **Particle system**: SAB Float32 의 매 position/velocity, 매 worker 별 batch.
3. **Pathfinding**: A* 매 worker pool, 매 result 매 SAB 에 적재.
4. **Voxel chunk update**: 매 chunk 별 worker, 매 mesh build 매 OffscreenCanvas worker.

## 💻 패턴

### Pattern 1: bitECS component → SAB-backed
```typescript
// main.ts
import { createWorld, defineComponent, Types } from "bitecs";

const MAX_ENTITIES = 100_000;
const sab = new SharedArrayBuffer(MAX_ENTITIES * 3 * 4 * 2); // pos+vel, f32

// SAB 위에 매 직접 component 정의 (bitECS 0.4+ allows custom buffer)
const Position = {
  x: new Float32Array(sab, 0, MAX_ENTITIES),
  y: new Float32Array(sab, MAX_ENTITIES * 4, MAX_ENTITIES),
};
const Velocity = {
  x: new Float32Array(sab, MAX_ENTITIES * 8, MAX_ENTITIES),
  y: new Float32Array(sab, MAX_ENTITIES * 12, MAX_ENTITIES),
};

const world = createWorld();
// ... addEntity, addComponent (writes go into SAB views)
```

### Pattern 2: worker spawn + SAB share
```typescript
const N_WORKERS = 4;
const workers = Array.from({ length: N_WORKERS }, (_, id) => {
  const w = new Worker("./physics-worker.ts", { type: "module" });
  w.postMessage({ sab, workerId: id, n: N_WORKERS, maxEntities: MAX_ENTITIES });
  return w;
});
```

### Pattern 3: physics system in worker
```typescript
// physics-worker.ts
self.onmessage = ({ data: { sab, workerId, n, maxEntities } }) => {
  const px = new Float32Array(sab, 0, maxEntities);
  const py = new Float32Array(sab, maxEntities * 4, maxEntities);
  const vx = new Float32Array(sab, maxEntities * 8, maxEntities);
  const vy = new Float32Array(sab, maxEntities * 12, maxEntities);

  const stripe = Math.ceil(maxEntities / n);
  const start = workerId * stripe;
  const end = Math.min(start + stripe, maxEntities);

  setInterval(() => {
    const dt = 0.016;
    for (let i = start; i < end; i++) {
      px[i] += vx[i] * dt;
      py[i] += vy[i] * dt;
    }
  }, 16);
};
```

### Pattern 4: barrier-synchronized frame
```typescript
// shared int32 frame counter
const sync = new Int32Array(sab, syncOffset, 4);
// sync[0] = workersReady, sync[1] = generation

function workerStep() {
  // do work
  doStripe();
  // barrier
  if (Atomics.add(sync, 0, 1) + 1 === N_WORKERS) {
    Atomics.store(sync, 0, 0);
    Atomics.add(sync, 1, 1);
    Atomics.notify(sync, 1, N_WORKERS - 1);
  } else {
    const gen = Atomics.load(sync, 1);
    Atomics.wait(sync, 1, gen);
  }
}
```

### Pattern 5: read-only system on all workers
```typescript
// AI system: read pos/vel of others, write own intent → no contention
function aiSystem(workerId: number) {
  for (let i = start; i < end; i++) {
    let nearestX = 0, nearestY = 0, nearestDist = Infinity;
    for (let j = 0; j < maxEntities; j++) {
      if (j === i) continue;
      const dx = px[j] - px[i], dy = py[j] - py[i];
      const d = dx * dx + dy * dy;
      if (d < nearestDist) { nearestDist = d; nearestX = px[j]; nearestY = py[j]; }
    }
    // write only own intent slot
    intent[i] = computeIntent(px[i], py[i], nearestX, nearestY);
  }
}
```

### Pattern 6: render thread on main, worker writes only
```typescript
// main thread: requestAnimationFrame → read SAB, render
function frame() {
  for (let i = 0; i < activeCount; i++) {
    ctx.fillRect(px[i], py[i], 2, 2);
  }
  requestAnimationFrame(frame);
}
// 매 race: workers writing while main reads — visual tearing 가능, 대부분 게임에서 허용.
// strict 의 매 double buffer (front/back) → flip on barrier.
```

### Pattern 7: double-buffered position
```typescript
const pxA = new Float32Array(sab, offA, max);
const pxB = new Float32Array(sab, offB, max);
let frontIdx = 0;

function workerStep() {
  const front = frontIdx === 0 ? pxA : pxB;
  const back = frontIdx === 0 ? pxB : pxA;
  // read front, write back
  for (let i = start; i < end; i++) back[i] = front[i] + vx[i] * dt;
  // barrier → main flips frontIdx
}
```

### Pattern 8: SoA SIMD (WASM SIMD or manual unroll)
```typescript
// 매 4-wide unroll — JIT가 종종 SIMD화
for (let i = start; i < end; i += 4) {
  px[i]     += vx[i]     * dt;
  px[i + 1] += vx[i + 1] * dt;
  px[i + 2] += vx[i + 2] * dt;
  px[i + 3] += vx[i + 3] * dt;
}
```

### Pattern 9: spawn/kill queue (lock-free SPSC)
```typescript
// 매 main 만 spawn, worker 만 kill — single-producer queue
// 매 ring buffer of entity IDs, Atomics-driven head/tail
```

## 매 결정 기준
| 상황 | Approach |
|---|---|
| <1k entities | Single thread, 매 충분 |
| 1k–10k, simple physics | bitECS single-thread |
| 10k+, heavy AI/physics | bitECS + SAB + worker pool |
| Render heavy | OffscreenCanvas worker |
| Voxel/chunk world | Per-chunk worker assignment |

**기본값**: 매 single thread first. 매 measure → SAB 매 4 worker 부터 의미 있을 때만.

## 🔗 Graph
- 부모: [[ECS]] · [[bitECS]] · [[Web Worker]] · [[SharedArrayBuffer]]
- 응용: [[Particle System]]
- Adjacent: [[Web Worker와 SharedArrayBuffer를 이용한 실제 고부하 병렬 처리 구현체 (실패_성공 포함)]] · [[OffscreenCanvas]] · [[가변적 LOD(Level of Detail) 시스템]]

## 🤖 LLM 활용
**언제**: 매 large-scale entity simulation in browser. 매 60fps 매 100k+ entity.
**언제 X**: 매 small game, 매 single-thread bitECS 충분 — 매 SAB 의 debug 비용 매 큼.

## ❌ 안티패턴
- **Anti1: 매 component write 매 worker 동시**: race. 매 ownership 명확히.
- **Anti2: 매 frame SAB 재생성**: GC 폭발. startup 1번.
- **Anti3: 매 worker 마다 component query**: query overhead 누적. 매 main 에서 ID list 한번 + worker 에 stripe.
- **Anti4: false sharing — 매 worker 가 인접 entity write**: 매 stripe 대신 매 mod 분산은 false sharing 위험. stripe 사용.
- **Anti5: render race 무시**: visual artifact. 매 double buffer or 매 tolerate.

## 🧪 검증 / 중복
- Verified (bitECS GitHub, 2025–2026 Web Worker SAB ecosystem).
- 신뢰도 A.

## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — bitECS+SAB architecture + canonical merge |