WebGPU unlocks GPU compute in the browser, but async/await patterns are poorly documented. Here's the definitive guide.

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A deep-dive into WebGPU's async concurrency model for compute shaders, covering four battle-tested patterns with full working code and benchmark data. The guide explains WebGPU's three-timeline model (Content, Device, Queue), demonstrates why naively awaiting every GPU operation leaves the GPU idle ~60% of the time, and shows how to fix it. Key patterns include: double-buffering staging buffers for pipeline parallelism (~1.7x speedup), encoding dependent passes into a single command buffer (~2.1x speedup), batching independent workloads with a single submit call (~1.9x speedup), and using pushErrorScope/popErrorScope plus device.lost handlers for production resilience. Benchmarks were run on M2 MacBook Pro, RTX 4070, and Pixel 8 Pro. Also covers timestamp queries for GPU profiling, common pitfalls like workgroup size mismatches and missing buffer usage flags, and WGSL shader examples.

The WebGPU Concurrency Guide: Mastering Async Compute Shaders

How to Master WebGPU Async Compute Shader Patterns

Understanding WebGPU's Three-Timeline Concurrency Model

Pattern 1: Basic Async Compute Dispatch and Readback

Pattern 2: Overlapping Submissions for Pipeline Parallelism

Pattern 3: Multi-Pass Compute with Dependency Graphs

Pattern 4: Error Scopes and Async Error Recovery

Performance Benchmarks: Measuring What Matters