| # ExecuTorch Wasm + WebGPU runtime |
|
|
| `executorch_wasm_lib.js` and `executorch_wasm_lib.wasm` are the ExecuTorch Wasm |
| bindings (`extension/wasm`) with the WebGPU backend, linked into one web bundle. |
| The `.js` loader ships in this folder. The `.wasm` is hosted on Hugging Face |
| (`executorch-community/ExecuTorch-WebGPU-Runtime`, pinned in `src/config/runtime.js`), |
| downloaded and checked against the sha256 below like a model file. |
| Every demo in the playground shares this one runtime (`src/runtime/executorch.js`). |
| The JS file defines `createExecuTorch()`. After `await et.initWebGPU()`, a `.pte` |
| loads with `et.Module.load(path)` and `loadMethod('forward')`, and runs with an |
| async `forward([tensors])`. |
|
|
| ## Source |
|
|
| Built from the ExecuTorch source tree of 2026-10-16 (`version.txt` 1.6.0) with the two |
| changes that make WebGPU run in the Wasm build, both merged upstream: |
|
|
| 1. pytorch/executorch#23938: the `EXECUTORCH_BUILD_WASM_WEBGPU` option, which links the |
| WebGPU backend into `extension/wasm`, and the `initWebGPU()` binding. |
| 2. pytorch/executorch#23914: `WebGPUGraph::propagate_resize` resizes every operand before |
| its consumer in one pass, so a multi-token LLM prefill works. |
|
|
| A build from ExecuTorch main that contains both, with the commands below, should give the |
| same files. The emdawnwebgpu override (`EXECUTORCH_WEBGPU_EMDAWNWEBGPU_PORT`) was only |
| needed because the build machine could not reach GitHub; without it, Emscripten downloads |
| the same emdawnwebgpu version itself. |
|
|
| ## Toolchain |
|
|
| - Emscripten 4.0.19, official release build `8b01e2ec3f33e6b94842096d7312ce4ef5f33f6c`. |
| - emdawnwebgpu v20251002.162335, the version Emscripten 4.0.19 pins. It was rebuilt |
| from Dawn source at `01940842b667a7812d0e4ca0ef4367fbec294241`, using Dawn's |
| own packaging recipe. |
| - CMake 3.31, Ninja 1.13. The configure step needs a Python with `torch` |
| (for `torchgen`). |
|
|
| ## Build |
|
|
| A small consumer project links the bindings into a distributable bundle, as |
| described under "Building for Web" in `extension/wasm/README.md`: |
|
|
| ```cmake |
| cmake_minimum_required(VERSION 3.29) |
| project(executorch_web) |
| add_subdirectory(${ET_SRC} executorch) |
| add_executable(executorch_wasm_lib) |
| target_link_libraries(executorch_wasm_lib PRIVATE executorch_wasm) |
| target_link_options(executorch_wasm_lib PRIVATE |
| -sMODULARIZE=1 -sEXPORT_NAME=createExecuTorch -sENVIRONMENT=web,worker |
| -sFORCE_FILESYSTEM=1 -sEXPORTED_RUNTIME_METHODS=FS -sINITIAL_MEMORY=64MB |
| -sEXPORT_EXCEPTION_HANDLING_HELPERS=1) |
| ``` |
|
|
| ```bash |
| emcmake cmake -S <consumer project> -B build -G Ninja -DCMAKE_BUILD_TYPE=Release \ |
| -DET_SRC=<executorch> \ |
| -DEXECUTORCH_BUILD_WASM=ON -DEXECUTORCH_BUILD_WEBGPU=ON -DEXECUTORCH_BUILD_WASM_WEBGPU=ON \ |
| -DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON -DEXECUTORCH_BUILD_EXTENSION_FLAT_TENSOR=ON \ |
| -DEXECUTORCH_BUILD_EXTENSION_MODULE=ON -DEXECUTORCH_BUILD_EXTENSION_NAMED_DATA_MAP=ON \ |
| -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \ |
| -DEXECUTORCH_ENABLE_LOGGING=ON -DEXECUTORCH_LOG_LEVEL=Info \ |
| -DEXECUTORCH_WEBGPU_EMDAWNWEBGPU_PORT=<emdawnwebgpu_pkg>/emdawnwebgpu.port.py \ |
| "-DCMAKE_C_FLAGS=-ffile-prefix-map=<executorch>=executorch" \ |
| "-DCMAKE_CXX_FLAGS=-ffile-prefix-map=<executorch>=executorch" \ |
| -DPYTHON_EXECUTABLE=<python with torch> |
| cmake --build build --target executorch_wasm_lib |
| ``` |
|
|
| The WebGPU Wasm option itself adds `-sASYNCIFY -sASYNCIFY_STACK_SIZE=65536 |
| -sALLOW_MEMORY_GROWTH=1 -sMAXIMUM_MEMORY=4GB -fexceptions`. The full portable |
| kernel library is linked (no selective build). Logging is at Info, so a failed |
| load or run prints the reason to the console. `-ffile-prefix-map` keeps |
| build-machine paths out of the binary. |
| |
| ## Files |
| |
| | File | Bytes | sha256 | |
| |---|---:|---| |
| | `executorch_wasm_lib.js` | 165,877 | `8a631b1537927f8f2ef184d9f1b343061f47df0a32ddb8f5190d74e80d40618e` | |
| | `executorch_wasm_lib.wasm` | 6,562,188 | `35a9087d0b6cd86c279e7111adfd54a58156bd993928b20f63348f1043652eb4` | |
| |
| ## Checked with this build |
| |
| Headless Chromium 141, WebGPU on SwiftShader (no `shader-f16`), with the |
| playground's models compared against ExecuTorch CPU references: |
| |
| - Depth Anything V2 Small, MODNet, Real-ESRGAN, D-FINE S: max abs difference |
| between 0 and 4.6e-3. |
| - SAM 2.1 Hiera Tiny: mask IoU 1.000 on a click, a second click, and a box prompt. |
| |
| The playground's own end-to-end checks, through the real UI, cover Qwen3 0.6B, |
| Llama 3.2 1B, SAM 2.1, Depth Anything V2, D-FINE S and Whisper base. Real GPUs |
| and the `shader-f16` kernel paths have not been tested with this build. |
| |
