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Merged
merged 9 commits into from
Oct 29, 2025
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docs: TypeGPU functions #1793

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e468491
Start wotk on better docs for JS Kernels
iwoplaza Oct 8, 2025
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More work on the docs
iwoplaza Oct 9, 2025
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Merge branch 'main' into docs/js-kernels
iwoplaza Oct 16, 2025
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More docs
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Merge branch 'main' into docs/js-kernels
iwoplaza Oct 29, 2025
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iwoplaza Oct 29, 2025
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Merge branch 'main' into docs/js-kernels
iwoplaza Oct 29, 2025
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5 changes: 0 additions & 5 deletions apps/typegpu-docs/astro.config.mjs
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Original file line number Diff line number Diff line change
Expand Up @@ -131,11 +131,6 @@ export default defineConfig({
label: 'Functions',
slug: 'fundamentals/functions',
},
{
label: 'TGSL',
slug: 'fundamentals/tgsl',
badge: { text: 'new' },
},
{
label: 'Pipelines',
slug: 'fundamentals/pipelines',
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6 changes: 3 additions & 3 deletions apps/typegpu-docs/package.json
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Expand Up @@ -50,10 +50,10 @@
"remeda": "^2.21.2",
"sharp": "^0.34.2",
"starlight-blog": "^0.23.2",
"starlight-typedoc": "^0.21.4",
"starlight-typedoc": "^0.19.0",
"tinybench": "^3.1.0",
"typedoc": "^0.28.13",
"typedoc-plugin-markdown": "^4.3.0",
"typedoc": "^0.27.9",
Comment on lines +53 to +55
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Is there a particular reason for this change?

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There is, the newer versions of these packages didn't generate any API Reference docs, but they also didn't fail the nr build command.

"typedoc-plugin-markdown": "4.3.0",
"typegpu": "workspace:*",
"typescript": "catalog:types",
"unplugin-typegpu": "workspace:*",
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50 changes: 20 additions & 30 deletions apps/typegpu-docs/src/content/docs/fundamentals/buffers.mdx
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Expand Up @@ -195,7 +195,7 @@ Since the buffer is already created, you are responsible for the buffer's lifecy

## Writing to a buffer

To write data to a buffer, you can use the `.write(value)` method. The typed schema enables auto-complete as well as static validation of this
To write data to a buffer from the CPU, you can use the `.write(value)` method. The typed schema enables auto-complete as well as static validation of this
method's arguments.

```ts twoslash
Expand Down Expand Up @@ -285,7 +285,7 @@ backupParticleBuffer.copyFrom(particleBuffer);

## Reading from a buffer

To read data from a buffer, you can use the `.read()` method.
To read data from a buffer on the CPU, you can use the `.read()` method.
It returns a promise that resolves to the data read from the buffer.

```ts twoslash
Expand Down Expand Up @@ -348,32 +348,25 @@ import * as d from 'typegpu/data';

const root = await tgpu.init();
// ---cut---
const pointsBuffer = root
.createBuffer(d.arrayOf(d.vec2i, 100))
.$usage('storage');

const bindGroupLayout = tgpu.bindGroupLayout({
points: { storage: d.arrayOf(d.vec2i, 100), access: 'mutable' },
const layout = tgpu.bindGroupLayout({
points: { storage: d.arrayOf(d.vec2i), access: 'mutable' },
});

const bindGroup = root
.createBindGroup(bindGroupLayout, { points: pointsBuffer });

const mainCompute = tgpu['~unstable'].computeFn({
in: { gid: d.builtin.globalInvocationId },
workgroupSize: [1],
})((input) => {
const pipeline = root['~unstable'].createGuardedComputePipeline((x) => {
'use gpu';
// Access and modify the bound buffer via the layout
bindGroupLayout.$.points[input.gid[0]] = d.vec2i(1, 2);
layout.$.points[x] = d.vec2i(1, 2);
});

const pipeline = root['~unstable']
.withCompute(mainCompute)
.createPipeline();
const pointsBuffer = root
.createBuffer(d.arrayOf(d.vec2i, 100))
.$usage('storage');

const bindGroup = root.createBindGroup(layout, {
points: pointsBuffer
});

pipeline
.with(bindGroupLayout, bindGroup)
.dispatchWorkgroups(100);
pipeline.with(bindGroup).dispatchThreads(100);
```

### Using fixed resources
Expand All @@ -394,18 +387,15 @@ import * as d from 'typegpu/data';

const root = await tgpu.init();
// ---cut---
const pointsBuffer = root.createMutable(d.arrayOf(d.vec2i, 100));
const pointsMutable = root.createMutable(d.arrayOf(d.vec2i, 100));

const mainCompute = tgpu['~unstable'].computeFn({
in: { gid: d.builtin.globalInvocationId },
workgroupSize: [1],
})((input) => {
const pipeline = root['~unstable'].createGuardedComputePipeline((x) => {
'use gpu';
// Access and modify the fixed buffer directly
pointsBuffer.$[input.gid[0]] = d.vec2i();
pointsMutable.$[x] = d.vec2i();
});

const pipeline = root['~unstable'].withCompute(mainCompute).createPipeline();
pipeline.dispatchWorkgroups(100);
pipeline.dispatchThreads(100);
```

TypeGPU automatically generates a "catch-all" bind group and populates it with the fixed resources.
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