High-performance charts powered by WebGPU
Documentation | Live Demo | Examples
ChartGPU is a TypeScript charting library built on WebGPU for smooth, interactive rendering—especially when you have lots of data.
- 🚀 WebGPU-accelerated rendering for high FPS with large datasets
- ⚡ Worker-based rendering with OffscreenCanvas (optional - for maximum performance)
- 📈 Multiple series types: line, area, bar, scatter, pie, candlestick
- 🌡️ Scatter density/heatmap mode (
mode: 'density') for large point clouds — seedocs/api/options.md#scatterseriesconfigandexamples/scatter-density-1m/ - 🧭 Built-in interaction: hover highlight, tooltip, crosshair
- 🔁 Streaming updates via
appendData(...)(cartesian series) - 🔍 X-axis zoom (inside gestures + optional slider UI)
- 🎛️ Theme presets (
'dark' | 'light') and custom theme support
At a high level, ChartGPU.create(...) owns the canvas + WebGPU lifecycle, and delegates render orchestration (layout/scales/data upload/render passes + internal overlays) to the render coordinator. For deeper internal notes, see docs/api/INTERNALS.md (especially “Render coordinator”).
flowchart TB
UserApp["Consumer app"] --> PublicAPI["src/index.ts (Public API exports)"]
PublicAPI --> ChartCreate["ChartGPU.create(container, options)"]
PublicAPI --> SyncAPI["connectCharts(charts)"]
subgraph MainThread["🔷 MAIN THREAD RENDERING (Default)"]
subgraph ChartInstance["Chart instance (src/ChartGPU.ts)"]
ChartCreate --> SupportCheck["checkWebGPUSupport()"]
ChartCreate --> Canvas["Create canvas + mount into container"]
ChartCreate --> Options["resolveOptionsForChart(options)<br/>(adds bottom reserve when slider present)"]
ChartCreate --> GPUInit["GPUContext.create(canvas)"]
ChartCreate --> Coordinator["createRenderCoordinator(gpuContext, resolvedOptions)"]
ChartCreate --> InstanceAPI["ChartGPUInstance APIs"]
InstanceAPI --> RequestRender["requestAnimationFrame (coalesced)"]
RequestRender --> Coordinator
InstanceAPI --> SetOption["setOption(...)"]
InstanceAPI --> AppendData["appendData(...)"]
InstanceAPI --> Resize["resize()"]
subgraph PublicEvents["Public events + hit-testing (ChartGPU.ts)"]
Canvas --> PointerHandlers["Pointer listeners"]
PointerHandlers --> PublicHitTest["findNearestPoint() / findPieSlice()"]
PointerHandlers --> EmitEvents["emit('click'/'mouseover'/'mouseout')"]
end
DataZoomSlider["dataZoom slider (absolute-positioned DOM overlay)<br/>chart reserves bottom space for x-axis"] --> Coordinator
end
subgraph WebGPUCore["WebGPU core (src/core/GPUContext.ts)"]
GPUInit --> AdapterDevice["navigator.gpu.requestAdapter/device"]
GPUInit --> CanvasConfig["canvasContext.configure(format)"]
end
subgraph RenderCoordinatorLayer["Render coordinator (src/core/createRenderCoordinator.ts)"]
Coordinator --> Layout["GridArea layout"]
Coordinator --> Scales["xScale/yScale (clip space for render)"]
Coordinator --> DataUpload["createDataStore(device) (GPU buffer upload/caching)"]
Coordinator --> DensityCompute["Encode + submit compute pass<br/>(scatter density mode)"]
DensityCompute --> RenderPass["Encode + submit render pass"]
subgraph InternalOverlays["Internal interaction overlays (coordinator)"]
Coordinator --> Events["createEventManager(canvas, gridArea)"]
Events --> OverlayHitTest["hover/tooltip hit-testing"]
Events --> InteractionX["interaction-x state (crosshair)"]
Coordinator --> OverlaysDOM["DOM overlays: legend / tooltip / text labels"]
end
end
end
subgraph WorkerThread["⚡ WORKER THREAD RENDERING (Optional - src/worker/)"]
subgraph WorkerProxyAPI["Worker Proxy API (src/worker/)"]
CreateInWorker["createChartInWorker(container, options)<br/>ChartGPU.createInWorker(container, options)"]
CreateInWorker --> ProxyInit["ChartGPUWorkerProxy initialization"]
ProxyInit --> CanvasTransfer["canvas.transferControlToOffscreen()"]
ProxyInit --> WorkerCreate["Create Worker (built-in or custom)"]
end
subgraph MainThreadProxy["Main Thread: ChartGPUWorkerProxy (src/worker/ChartGPUWorkerProxy.ts)"]
ProxyInit --> ProxyInstance["ChartGPUWorkerProxy implements ChartGPUInstance"]
ProxyInstance --> ProxyState["Local state cache<br/>(options, interactionX, zoomRange)"]
ProxyInstance --> EventForwarding["Event forwarding to worker<br/>(pointerdown/move/up/leave/wheel)"]
ProxyInstance --> ProxyOverlays["DOM overlay management<br/>(tooltip, legend, text, slider)"]
ProxyInstance --> ResizeMonitoring["ResizeObserver + DPR monitoring<br/>(RAF batched)"]
EventForwarding --> ForwardPointer["computePointerEventData()<br/>(calculates grid coords on main thread)"]
ResizeMonitoring --> ResizeRAF["RAF-batched resize messages"]
end
subgraph WorkerInbound["Main → Worker (src/worker/protocol.ts)"]
CanvasTransfer -->|"postMessage: init"| WorkerInit["InitMessage + OffscreenCanvas transfer<br/>(includes devicePixelRatio from main thread)"]
ProxyInstance -->|"postMessage: setOption"| WorkerSetOpt["SetOptionMessage"]
ProxyInstance -->|"postMessage: appendData"| WorkerAppend["AppendDataMessage + ArrayBuffer transfer"]
ResizeRAF -->|"postMessage: resize"| WorkerResize["ResizeMessage<br/>(includes devicePixelRatio)"]
ForwardPointer -->|"postMessage: forwardPointerEvent"| WorkerPointer["ForwardPointerEventMessage<br/>(includes pre-computed grid coordinates)"]
ProxyInstance -->|"postMessage: setZoomRange"| WorkerZoom["SetZoomRangeMessage"]
ProxyInstance -->|"postMessage: setInteractionX"| WorkerInteractionX["SetInteractionXMessage"]
ProxyInstance -->|"postMessage: dispose"| WorkerDispose["DisposeMessage"]
end
subgraph WorkerCore["Worker Thread: ChartGPUWorkerController (src/worker/ChartGPUWorkerController.ts)"]
WorkerInit --> WGPUInit["GPUContext.create(offscreenCanvas)"]
WGPUInit --> WOptions["resolveOptionsForChart(msg.options)<br/>(adds bottom reserve when slider present)"]
WOptions --> WCoordinator["createRenderCoordinator(gpuContext, resolvedOptions)<br/>computeInteractionScalesGridCssPx<br/>(supports OffscreenCanvas)"]
WCoordinator --> WRenderLoop["MessageChannel render loop"]
WorkerSetOpt --> WOptions
WorkerAppend --> WDataStore["Worker DataStore (GPU buffer upload)"]
WorkerResize --> WCoordinator
WorkerPointer --> WHitTest["Worker hit-testing<br/>(uses interactionScales with grid coords)<br/>findNearestPoint/findPointsAtX"]
WorkerZoom --> WCoordinator
WorkerInteractionX --> WCoordinator
WorkerDispose --> WCleanup["Resource cleanup"]
end
subgraph WorkerOutbound["Worker → Main (postMessage)"]
WGPUInit -->|"ready"| ReadyMsg["ReadyMessage + GPU capabilities + PerformanceCapabilities"]
WRenderLoop -->|"rendered"| RenderedMsg["RenderedMessage (frame stats)"]
WRenderLoop -->|"performanceUpdate"| PerfMsg["PerformanceUpdateMessage (FPS, frame time, memory)"]
WHitTest -->|"tooltipUpdate"| TooltipMsg["TooltipUpdateMessage<br/>(complete tooltip content + position)"]
WCoordinator -->|"legendUpdate"| LegendMsg["LegendUpdateMessage"]
WCoordinator -->|"axisLabelsUpdate"| AxisMsg["AxisLabelsUpdateMessage"]
WHitTest -->|"hoverChange"| HoverMsg["HoverChangeMessage"]
WHitTest -->|"click"| ClickMsg["ClickMessage"]
WHitTest -->|"crosshairMove"| CrosshairMsg["CrosshairMoveMessage"]
WCoordinator -->|"zoomChange"| ZoomMsg["ZoomChangeMessage"]
WGPUInit -->|"deviceLost"| DeviceLostMsg["DeviceLostMessage"]
WCleanup -->|"disposed"| DisposedMsg["DisposedMessage"]
WCoordinator -->|"error"| ErrorMsg["ErrorMessage"]
end
subgraph MainThreadDOM["Main Thread: DOM Overlay Rendering (ChartGPUWorkerProxy)"]
ReadyMsg --> ProxyOverlays
ReadyMsg --> PerfCache["Cache PerformanceCapabilities + set isInitialized"]
PerfMsg --> PerfUpdate["Cache PerformanceMetrics + notify callbacks"]
TooltipMsg --> DOMTooltip["RAF-batched tooltip.show(x, y, content)<br/>(receives complete tooltip data from worker)"]
LegendMsg --> DOMLegend["RAF-batched legend.update(items, theme)"]
AxisMsg --> DOMAxis["RAF-batched textOverlay.addLabel(...)<br/>(auto-handles container overflow)"]
HoverMsg --> DOMHover["Re-emit 'mouseover'/'mouseout' events"]
ClickMsg --> DOMClick["Re-emit 'click' event"]
CrosshairMsg --> DOMCrosshair["Update cached interactionX + emit"]
ZoomMsg --> DOMZoom["Update cached zoomRange + zoomState"]
ProxyOverlays --> DOMTooltip
ProxyOverlays --> DOMLegend
ProxyOverlays --> DOMAxis
end
end
subgraph Renderers["GPU renderers (src/renderers/*)"]
RenderPass --> GridR["Grid"]
RenderPass --> AreaR["Area"]
RenderPass --> BarR["Bar"]
RenderPass --> ScatterR["Scatter"]
RenderPass --> ScatterDensityR["Scatter density/heatmap"]
RenderPass --> LineR["Line"]
RenderPass --> PieR["Pie"]
RenderPass --> CandlestickR["Candlestick"]
RenderPass --> CrosshairR["Crosshair overlay"]
RenderPass --> HighlightR["Hover highlight overlay"]
RenderPass --> AxisR["Axes/ticks"]
WRenderLoop --> GridR
end
subgraph Shaders["WGSL shaders (src/shaders/*)"]
GridR --> gridWGSL["grid.wgsl"]
AreaR --> areaWGSL["area.wgsl"]
BarR --> barWGSL["bar.wgsl"]
ScatterR --> scatterWGSL["scatter.wgsl"]
ScatterDensityR --> scatterDensityBinningWGSL["scatterDensityBinning.wgsl"]
ScatterDensityR --> scatterDensityColormapWGSL["scatterDensityColormap.wgsl"]
LineR --> lineWGSL["line.wgsl"]
PieR --> pieWGSL["pie.wgsl"]
CandlestickR --> candlestickWGSL["candlestick.wgsl"]
CrosshairR --> crosshairWGSL["crosshair.wgsl"]
HighlightR --> highlightWGSL["highlight.wgsl"]
end
subgraph ChartSync["Chart sync (src/interaction/createChartSync.ts)"]
SyncAPI --> ListenX["listen: 'crosshairMove'"]
SyncAPI --> DriveX["setCrosshairX(...) on peers"]
end
InteractionX --> ListenX
DriveX --> InstanceAPI
CrosshairMsg --> ListenX
Financial OHLC (open-high-low-close) candlestick rendering with classic/hollow style toggle and color customization. The live streaming demo renders 5 million candlesticks at over 100 FPS with real-time updates.
GPU-binned density/heatmap mode for scatter plots (mode: 'density') to reveal structure in overplotted point clouds. See docs/api/options.md#scatterseriesconfig and the demo in examples/scatter-density-1m/.
10,000,000 points rendered at ~120 FPS (benchmark mode).
import { ChartGPU } from 'chartgpu';
const container = document.getElementById('chart')!;
await ChartGPU.create(container, {
series: [{ type: 'line', data: [[0, 1], [1, 3], [2, 2]] }],
});For maximum performance with large datasets, use worker-based rendering to keep the main thread responsive:
import { ChartGPU } from 'chartgpu';
const container = document.getElementById('chart')!;
// Identical API, but rendering happens in a Web Worker
await ChartGPU.createInWorker(container, {
series: [{ type: 'line', data: [[0, 1], [1, 3], [2, 2]] }],
});When to use workers:
- Large datasets (>10K points) with frequent updates
- Real-time streaming data
- Complex multi-series charts
- Mobile/low-power devices
See Worker API Documentation for details.
npm install chartgpu
React bindings are available via chartgpu-react:
npm install chartgpu-reactimport { ChartGPUChart } from 'chartgpu-react';
function MyChart() {
return (
<ChartGPUChart
options={{
series: [{ type: 'line', data: [[0, 1], [1, 3], [2, 2]] }],
}}
/>
);
}See the chartgpu-react repository for full documentation and examples.
- Chrome 113+ or Edge 113+ (WebGPU enabled by default)
- Safari 18+ (WebGPU enabled by default)
- Firefox: not supported (WebGPU support in development)
- Full documentation: Getting Started
- API reference:
docs/api/README.md
- Browse examples:
examples/ - Run locally:
npm installnpm run dev(openshttp://localhost:5176/examples/)
See CONTRIBUTING.md.
MIT — see LICENSE.




