GPU Tables
From v9.4Experimental API
@luma.gl/experimental/gpu-tables provides experimental batch-preserving table helpers for rendering,
transforms, and compute. It builds on the primitive objects in
@luma.gl/gpgpu/gpu-data.
Start Here
- Read the GPU Tables guide for end-to-end attribute and storage workflows.
- Read GPU Table Structure for the logical-column and physical-batch object model.
- Use
GPUTablefor data ownership andGPUTableShaderBindingsfor backend-specific shader resources.
API Reference
- GPU Table Structure
- GPU Table Lifecycle
- GPUTable
- GPURecordBatch
- GPUSchema
- GPUInputSchema
- GPUTable Shader Bindings
- GPUTableBufferPlanner
- GPGPU Data Primitives
The subpath owns GPURecordBatch, GPUTable, GPUSchema, GPUField, GPUTypeMap, table
bindings, table computations, and generic table planners. Models can publish GPUInputSchema
declarations for the prepared table inputs they accept. GPUTableShaderBindings
resolves those declarations into owned, batch-preserving attribute and storage
resources for a shader layout. Table-oriented execution helpers include
TableTransform,
GPUTableComputation, GPUTableBufferPlanner, and generated-buffer batching
utilities. GPUTableModel renders preserved table batches through one model pipeline, while
GPUTableGeometry exposes a packed static table as ordinary GPU geometry. Specialized path and
polygon models live separately in @luma.gl/experimental/models.
Source-specific construction and analysis belongs in application adapters that build the generic GPU table objects exposed here.
Installing
This subpath is experimental in 9.4 and is installed with its containing package. Install GPGPU as well when constructing primitive data objects directly:
npm install @luma.gl/gpgpu @luma.gl/experimental