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compute

Work on CUDA, OpenCL, GLSL compute, GL/CUDA or GL/OpenCL interop, GPU data ownership, kernels, argument packing, and compute-driven rendering.

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node-3d/node-3d67 stars(GitHub 67 + cccskills 0)

Run score Not tested

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Files included (2)

  • SKILL.md1.3 KB
  • agents/openai.yaml181 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Compute

Owns

GPU compute architecture, resource ownership, synchronization, and compute examples.

Workflow

  1. Identify the backend and where simulation/render state lives.
  2. Keep GPU data resident where practical; avoid per-frame CPU round trips.
  3. Make GL/compute ownership transitions explicit and exception-safe.
  4. Keep JS responsible for orchestration and kernels for data-parallel work.
  5. Keep kernel argument layout explicit; validate handles, contexts, lifetimes, and dynamic pointer updates.
  6. Give examples explicit runtime/device requirements and a bounded automation path where practical.
  7. Choose texture ping-pong for browser-style GPGPU or shared GL VBOs for compute/render interop; keep dynamic state stride and typed representation explicit.

Load References

Load .agents/references/gpu-interop.md for GL/CUDA/OpenCL ownership, synchronization, resource handles, or argument packing.

Load .agents/references/boids-workflow.md when extending or diagnosing the canonical packages/core/examples/core/boids implementations.

Use $examples/$tests as secondary skills only when modifying their artifacts.

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