docs(v0.2.3): add TF32 design doc and demo script#47
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- Add docs/tf32_tensorcore_design.md with: - PTX mma.sync fragment mapping (empirically verified) - cp.async double-buffering pipeline - Kernel architecture and tiling parameters - Performance results and API usage - CUTLASS reference for future optimization - Add examples/demo_v023.py demonstrating: - gp.matmul(a, b, use_tf32=True) - gp.get_device_capabilities() - Performance benchmark (FP32 vs TF32) - Correctness validation Demo results (RTX 3090 Ti): - 2048x2048: 10.66 TFLOPS (1.33x speedup) - 4096x4096: 21.42 TFLOPS (1.63x speedup) - 8192x8192: 28.44 TFLOPS (1.66x speedup) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Summary
docs/tf32_tensorcore_design.md- comprehensive TF32 TensorCore design documentationexamples/demo_v023.py- demo script showcasing v0.2.3 featuresDocumentation Contents
docs/tf32_tensorcore_design.mdexamples/demo_v023.pyDemo Results (RTX 3090 Ti)
Test plan
Closes partial requirements for #41
🤖 Generated with Claude Code