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10-layer architecture synthesizing all expanded theories: - Layer 0: Raw UTF-8 → semantic density field - Layer 1: Density field extraction (Morse-Smale complex) - Layer 2: Hypercube-rhomboid shear (Gram matrix as dictionary) - Layer 3: S3C shell coordinate encoding - Layer 4: GCCL-GEC packet encoding (7-field glyphs) - Layer 5: OAC speculative manifestation - Layer 6: Radius-ratio local quantization - Layer 7: FAMM temporal sequencing - Layer 8: PIST perturbation encoding - Layer 9: erans residual entropy coding - Layer 10: Archive assembly 9 component interdependencies mapped (density→GCCL, GCCL→OAC, shear→S3C, S3C→FAMM, radius→GCCL, FAMM→PIST, PIST→erans, OAC→receipts, shear→EigenBook). 10 compression gain sources quantified (geometric shear 15-30%, topological skeleton 50-150MB vs 1GB, glyph kernels, S3C shells, OAC speculation 2-5%, FAMM context 10-20%, PIST bundle 5-8%, erans entropy, radius-ratio quantization, Gram dictionary MB→KB). 7 implementation phases defined (Foundation → Density Field → GCCL-GEC Core → Shear/Eigen → OAC/Speculation → PIST/erans → Integration → Benchmark). 14 keeper phrases. Core synthesis: density field = manifold, glyph packets = navigators, shear matrix = map. |
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| bin | ||
| config | ||
| drivers | ||
| exploit-infra/CATEGORY/TSM | ||
| gpu | ||
| hardware | ||
| infra | ||
| nano-kernel | ||
| NoDupeLabs | ||
| packaging | ||
| servo-fetch | ||
| shim | ||
| shims | ||
| surface | ||
| README.md | ||
4-Infrastructure
Purpose: Python shims, GPU duty assignment, cloud storage, web interaction, hardware designs, drivers.
Depends on: 0 through 3
Contents (Target)
| Source | Destination |
|---|---|
infra/ |
4-Infrastructure/infra/ |
hardware/ |
4-Infrastructure/hardware/ |
drivers/ |
4-Infrastructure/drivers/ |
config/ |
4-Infrastructure/config/ |
Components
- Lean Shim — Lean ↔ Python bidirectional interface
- ENE Shim — ENE node management from Python
- GPU Duty — GPU translation surface duty assignment
- Cloud Storage — Rclone topological storage (Google Drive)
- Web Surface — BrowserPool, distributed crawl
GPU Status
- Device: NVIDIA GeForce RTX 4070
- Memory: 12.3GB total, ~10GB available
- CUDA: 13.0