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Author SHA1 Message Date
Brandon Schneider
aba1fba7ad fix(adversarial-review): resolve 35 critical coding bugs across 8 subsystems 
Security & correctness fixes from full adversarial review:

Lean (7 fixes):
- FixedPoint.lean: guard false theorem with n > 0 precondition
- QFactor.lean: remove double-scaling error in energy decrease
- AVMIsa/Step.lean: implement addSatQ16/subSatQ16 primitives
- BraidEigensolid.lean: fix crossStep second output argument swap
- SSMS.lean: complete ACI preservation proof (with rounding caveat)
- HouseholderQR.lean: add n > 0 precondition to spectral theorem

Verilog (7 fixes):
- q16_lut_core.v: fix multiply shift (16 → 32 bits)
- q16_lut_top.v: fix valid bit (0 → 1)
- cff_accelerator.v: fix SHA-256 padding (len < 448 check)
- research_stack_top.v: fix trigger aliasing (unique counters)
- Blitter6502OISC_small.v: fix address width (15 → 16 bits)
- spatial_hash_bram.v: add OOB write guard
- tmr_oepi_safety_fsm.v: fix double-increment race

WGSL (6 fixes):
- shaders.wgsl: atomicAdd for concurrent writes
- frustration_qubo.wgsl: double-buffer + CAS loop
- braid_fft.wgsl: workgroupBarrier synchronization
- burgers_scar_filter.wgsl: atomic E_bins array

Rust (9 fixes):
- thermodynamic.rs: Arc::from_raw → Arc::clone (double-free)
- thermodynamic.rs: Box::into_raw → Box (leak)
- tools/src/lib.rs: shell injection → shlex.quote
- ene-node/src/lib.rs: LRU caps, constant-time HMAC, peer caps

Python (6 fixes):
- similarity/__init__.py: pickle.load → RestrictedUnpickler
- AI-Feynman: torch.load → weights_only=True (14 calls)
- fetch_arxiv.py, fetch_s2.py: eval → ast.literal_eval
- topology.py: os.system → shutil.copy2
- SSH pipe: os.system → base64 pipe

Build: lake build 3572 jobs, 0 errors
 2026-05-31 23:38:03 -05:00
Brandon Schneider
0ea09c4462 docs: add Reality Audit section to k3s-flake README 
Document discrepancies between the aspirational architecture (in the
flake/docs) and what's actually deployed. Covers control plane location,
edge Caddy divergence, Traefik port, cross-namespace services, and
hostname mismatches. Load the research-stack-infrastructure-bootstrap
skill for the actual deployment procedure.

Build: no build needed
 2026-05-31 23:19:42 -05:00
Brandon Schneider
978cfb9075 fix(ingress): correct Authentik forward-auth service namespace 
- Change middleware address from authentik-server.services.svc.cluster.local
  to authentik-server.authentik.svc.cluster.local (Authentik lives in
  authentik namespace, not services)
- Create ExternalName service authentik-server in services namespace so
  the rs-auth Ingress can route to the cross-namespace service

Build: no build needed
 2026-05-31 23:15:46 -05:00
Brandon Schneider
6d9c4e23de fix(infra): standardize k3s cluster — Traefik, ingress, architecture docs, Ray GPU workers 
Architecture alignment:
- Rewrite k3s-server.nix from aspirational role=server to actual role=agent
  (cupfox is the real control-plane at 100.110.163.82:6443)
- Update flake.nix: correct serverAddr for all nodes, annotate dead nodes,
  fix hostname from nixos-laptop to nixos
- Update join-agent.sh default SERVER to cupfox
- Document actual vs intended architecture in comments

Ingress:
- Add rs-apps-books Ingress for audiobookshelf (/apps/books → media ns)
- Add strip-apps-books middleware for prefix stripping
- Create ray-ingress.yaml for Ray dashboard at /server/ray

Ray:
- Fix raycluster.yaml: enable dashboard, mount /dev/dri on gpu-workers
- Point gpu-workers to qfox-1 (was neon-64gb)
- Remove nvidia.com/gpu resource dependency (use /dev/dri via Mesa)

Security:
- Move OPENID_CLIENT_SECRET from plaintext to K8s Secret ref
- Update manifest to use valueFrom.secretKeyRef

Cleanup:
- Remove 53 committed test PNG screenshots from git tracking
- Remove auth-state.json from git tracking
- Add *.png, *.json to tests/.gitignore

Build: no build needed
 2026-05-31 23:13:04 -05:00
Brandon Schneider
83ea1580d9 feat(homarr): add Playwright test specs for login, onboard, OIDC, board creation, and integrations 
17 new .spec.ts files and 4 debug .png screenshots capturing:
- OIDC login flows (oidc-setup, oidc-login)
- Login variants (admin, v2, quick, cookie capture)
- Board creation and management
- Integration setup flows
- Onboarding test sequence
- Check/init/do-init lifecycle tests

Build: 0 jobs, 0 errors (no Lean files touched)
 2026-05-31 20:26:16 -05:00
Brandon Schneider
fb9e41b2a0 chore(homarr): onboard started, OIDC configured, DB created 
- Homarr OIDC env vars set (sso-homarr)
- Database created at /data/db.sqlite
- Config schema updated to v2
- Onboard wizard needs final UI completion

Build: 3313 jobs, 0 errors
 2026-05-31 15:12:44 -05:00
Brandon Schneider
7fe8b6ba72 feat(jellyfin): add media libraries (Movies, TV Shows, Music) 
- Libraries created via API (204 on creation + path update)
- Paths: /media/movies, /media/tv, /media/music
- SSO-Auth plugin Active, SSO button on login page
- Paths may need manual setting through Dashboard UI

Build: 3313 jobs, 0 errors
 2026-05-31 14:55:59 -05:00
Brandon Schneider
3fdc7de196 feat(jellyfin): SSO-Auth plugin active, branding configured 
- SSO-Auth plugin Active with Authentik OIDC provider
- SSO redirect endpoint verified (302 -> auth.researchstack.info)
- Login disclaimer and custom CSS for SSO button
- All 22+ services operational with HTTPS

Build: 3313 jobs, 0 errors (lake build Compiler)
 2026-05-31 14:48:21 -05:00
Brandon Schneider
123d1fea0b chore(jellyfin): SSO-Auth config file + Playwright setup script 
- SSO-Auth plugin config written to Jellyfin config directory
- Playwright automation script for SSO-Auth setup created
- Plugin not auto-loading - needs UI catalog install

Build: 3313 jobs, 0 errors
 2026-05-31 14:24:44 -05:00
Brandon Schneider
9e80ac68ca feat(infra): Jellyfin wizard complete, SSO-Auth plugin files deployed 
- Jellyfin setup wizard completed, admin account created (admin/jellyfin-admin)
- SSO-Auth plugin v4.0.0.3 downloaded and placed in plugins directory
- Authentik OIDC provider for Jellyfin updated with correct redirect URI
- All services verified running

Build: 3313 jobs, 0 errors (lake build Compiler)
 2026-05-31 14:14:20 -05:00
Brandon Schneider
02602f12a3 feat(infra): complete OIDC config, homarr manifest, vw api verified 
- Homarr OIDC env vars in manifest + applied
- Navidrome, Kavita, Audiobookshelf OIDC env vars verified
- Vaultwarden API running with allaun@researchstack.info
- Jellyfin DB reset - needs web UI first-run setup

Build: 3313 jobs, 0 errors (lake build Compiler)
 2026-05-31 13:48:05 -05:00
Brandon Schneider
770e3f0805 fix(infra): configure vaultwarden-api with user credentials 
- Vaultwarden signups enabled then disabled after user created
- vaultwarden-api configured with allaun@researchstack.info
- API verified responding at vaultapi.researchstack.info

Build: 3313 jobs, 0 errors (lake build Compiler)
 2026-05-31 13:36:51 -05:00
Brandon Schneider
0d87bcb770 feat(infra): media stack, Vaultwarden, Cloudflare tunnel, OIDC providers, Caddy TLS 
- Media stack deployed: qBittorrent, Sonarr, Radarr, Lidarr, Prowlarr, Bazarr,
  Navidrome, Audiobookshelf, Jellyfin, Homarr, Kavita, MeTube, SuggestArr, BoxArr
- Romm, ebook2audiobook (GPU CUDA), TrailBase, FlareSolverr deployed
- Vaultwarden + Vaultwarden-API deployed
- Caddy reverse proxy on racknerd with Let's Encrypt TLS at *.researchstack.info
- Authentik 7 OIDC providers + 12 proxy providers for SSO
- NVIDIA GPU support enabled on k3s (device plugin + containerd runtime)
- Cloudflare tunnel created (DNS on Porkbun)

Build: 3313 jobs, 0 errors (lake build Compiler)
 2026-05-31 11:01:39 -05:00
Brandon Schneider
7c1f690e0f feat(infra): Garage 6-node RF3 cluster, Cloudflare Workers deploy, k3s node additions 
- Garage scale-out complete: 6 nodes across 6 zones with replication_factor=3
- neon-64gb: added to Garage cluster (zone netcup-arm, 93 GiB)
- steamdeck: installed Garage v2.3.0, added to cluster (zone gpu, 373 GiB)
- nixos-laptop: converted from k3s server to agent in cupfox cluster
- qfox-1: k3s agent rejoined cupfox cluster
- Cloudflare Workers: WASM trinary VM deployed at wasm-compute-edge.researchstack.workers.dev
- node-registry.json: updated with all 6 Garage nodes
- Documentation: AGENTS.md, WIKI.md, ROADMAP.md, LLM-Context.md updated
- Lake build: 3313 jobs, 0 errors

Build: 3313 jobs, 0 errors (lake build Compiler)
 2026-05-31 03:39:11 -05:00
Brandon Schneider
008cf8fefe feat(infra): migrate external service registry to aiven mysql with ssl 
- Migrated service_registry.py defaults from InfinityFree to Aiven MySQL.
- Enforced REQUIRED SSL mode on connections (ssl_mode for mysql-connector, ssl dict for pymysql).
- Added helper _get_dict_cursor to resolve pymysql compatibility issues.
- Configured registry password and encryption key in decrypted/encrypted .env via SOPS.

Build: 3313 jobs, 0 errors (lake build)
 2026-05-31 02:10:10 -05:00
Brandon Schneider
d9a647cb4d chore(infra): bootstrap racknerd and configure multi-node garage cluster 
- Bootstrapped microvm-racknerd node on its live Tailscale IP 100.80.39.40.
- Connected racknerd to the central QFox cluster.
- Assigned racknerd to its own vps zone with 1G capacity.
- Made garage-cluster-init.sh robust and idempotent.
- Updated comments and topology mappings.

Build: 3313 jobs, 0 errors (lake build)
 2026-05-31 02:04:32 -05:00
Brandon Schneider
aff285be30 fix(infra): service registry is backup/fallback, not primary 
Primary: Tailscale mesh + internal PostgreSQL/SQLite
Backup:  InfinityFree MySQL (this file)

Use cases for backup path:
  - Edge nodes that cant reach mesh (ESP32, Cloudflare Workers)
  - Mesh-down fallback (Tailscale outage)
  - Cross-mesh discovery (different tailnets)
  - Low-impact config distribution
 2026-05-30 21:19:24 -05:00
Brandon Schneider
ebcf0571ec feat(infra): external service registry via InfinityFree MySQL 
service_registry.py — mesh-independent node discovery and credential store.

Tables:
  nodes       — registered devices with capabilities, tier, IPs
  credentials — encrypted blobs (ChaCha20) with TTL auto-expiry
  config      — distributed key-value configuration

Features:
  - auto_register() — uses device_capability_probe to register
  - discover_nodes() — find nodes by tier, with max-age filter
  - store/get_credential() — encrypted at rest, short TTL
  - heartbeat() — keepalive for node registry
  - CLI: init, register, discover, store, get, cleanup, config-set/get

Any node with internet can reach it (no Tailscale required).
Credentials encrypted with ChaCha20, key from REGISTRY_ENCRYPT_KEY env.
 2026-05-30 21:14:51 -05:00
Brandon Schneider
6d4d099625 fix(infra): tier limits leave headroom for device function 
Each tier now reserves resources for its primary function:
  GPU_CUDA:     8GB VRAM (not 12 — keep 4GB for display/compositor)
  GPU_VAAPI:    256MB (keep VRAM headroom for desktop)
  GPU_APU:      128MB (shared DDR, OS needs bandwidth)
  CPU_FFMPEG:   64MB, half cores (leave for OS/k3s)
  BATCH:        1500 min/month (reserve 500 for actual CI/CD)
  ETHERNET:     500ms timeout (leave bandwidth for SSH/mgmt)
  FRAMEBUFFER:  768KB (half — keep display visible, compute in top rows)
  WASM:         512B payload, 8ms CPU (leave 2ms for JSON overhead)
  DSP:          2048 samples (half FFT, leave for overlap buffer)
  ESP32:        512B (WiFi/BLE stack needs ~80KB of 520KB SRAM)
 2026-05-30 20:45:50 -05:00
Brandon Schneider
ba1bf871f8 feat(infra): per-tier device limitations for Ray scheduling 
DeviceLimitations dataclass with hard constraints per tier:
  GPU_CUDA:     1GB payload, 16 concurrent, 60s, NVENC, 12GB VRAM
  GPU_VAAPI:    512MB payload, 8 concurrent, 60s, VAAPI HW
  GPU_APU:      256MB payload, 4 concurrent, 30s, shared DDR
  CPU_FFMPEG:   128MB payload, 2 concurrent, 120s, software
  BATCH:        64MB payload, 1 concurrent, 6h, 2000 min/month
  ETHERNET:     1400B payload, 1 concurrent, 1s, virtio-net
  FRAMEBUFFER:  1.5MB payload, 1 concurrent, 100ms, DMA only
  WASM:         1KB payload, 1 concurrent, 10ms, 100K req/day
  DSP:          16KB payload, 1 concurrent, 5s, FFT only
  ESP32:        2KB payload, 1 concurrent, 100ms, Q0_16 scalar

get_limitations(caps) returns actual hardware-aware limits
(vram override, framebuffer capacity, memory override)
 2026-05-30 20:44:31 -05:00
Brandon Schneider
cadb38cc1b feat(infra): add AMD VAAPI + FLAC DSP to FrameDispatcher 
FrameDispatcher now routes 6 tags:
  TAG_STRAND(0x01)  → BraidBackend (VCN compute)
  TAG_CROSSING(0x02) → BraidBackend (VCN compute)
  TAG_PIST(0x03)    → BraidBackend (VCN compute)
  TAG_LUPINE(0x04)  → CUDABackend (NVIDIA CUDA)
  TAG_VAAPI(0x05)   → VAAPIBackend (AMD/Intel VA-API)  ← NEW
  TAG_FLAC(0x06)    → FLACBackend (PipeWire/FLAC DSP)  ← NEW

New backends:
  - VAAPIBackend/LocalVAAPIBackend: AMD/Intel hardware encode/decode
  - FLACBackend/LocalFLACBackend: FFT spectral analysis, centroid, RMS
  - RayVAAPIBackend: Ray actor for VA-API operations
  - SyncVAAPIWrapper/SyncFLACWrapper: sync bridges for FrameDispatcher

Capability probe: DSP tier(1) added between FRAMEBUFFER(2) and ESP32(0)
 2026-05-30 20:35:42 -05:00
Brandon Schneider
5320a08105 feat(infra): integrate edge WASM and GitHub batch compute tiers 
- Update device_capability_probe.py to add BATCH and WASM tiers and fix a NameError bug on has_virtio_net.
- Build Cloudflare Workers WASM compilation and JS fetch handler in 4-Infrastructure/cloudflare/ executing trinary VM steps.
- Create GitHub Actions batch_compute.yml workflow to harvest runner minutes.
- Keep 4-Infrastructure/AGENTS.md updated with the WASM core library anchor.

Build: 3313 jobs, 0 errors (lake build)
 2026-05-30 20:08:31 -05:00
Brandon Schneider
51664eb060 docs(infra): plan — mesh networking layers over Ray 
Architectural plan for Tailscale mesh + Ray + VCN + compute surfaces.

5-layer stack:
  1. Tailscale connects everything (WireGuard, DERP relay)
  2. Ray schedules work across the mesh
  3. VCN compresses data (50x bandwidth reduction)
  4. FrameDispatcher routes by tag
  5. Compute surfaces execute (GPU/CPU/Ethernet/framebuffer/MCU)

Key insight: every device in the Tailscale mesh is a potential
compute node. Framebuffer and Ethernet surfaces turn devices
that "cant run Ray" into compute participants.

4 phases:
  1. Ray over Tailscale (mostly done)
  2. Multi-tier scheduling (probe done, placement pending)
  3. Framebuffer + Ethernet integration (host-side pending)
  4. Edge devices (ESP32, 1-Wire sensors)
 2026-05-30 20:03:57 -05:00
Brandon Schneider
d6fc9cfe6d feat(infra): add ETHERNET compute tier for virtio-net PistPacket DMA 
New tier between CPU_FFMPEG and FRAMEBUFFER:
  GPU_CUDA(7) > GPU_VAAPI(6) > GPU_APU(5) > CPU_FFMPEG(4) >
  ETHERNET(3) > FRAMEBUFFER(2) > ESP32(1) > RELAY(0)

- _detect_virtio_net(): probes /sys/class/net for virtio driver (0x1af4)
- PistPacket computation via TX/RX descriptor rings
- Host vhost-user backend does matrix transforms
- CRC32 hardware offload = witness verification
- Works in any VM with network (even without framebuffer)
 2026-05-30 20:02:06 -05:00
Brandon Schneider
66abf92214 fix(infra): handle Cirrus Logic virtual VGA and DRM naming edge cases 
- Add Cirrus Logic (0x1013) and virtio (0x1af4) to vendor map
- Fix DRM card parsing for names like "card0-VGA-1"
- Virtual GPUs (cirrus, virtio) never classified as discrete
- Virtual GPUs skip VA-API tier, fall to FRAMEBUFFER

Racknerd microVM (2vCPU, 715MB, Cirrus VGA) correctly classified as
FRAMEBUFFER tier: 1024x768 @ 16bpp = 1.57 MB DMA backplane.
 2026-05-30 19:59:38 -05:00
Brandon Schneider
16101a787f feat(infra): device capability probe with framebuffer fallback 
device_capability_probe.py: classify every device into a compute tier.

Tiers (highest to lowest):
  GPU_CUDA    — NVIDIA discrete + CUDA (NVENC, Ray GPU worker)
  GPU_VAAPI   — AMD/Intel discrete + VA-API (hardware encode)
  GPU_APU     — AMD integrated, yuvj420p, bandwidth-optimized
  CPU_FFMPEG  — Software encode only (libx264)
  FRAMEBUFFER — /dev/fb0 DMA backplane (8.29 MB/frame at 1080p)
  ESP32       — MCU, Q0_16 scalar in FreeRTOS idle hook
  RELAY       — Network only, no compute
  OFFLINE     — Unreachable

Features:
  - Multi-GPU DRM render node scanning (card0=AMD, card1=NVIDIA)
  - APU vs dGPU classification via device name + VRAM heuristics
  - Framebuffer detection with /sys/class/graphics/fb0 resolution
  - Ray scheduling helpers (get_ray_placement_strategy)
  - Cluster probe via SSH
  - JSON + human-readable output
 2026-05-30 19:57:07 -05:00
Brandon Schneider
cf907e2835 feat(infra): add QEMU graphics framebuffer packing shim and spec 
- Add qemu_framebuffer_packer.py supporting ARGB8888/RGB24 raw matrix mapping
- Implement zero-copy mmap write/read interface to /dev/fb0 with signature headers
- Document the QEMU graphics framebuffer backplane in Section 11 of spec
- Update 4-Infrastructure/AGENTS.md and walkthrough.md documentation
- Verify syntax and workspace compilation baseline status

Build: 3313 jobs, 0 errors (lake build)
 2026-05-30 19:49:25 -05:00
Brandon Schneider
850f644e0f feat(infra): Ray VCN bridge — FrameDispatcher over Ray transport 
ray_vcn_bridge.py: Ray transport for the VCN-LUPINE bridge.
  Replaces GPUNodeConnection TCP/MKV transport with Ray ObjectRef.
  FrameDispatcher, BraidBackend, CUDABackend are unchanged — only
  the wire between daemon and GPU node changes.

  - RayBraidBackend: compute actor matching VCNBraidBackend pattern
  - RayCUDABackend: GPU actor with /dev/dri (Mesa, no NVIDIA plugin)
  - RayVCNBridge: full bridge as Ray actor (replaces daemon)
  - RayGPUNodeConnection: drop-in for GPUNodeConnection
  - SyncBraidWrapper/SyncCUDAWrapper: bridge Ray actors to sync interface

  STRAND 42B → 63B, CROSSING 42B → 22B, PIST 24B → 57B
  Batch 10: 5ms (0.5ms/frame), 10/10 non-empty
 2026-05-30 19:48:34 -05:00
Brandon Schneider
30d4772a3f feat(infra): support heterogeneous environments in video compute decoder 
- Implement dynamic resolution and format probing using ffprobe inside decode_frames
- Eliminate hardcoded YUV420 frame size slicing during video file readback
- Standardize NVIDIA hardware config to 8-bit full-range yuv444p to keep byte layout unified
- Verify Python compilation and Lean workspace integrity checks

Build: 3313 jobs, 0 errors (lake build)
 2026-05-30 19:48:09 -05:00
Brandon Schneider
2bce7abaa9 feat(infra): optimize AMD APU/iGPU lossless pipeline targeting H.265 cores 
- Add detection for integrated AMD graphics (APUs/iGPUs) based on hardware model name
- Configure UMA-friendly full-range yuvj420p format to reduce system memory bandwidth footprint by 50%
- Force lossless constant QP (-qp 0) and full PC range to prevent clamping loss
- Re-run syntax checks and Lean compiler verification tests

Build: 3313 jobs, 0 errors (lake build)
 2026-05-30 19:46:34 -05:00
Brandon Schneider
6ea34fbae6 feat(infra): add GPU-specific math optimization loader for H.265 VCN/NVENC 
- Implement MathOptimizationLoad dataclass to represent GPU packing configurations
- Update probe_vcn_capabilities to resolve optimizations for NVIDIA/AMD/Intel GPUs
- Extend compute_frame_size to support yuvj420p, 10-bit YUV, and YUV444p
- Propagate optimized pixel formats into select_optimal_resolution and spec
- Update _build_ffmpeg_cmd to inject lossless/zero-latency options and HEVC/H.265 metadata SEI NAL parameters
- Update 4-Infrastructure/AGENTS.md documentation

Build: 3313 jobs, 0 errors (lake build)
 2026-05-30 19:45:09 -05:00
Brandon Schneider
63093f56da feat(infra): Ray VCN transport + cluster restoration 
- ray_vcn_transport.py: @ray.remote wrappers for braid VCN encode/decode
  - Distributed encode on CPU workers, compute on GPU workers
  - RayVCNTransport actor with frame counter + ObjectRef storage
  - FAMM-gated encode task, batch encode/decode helpers
  - 20 strands in 576ms (28.8ms/strand), 20/20 CRC ok

- raycluster.yaml: KubeRay cluster on qfox-1
  - Head + CPU worker + GPU worker (RTX 4070 SUPER via /dev/dri)
  - No NVIDIA device plugin — Mesa direct device access
  - Tolerations for desktop taint on qfox-1
  - num-gpus instead of custom GPU resource

- fix-nftables-k3s.sh: nftables forward rules for flannel/cni0
  - nftables default policy=drop blocks pod-to-pod networking
  - systemd service nftables-k3s-fix for persistence

- KubeRay operator moved to nixos (control plane can reach API server)
- FFmpeg 8.0 + reedsolo installed in Ray head pod via conda
 2026-05-30 19:42:39 -05:00
Brandon Schneider
61b38ca697 refactor(infra): optimize YUV420 frame packing using numpy 
- Vectorized create_yuv420_frame when numpy is available to eliminate the 500k-iteration scalar Python loop.
- Pre-filled memoryview slice buffers in the fallback path.
- Updated 4-Infrastructure/AGENTS.md to document the optimization.

Build: 3313 jobs, 0 errors (lake build)
 2026-05-30 19:32:11 -05:00
Brandon Schneider
30d8c56158 feat(infra): improve RRC Ray Layer Tagger and align registry 
Improved rrc_ray_tagger.py with prioritized source name-based variant matching, corrected NetworkRayReceipt (3 variants, 67us) and BurgersRGSolver (5 variants) shapes, fixed Hopf-Cole fallback bug using string normalization, dynamically deduced workspace root path, and quarantined phase_update due to adversarial review falsification. Registered anchor in 4-Infrastructure/AGENTS.md.

Build: 3313 jobs, 0 errors (lake build Compiler)
 2026-05-30 19:18:02 -05:00
Brandon Schneider
4965029758 feat: integrate May 2026 math papers into Research Stack 
1. Singer Sidon Sets (2605.03274):
   - New SidonSets.lean: IsSidon, IsSidonMod, IsIntervalSidon, h(N)
   - 5 fully proved lemmas, 13 sorry with TODO(lean-port)
   - GoldenRatioSeparation.lean: singer_density_lt_golden (proved)
   - lake build: 3303 jobs, 0 errors

2. Hexagonal lattice + RG (2605.09974):
   - New test_hexagonal_lattice_rg() in unified_rg_tests.py
   - Avila's global theory exact phase diagram
   - RG confirms localized/extended regimes
   - Fractal dimension: extended→1, critical→0.5, localized→0
   - 7 tests, all pass

3. Burgers + Hopf-Cole + Fokas (2605.11788):
   - Added solve_heat_fokas() — unified transform method
   - Added solve_burgers_fokas() — full Burgers via Hopf-Cole + Fokas
   - Added solve_heat_fourier_series() — comparison solver
   - Fokas converges in ~64 quadrature points vs Fourier 2000 terms
   - Hopf-Cole FFT: 8-208x faster than finite differences
 2026-05-30 18:16:57 -05:00
Brandon Schneider
a53e023cbe feat: Hopf-Cole exact solver for 1D Burgers — 151x speedup 
Hopf-Cole transformation maps Burgers to heat equation:
  u = -2v * d(ln ψ)/dx
  dψ/dt = v * d²ψ/dx² (exact via FFT)

Benchmark results:
  N=512,  v=0.01: 1.45x speedup
  N=1024, v=0.01: 83.4x speedup
  N=2048, v=0.01: 151.3x speedup

Key insight from adversarial review:
  - RG assumption (nonlinear term vanishes) is FALSE
  - But 1D Burgers IS integrable via Hopf-Cole
  - Exact solution in O(N log N), no time stepping
  - The 'insultingly easy' regime exists — just not via RG

This is the exact solution the agents found when they
broke the RG fixed point assumption.
 2026-05-30 17:36:12 -05:00
Brandon Schneider
c556d64ae0 feat: QEMU compute surfaces — virtio-crypto + ivshmem 
virtio_crypto_transform.py:
- VirtioCryptoSession: HASH session (SHA-256, SHA-512, MD5)
- VirtioCryptoHashTransform: encode as HASH request, produce receipt
- Receipt: {schema, transform_type, algo, payload_bytes, result_hex, witness_hash}
- Wire-format structs: CtrlHdr(20B), HashSessionPara(8B), HashDataReq(28B)
- RFC 6234 test vectors: all pass

ivshmem_client.py:
- IvshmemClient: mmap /dev/shm/ivshmem_bar0
- IvshmemRing: doorbell notification
- IvshmemTransform: write payload, ring doorbell, produce receipt
- Receipt: {schema, transform_type: shared_memory, offset, length, witness_hash}
- Memory layout: registers 0x0000, metadata 0x10000, data 0x20000
- /dev/shm fallback test: verified
 2026-05-30 17:35:24 -05:00
Brandon Schneider
f63e4b5179 feat(infra): virtio-net ring as compute pipeline 
Add virtio_net_transform.py: three Class-1 computation primitives via
virtio-net TX/RX rings — zero backend code changes needed.

  1. HASH_REPORT — host writes Toeplitz RSS hash into RX header
     (virtio_net_hdr_v1_hash.hash_value return channel)
  2. TSO gso_size — host splits large buffer via TCP segmentation offload
     (spatial partition into N × gso_size chunks)
  3. MRG_RXBUF — host merges multiple RX buffers (aggregation primitive)

Structs: VirtioNetHdr (12B), VirtioNetHdrHash (20B), VringDesc (16B).
Receipt schema: virtio_transform_receipt_v1 with CRC32 witness_hash.

The copy-if filter (skip zero deltas, process non-zeros) maps directly
onto the HASH_REPORT return channel: delta=0 → hash skip, delta≠0 →
hash_as_function_of_payload. This is the ambient compute model:
any QEMU/firecracker microVM is already a computation device without
knowing it.

Build: 3313 jobs, 0 errors (lake build)
Tools: glslang, spirv-as, spirv-dis (native); tint from nixpkgs for WGSL
 2026-05-30 16:54:09 -05:00
Brandon Schneider
9c5fe97dc1 feat(infra): SPIR-V packet generator and WGSL scar filter shader 
Add spirv_packet_generator.py: reads SPIR-V assembly, applies copy-if
optimization (OpPhi→OpSelect transform), and emits JSON packet descriptors
with the 5 OpPhi-derived fields (type_id, cond_id, true_val_id,
false_val_id, result_id) that fully specify the packet layout.

Add burgers_scar_filter.wgsl: 291-line WGSL compute shader for spectral
scar filtering in 2D Burgers RG solver. Uses three copy-if patterns:
  1. scar_pressure > threshold → apply hyperviscosity damping
  2. |kx| > k_cut || |ky| > k_cut → zero (dealiasing)
  3. factor < 0.999 → multiply velocity components

Also fix spirv_copy_if_optimizer.py: OpSelect now uses phi_instr.args[0]
(type operand) as its type, instead of compute_instr.result_id. This
produces structurally correct SPIR-V where the result type matches the
OpSelect opcode layout.

Build: 3313 jobs, 0 errors (lake build)
Tools: glslang, spirv-as, spirv-dis (native); tint from nixpkgs for WGSL
 2026-05-30 16:40:58 -05:00
Brandon Schneider
cfd43e1e95 feat(codec): extend BraidDiatCodec with BraidDiatFrame encoder/decoder 
- BraidDiatCodec.lean: BraidDiatFrame now handles encode/decode of full
  SpherionState × BraidReceipt with 256-bit header and variable mountain list
- braid_diat_codec.py: Python extraction updated to match, benchmark artifact
  at shared-data/artifacts/braid_diat_codec_benchmark.json (714B avg vs
  messagepack 1748B avg)

Build: lake build Compiler 3313 jobs, 0 errors
 2026-05-30 16:23:41 -05:00
Brandon Schneider
4df6997b51 docs(kube): update infra docs, RayCluster manifest with nightly GPU images 
- infrastructure-status.md: rewrite with current cluster topology (cupfox control-plane,
  neon-64gb/racknerd/steamdeck workers), RayCluster status, Garage storage,
  Caddy edge, open issues
- k3s-cluster-setup.md: fix steamdeck hardware specs (8 vCPU, 14.5 GB RAM)
- raycluster.yaml: upgrade to rayproject/ray:nightly-py313-gpu (multi-arch amd64+arm64),
  add gpu-workers group targeting neon-64gb, add arm64-workers for neon-64gb CPU
- README.md: update build job count (3460 → 3313, verified)

Build: lake build Compiler 3313 jobs, 0 errors
 2026-05-30 16:23:13 -05:00
Brandon Schneider
81d4338627 feat: ARM64 copy-if optimizer — branches to CSEL 
Transforms branch patterns to ARM64 conditional selects:
  Before: CMP + BEQ + compute + B + MOV = 5-47 cycles
  After: CMP + compute + CSEL = 4-6 cycles

ARM64 CSEL instruction:
  CSEL Xd, Xn, Xm, cond
  - Single cycle on most ARM64 processors
  - No branch prediction penalty
  - No pipeline flush on mispredict

Pattern detection:
  - CMP + BEQ/BNE/B.LT/etc
  - True block: 1-3 compute instructions + B
  - False block: single MOV
  - Merge point

Same pattern as:
  - SPIR-V OpSelect (GPU shaders)
  - VCN delta+RLE (3.3x)
  - QR spatial hash (2.18x)
  - Lean CopyIfTactic (2.7x)

Works on ARM64 assembly from GCC/LLVM/Rust.
No compiler fork needed — post-processing pass.

Targets: Neon-64GB (18 vCPU ARM64 EPYC)
 2026-05-30 15:59:24 -05:00
Brandon Schneider
2e15c7c0a5 feat: SPIR-V copy-if optimizer — skip zero deltas in GPU shaders 
Transforms branch-based patterns to OpSelect:
  Before: 3 blocks, OpBranchConditional, OpPhi
  After: 1 block, OpSelect (single-cycle on most GPUs)

Pattern detection:
  - OpSelectionMerge + OpBranchConditional
  - True block: single compute + OpBranch
  - False block: empty (just OpBranch)
  - Merge block: OpPhi merging true/false values

Transformation:
  - Remove SelectionMerge + BranchConditional
  - Inline compute instruction
  - Replace OpPhi with OpSelect
  - Collapse 3 blocks to 1

Same pattern as:
  - VCN delta+RLE (3.3x): skip zero bytes
  - QR spatial hash (2.18x): skip non-neighbors
  - Lean compilation (2.7x): skip trivial theorems
  - Spatial hash (86.5% cache hit): skip empty cells

Driver-agnostic: works at SPIR-V level before Mesa.
No Mesa fork required. No NIR pass needed.
 2026-05-30 15:57:08 -05:00
Brandon Schneider
d5428a8950 feat: QR spatial hash integration — 2.18x speedup 
Cache-friendly Householder QR via Morton-code spatial hash:
- When adding column, only apply reflections to 3x3x3 neighborhood
- Reduces per-update from O(n) to O(27) per column
- 50x50 matrix, 500 updates: 2.18x faster than naive

Naive: 0.124ms/update
Spatial: 0.057ms/update
Speedup: 2.18x

Key insight: Morton code ordering means nearby columns in 3D
are nearby in memory → cache-friendly access → fewer misses.

This completes all 4 next steps:
1. ✅ O_AMMR_QRNode wired into BraidDiatFrame (already done)
2. ✅ O_AMMR_valid strengthened with residual bounds (NS_MD.lean)
3. ✅ Hash benchmark: Morton wins (86.5% cache hit rate)
4. ✅ QR spatial hash: 2.18x speedup
 2026-05-30 15:30:06 -05:00
Brandon Schneider
bdc227459a feat: O_AMMR_valid strengthened + hash benchmark complete 
NS_MD.lean:
- Added QRResidualWitness structure (Q16_16 fixed-point)
- Added residual_bound_ok, basis_size_ok, orthogonality_ok predicates
- Extended O_AMMR_Node with qr_witness field
- Strengthened O_AMMR_valid: 4 conjuncts (admission + residual + basis + ortho)
- lake build: 3300 jobs, 0 errors

hash_benchmark.py (240 data points):
- Hilbert vs Morton vs xxHash
- 5 grid sizes (16^3 to 256^3), 4 trace sizes, 4 patterns

Key findings:
  Morton: 86.5% cache hit rate, 1.08µs p50, 0.512 locality
  xxHash: 30.3% cache hit rate, 0.96µs p50, 0.342 locality
  Hilbert: 27.6% cache hit rate, 2.29µs p50, 0.833 locality

Morton wins overall for spatial hash grids.
 2026-05-30 15:15:33 -05:00
Brandon Schneider
c6011dbbdf feat: wire BraidDiatCodec into FAMM transport 
BraidDiatCodec (714 bytes avg) imported alongside VCN encoder.
When available, can replace Delta+RLE for braid data encoding.

Benchmark (from braid_diat_codec_benchmark.json):
  BraidDiat: 0.029ms encode, 0.034ms decode, 714 bytes
  MessagePack: 0.103ms encode, 0.002ms decode, 1748 bytes
  Cap'n Proto: 0.002ms encode, 0.0001ms decode, 29 bytes

BraidDiatCodec is 2.5x smaller than MessagePack and encodes
braid data natively (Q0_2 fields, Mountain packed, MMR state).
 2026-05-30 14:36:16 -05:00
Brandon Schneider
c64e4f15eb docs: update AGENTS.md — BraidDiatCodec shim + bridge modules 
4-Infrastructure: add braid_diat_codec.py to stack-solidification anchors
Semantics: document BraidSpherionBridge admits (IntNodeToPhaseVec linearity, receipt_correspondence)
 2026-05-30 13:30:55 -05:00
Brandon Schneider
e797f06bd0 feat(shim): BraidDiatCodec Python extraction 
Python implementation of the 4-layer BraidDiatCodec:
- ChiralityDIAT encode/decode (64-bit slot)
- MountainPacked from_mountain/to_mountain
- BraidResidualPacked from_bracket/to_bracket (Q0_2 packing)
- BraidDiatFrame encode/decode

Benchmark: braid_diat (714B avg) vs messagepack (1748B avg)
on synthetic MMR/spike train frames.
 2026-05-30 13:30:01 -05:00
Brandon Schneider
ba203ca971 feat: spatial hash grid — GPU-style particle physics (Python + FPGA) 
Ported from ScaleSpaceSynth (WebGPU particle simulator):
- 64×64×64 spatial hash, 32 particles/cell, lock-free insertion
- Curl noise: divergence-free 3D turbulence
- Pairwise forces: attractive (ratio>0.15) + repulsive (ratio<=0.15)
- Trilinear density interpolation
- HalfLife particle lifecycle
- Q16_16 encode/decode for VCN transport

Python (spatial_hash_grid.py): 6/6 tests pass
  10K particles, neighbor query, forces, 100 sim steps, curl noise verified

FPGA (spatial_hash_bram.v):
  16×16×16 grid, dual-port BRAM, 27-cycle neighbor scan
  Density → voltage mode selector (STORE/COMPUTE/APPROX/MORPHIC)
  Integrated into research_stack_top.v

Same pattern as ScaleSpaceSynth GPU:
  GPU: atomicAdd for lock-free cell assignment
  FPGA: BRAM read-modify-write for cell assignment
  Ray: content-addressed ObjectRef for lock-free reads
  All: partition space → compute density → find structure at multiple scales
 2026-05-30 01:25:19 -05:00
Brandon Schneider
df6ea7ba15 feat: GCCL + WaveProbe + MetaProbe + delta compression 
Ports Lean formalization to Python:
- GCCL: LawAxis, PromotionRung, Decision, ScaleBand, Receipt, Wrapper, Transition
- gcclSwapGate: accept if new cost < old cost (from MassNumber.lean)
- fammRouteGate: route mass <= stress mass within thermal budget
- braidTransferGate: delta admissible <= delta risk
- WaveProbe: golden angle sampling (40503 = 1/φ × 65536)
- MetaProbe: probe-but-don't-commit, EXPORT_GRANT
- Delta compression with GCCL gates
- gccl_encode: full GCCL-gated encode pipeline

Tests:
  WaveProbe overlap (identical): 1.0000
  WaveProbe overlap (shifted): 0.6694
  MetaProbe (low residual): EXPORT_GRANT
  MetaProbe (high residual): HOLD
  GCCL transition admissible: True

All Q16_16 arithmetic (no Float in compute paths).
 2026-05-30 01:09:14 -05:00