Files
neuron-tai/.scratch/distributed-gguf-runtime
Dobromir Popov 7da90ef475 feat: implement numbered patch-stack apply/verify enforcement (DGR-028)
Split the range-loader patch into single-concern patches 0002-0005 (loader,
filtered state report, boundary I/O endpoint guard, worker range-report
hook), add UPSTREAM-ASSUMPTIONS.json describing each patch's assumptions,
and enforce control-plane/license boundary checks plus first-incompatible-
patch reporting in scripts/llama_cpp_dependency.py apply/reverse/verify.

7 passed in tests/test_llama_cpp_dependency.py; SHA256SUMS verified against
all five patches; focused native CTest (test-meshnet-range-ownership 1/1)
recorded in evidence README (build/ dir not present in this environment to
independently reverify).
2026-07-21 13:22:55 +03:00
..

Distributed GGUF Runtime planning workspace

Specification status: planning artifacts only. No distributed GGUF runtime is implemented. DGR-017 cleanup is complete; no runtime implementation story has completion credit. prd.json is authoritative.

Locked scope

  • Existing Meshnet Tracker routing, load balancing, billing, telemetry, relay, and provider semantics are backend-agnostic and are not redesigned. GGUF contributes exact compatibility, range/capacity, queue/load, seam-cost, health/reliability, and certification inputs only.
  • The data plane is a standalone project-owned C++ Shard worker with gRPC/Protobuf and a project-owned ShardEngine boundary.
  • llama.cpp is fetched at one exact commit into an ignored workspace from an in-repo manifest, then a numbered minimal patch stack is applied. There is no submodule, vendored tree, or permanent-fork dependency.
  • llama.cpp owns DeepSeek V4 graphs, mHC, MoE, attention, hash routing, and kernels. Meshnet adds only range-ownership hooks, typed boundary/local-state adapters, worker integration, and parity/certification.
  • Quantization and placement are dynamic recipe inputs. The 24 and 10+ stage layouts are certification scenarios, never product constants.
  • Per-shard Hot KV and V4 CSA/HCA/SWA/indexer/compressor state remain local and keyed by route session/epoch. The WAN seam carries the typed mHC 4×4096 residual boundary, positions, token-ID sideband where required, and schema/cache expectations—not per-layer caches.
  • Route changes use cache miss plus re-prefill/restart. There is no WAN KV or V4 auxiliary-cache migration.
  • CPU/CUDA/ROCm/Vulkan/Metal compile lanes are planned; only exact real-hardware-certified backend/model/recipe lanes may be advertised.
  • Alpha requires correctness and the pre-locked useful-speed gate. MTP is reserved and off for alpha; its ownership contract, implementation, and benchmark are required before beta.

Target identities

  • DeepSeek V4 official target SHA: 60d8d70770c6776ff598c94bb586a859a38244f1.
  • llama.cpp V4 support lineage began at PR 24162 / merge 8c146a8366304c871efc26057cc90370ccf58dad; DGR-027 later pins one exact validated current commit.
  • V4 scope: 43 main layers plus MTP; mHC 4×4096 boundary; 256 routed + 1 shared experts with six routed active; token IDs required for the first three hash-routed layers.
  • Exact split-GGUF artifacts are provisioned to mounted-drive storage with a complete hashed manifest and resumable verification; no model artifact may be placed under /home.

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