popov/neuron-tai
1
0
Fork 0
Code Issues 42 Pull Requests Actions Packages Projects Releases Wiki Activity

story: DGR-036 Prove dense fixture and real-model range parity

Browse Source
This commit is contained in:
Dobromir Popov
2026-08-01 01:20:16 +03:00
parent 6e88b3bd8f
commit 6e8bf7a64d
3 changed files with 141 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
.scratch/distributed-gguf-runtime/evidence/DGR-036/BLOCKED.md Normal file
View File

@@ -0,0 +1,12 @@
# DGR-036 real-model lane blocker
`DGR-036` cannot receive completion credit yet. The live standalone worker is DGR-033's `FakeShardEngine`, a CRC/echo fixture; DGR-037's real llama.cpp `ShardEngine` binding has not been implemented. Consequently no code path can execute a whole or ranged dense GGUF and no real prefill/logit or greedy-token parity result exists.
The deterministic two-process fake-worker regression is implemented in `tests/test_native_shard_worker.py`, but this sandbox cannot open loopback sockets (`PermissionError: [Errno 1] Operation not permitted`), so that runtime test needs host-side execution as well.
Unblock in this order:
1. Complete DGR-037's real ranged llama.cpp worker binding without changing the DGR-035 dense boundary contract.
2. Provision a small exact dense GGUF on mounted-drive storage and record its artifact/split hashes plus runtime/backend/hardware/network identity.
3. Run whole-model and two-range prefill comparison, then record at least 32 greedy token IDs against the locked tolerance and retain raw metrics.
4. Run the deterministic two-process test on a host with loopback sockets, then update `README.md` and only then set `prd.json` completion truth.