FastStrata v0.4.0

A new engine: while an answer is written, the VRAM that prompts are read through holds more of the model's experts.
On the 6 GB test laptop an agent's answers are written 3% faster; on a 4 GB card, where no expert fitted in VRAM
before, a third of them do now. The README says what a 4 GB card runs: which Qwen file, which context cache and how
long a context. The ready-made engine of this release is a new file,
strata-poly-windows-x64-5a009f5d29282ef6.zip (RTX 20 to RTX 50, CUDA 13.0).

• --lend-staging (step 13 of docs/OPTIMIZATION_LOG.md): while an answer is written, the 500 MiB staging buffer that
  prompt batches copy experts through holds cached experts, and it goes back before the next batch. On the 6 GB test
  laptop an agent's 35 answers were written at 85.0 and 83.9 tok/s where 82.1 and 82.0; on the laptop with 2 GiB held
  (a 4 GB card) a third of the experts came from VRAM where none did, 11 to 19% faster without guesses. The answers
  move as between two runs without it. Setup writes it on one NVIDIA card. It needs this release's engine: with an
  older one setup leaves the option out and says so. An install updated with UPDATE.bat keeps its config: add
  "--lend-staging" to the args of strata-<model>.json.
• STRATA_ROUTE_TRACE and STRATA_SWAP_HALF (step 12), tools for measuring the expert cache: a trace of the routing
  and of what the cache held, for a simulator of cache rules (in the working repository). No rule the simulator
  tried beat the engine's own by more than 3%, and tables of experts by kind of work (code, documents) did not help.
• README.md and README.pl.md: a section on a 4 GB card, measured on the 6 GB card with 2 GiB held: Q4 (UD-Q4_K_M)
  with the 8-bit context cache at 32K, Q3 (UD-Q3_K_M) up to 48K, which to take with 32 GB of RAM and with more, and
  what was not measured.
• Without the new options the engine writes v0.3.0's tokens.