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bigmerge b3f410fc91 engram: batch-cosine Adapter/Strategy/Factory over ggml, supersedes hand-rolled PR #114
El SDK CI - dev / build-and-test (pull_request) Failing after 4m29s
Stop hand-rolling GPU kernels for batch cosine similarity — use ggml (the
MIT-licensed compute library underneath llama.cpp, installed standalone via
Homebrew) as the preferred backend, without ripping out PR #114's
carefully-verified hand-rolled Metal shader.

Structure: one stable public adapter (eg_cosine_batch.h, zero #ifdef at call
sites) backed by three selectable concrete Strategies behind an internal
vtable (eg_cosine_batch_strategy.h) chosen by a Factory (eg_cosine_batch.c):

  - eg_cosine_batch_strategy_ggml.c    — NEW. ggml + dynamically-loaded Metal
                                          backend plugin (ggml_backend_load_all_from_path
                                          + ggml_mul_mat for the batched dot
                                          product), gather/scatter around the
                                          -2.0 sentinel contract.
  - eg_cosine_batch_strategy_metal_hand.m — PR #114's original hand-rolled
                                          Metal shader bridge, preserved
                                          almost verbatim, now one strategy
                                          among several rather than the only
                                          option. eg_cosine_batch.metal kept
                                          byte-identical to the original.
  - eg_cosine_batch_strategy_cpu.c     — universal always-false fallback
                                          (direct descendant of PR #114's
                                          eg_metal_cosine_stub.c).

Selection: EL_COSINE_BATCH_STRATEGY=ggml|metal|cpu|auto (default: ggml first,
then hand-rolled Metal, then CPU — first available wins), plus back-compat
EL_METAL_COSINE=0 to disable every GPU-backed strategy. build_vindex_bench.sh
compiles all three strategies on Darwin, CPU-fallback-only elsewhere.

vindex_bench.c now reports BRUTE-GGML and BRUTE-METAL side by side against
the same CPU oracle, on the same dataset, in one run (real numbers vs. real
store snapshot in the PR body).
2026-08-15 17:16:41 -05:00