36 lines
1.7 KiB
C++
36 lines
1.7 KiB
C++
#pragma once
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#include <memory>
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#include <vector>
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// ── ISimilarityEngine ─────────────────────────────────────────────────────────
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// Backend-agnostic gallery similarity engine for the identity matcher.
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//
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// The full reference gallery (n_gallery × 512 L2-normalised embeddings) is
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// uploaded to the GPU once at construction and stays resident. Per frame, the
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// small query matrix (n_faces × 512) is uploaded and a single SGEMM produces the
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// similarity matrix S (n_gallery × n_faces, column-major) — i.e. S[g + f*n_gal]
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// is cosine_similarity(gallery[g], query[f]).
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//
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// The GPU math backend (cuBLAS/CUDA or rocBLAS/HIP) is selected at compile time
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// by CMake (SAE_GEMM_BACKEND); backends/gemm_backend.cpp provides
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// make_similarity_engine(). The core matcher node sees only this interface and
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// holds no CUDA/HIP/BLAS headers.
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struct ISimilarityEngine {
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virtual ~ISimilarityEngine() = default;
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// Largest n_faces accepted by compute() per call (bounds GPU buffer sizes).
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virtual int max_faces() const = 0;
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// Compute similarities for n_faces query embeddings.
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// query_row_major: n_faces × 512, row fi at query + fi*512.
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// Returns a pointer to host memory holding S column-major: the gallery
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// similarities for face fi start at result + fi*n_gallery. The pointer is
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// owned by the engine and valid until the next compute() call.
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virtual const float* compute(const float* query_row_major, int n_faces) = 0;
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};
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// gallery_row_major: n_gallery × 512, embedding i at gallery + i*512.
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std::unique_ptr<ISimilarityEngine> make_similarity_engine(
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const float* gallery_row_major, int n_gallery, int max_faces);
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