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Dequantize quantized/BF16/F32 KV caches to F16, then route them through oneDNN's fused SDPA primitive for XMX acceleration. Fills the gap between #25222 (native F16 SDPA) and the existing TILE/VEC fallback.
No dependency on #25025 — HYBRID falls back to TILE, not MKL.
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ggmlchanges relating to the ggml tensor library for machine learningSYCLhttps://en.wikipedia.org/wiki/SYCL - GPU programming language
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Dequantize quantized/BF16/F32 KV caches to F16, then route them through oneDNN's fused SDPA primitive for XMX acceleration. Fills the gap between #25222 (native F16 SDPA) and the existing TILE/VEC fallback.
No dependency on #25025 — HYBRID falls back to TILE, not MKL.
Dispatch funnel: ONEDNN → HYBRID → TILE/VEC.