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The CPU backend on Kotlin/Native macOS currently uses scalar loops for all tensor operations. This documents the plan to add Apple Accelerate framework integration (cblas_sgemm, vDSP_*) for 5-20x speedup on native macOS. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Replace scalar DefaultCpuOps on Apple platforms with AccelerateCpuOps that dispatches hot-path operations to Apple's Accelerate framework: - matmul: cblas_sgemm (NEON + AMX hardware acceleration) - add/subtract/multiply/divide: vDSP_vadd/vsub/vmul/vdiv - sum/mean: vDSP_sve/meanv - relu: vDSP_vthres - silu: optimized scalar loop on contiguous buffer - transpose: vDSP_mtrans All operations fall through to DefaultCpuOpsBase for non-FP32, non-contiguous, or complex broadcasting cases. Split PlatformCpuOpsFactory from single nativeMain actual into: - appleMain (macOS + iOS) → AccelerateCpuOps - linuxMain → DefaultCpuOps (scalar fallback) All 23 existing test suites pass on macosArm64 with zero failures. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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