The same AI logic can behave very differently across embedded architectures. AURIX TC4x PPU, ARM Neon/SVE, RISC-V RVV, and x86 AVX expose different ways to use vector units, parallel execution, intrinsics, and hardware-specific capabilities.

If generated code stays too generic, these capabilities may remain unused. If it becomes too target-specific too early, portability and maintainability become harder.This is where vectorization and parallelization become architecture-dependent.

The emmtrix Edge AI Compiler addresses this through target-specific backend code generation based on an optimized intermediate representation.

Depending on the platform, this can include:

• platform-specific intrinsics
• compiler-specific vector C extensions
• inline assembly

For Edge AI, hardware-aware code generation is not a detail at the end. It is part of making generated code usable on the actual target.