interpreters

The best dispatch strategy for a bytecode interpreter depends on your CPU's branch predictor, with computed goto and direct threading often outperforming standard switch dispatch by reducing branch mispredictions. Trade-offs exist between portability, maintainability, and raw execution speed.

To represent values efficiently in a stack-based VM, use tagged pointers or NaN boxing to pack type information and payload tightly. This minimizes memory overhead and keeps hot VM state cache-friendly during arithmetic and call operations.

Inline caching improves bytecode interpreter performance by memoizing lookup results at specific call sites, bypassing expensive runtime dispatch for monomorphic or polymorphic operations. This drastically reduces overhead in hot loops and repetitive method calls.

You can build a simple baseline JIT compiler using mmap and mprotect to allocate executable memory for emitting raw x86-64 machine code. This approach allows small scripting language runtimes to compile hot arithmetic operations dynamically.

Choosing between a stack-based and register-based VM architecture involves trade-offs between implementation complexity and instruction dispatch overhead. Register-based VMs often yield shorter bytecode and fewer dispatch cycles, while stack-based VMs are simpler to compile targeting.

High overhead in a bytecode dispatch loop usually stems from branch mispredictions in switch-based dispatch and poor cache locality. Migrating to computed goto or direct threading helps the CPU predictor and reduces hot loop stalling.