Another orthogonal aspect with modern hardware is the increased amount of parallel execution. Most of the standard programming languages are not really designed to support this well. So we use extensions like CUDA. But this is not really general purpose but only for GPU.
Once we reach maybe 100 cores, or 1000 cores, or some orders of magnitude more cores in the CPU, we have to have better general purpose language support for this. Most memory is local for some subset of cores. There are warps which execute the same code (SIMT).
What's this "once"? This was a theory of future CPUs from maybe a decade ago that totally hasn't happened. We're instead getting increasingly smaller few-core CPUs in things like smartwatches. In laptops, M1 replaces a hyperthreading CPU with one that runs a single thread much faster.
Once we reach maybe 100 cores, or 1000 cores, or some orders of magnitude more cores in the CPU, we have to have better general purpose language support for this. Most memory is local for some subset of cores. There are warps which execute the same code (SIMT).