A CPU that runs entirely on GPU

Original Article ↗ Hacker News Discussion ↗

Project concept

  • The project implements an AArch64 CPU simulator that runs entirely on a GPU using neural networks for ALU operations, including add, mul, sqrt.
  • Commenters frame it as a “because we can” hack, akin to CPUs in Game of Life or Minecraft, more about exploration than practicality.
  • Some note it’s closer to “a CPU on an NPU that happens to be a GPU” than a conventional CUDA-based GPU CPU-emulator.

Performance and practicality

  • One estimate: ~625,000× slower than a 2.5 GHz CPU for addition/subtraction.
  • People question real-world utility, but others argue it doesn’t need a practical purpose.
  • There is curiosity about how many such CPUs could run in parallel on one GPU and whether massive parallelism could offset slowness, but skepticism remains.
  • Comparisons are made to more efficient GPU CPU-emulation approaches (qemu-style dynamic translation to shaders), which could be orders of magnitude faster.

Neural arithmetic and exactness

  • Discussion around whether an LLM (or neural system) should perform exact arithmetic without external tools, versus just calling out to conventional hardware.
  • Some question why one would train networks for operations like sqrt when the GPU already has fast, precise hardware instructions.
  • The inversion where multiplication is much faster than addition is highlighted; explained by lookup-like parallelism for mul vs. carry chains for add.
  • Idea raised that a fully neural CPU makes execution differentiable, enabling backpropagation through programs for program synthesis, though not useful for normal OS work.

GPU vs CPU roles and future

  • Extended debate on whether GPUs could replace CPUs.
  • Consensus trend: CPUs and GPUs solve different problems (latency-sensitive, branchy vs massively parallel), and full replacement is unlikely.
  • Many expect continued convergence into heterogeneous systems (APUs, unified memory, mixed units like GPU, CPU, NPUs, FPGAs) rather than dominance of one.

Uses, OS-on-GPU, and culture

  • Project author’s stated long-term dream: an OS running purely on GPU or on “learned systems.”
  • Some link to prior work on parallel operating systems and “compute in memory” concepts.
  • Thread contains the usual “can it run Doom?” jokes, references to Doom-on-GPU, and playful renamings of “GPU,” capturing both amusement and admiration for the hack.