tinygrad/docs-legacy/OVERVIEW.md

tinygrad has four pieces

• frontend (Tensor -> LazyBuffer)
  • See tensor.py, function.py, multi.py, and lazy.py
  • The user interacts with the Tensor class
  • This outputs LazyBuffers, which form the simple compute graph
• scheduler (LazyBuffer -> ScheduleItem)
  • See engine/schedule.py
  • When a Tensor is realized, the scheduler is run to get its LazyBuffers to be computed
  • This takes in LazyBuffers and groups them as appropriate into kernels.
  • It returns a list of ScheduleItems + all the Variables used in the graph
• lowering (TODO: lots of work to clean this up still)
  • See codegen/ (ScheduleItem.ast -> UOps)
    • ScheduleItems have an ast that's compiled into actual GPU code
    • Many optimization choices can be made here, this contains a beam search.
  • renderer/compiler (UOps -> machine code)
    • UOps are tinygrad's IR, similar to LLVM IR
    • Here we either convert them to a high level language or machine code directly
  • engine/realize.py (ScheduleItem -> ExecItem)
• runtime
  • See runtime/
  • Runtime actually interacts with the GPUs
  • It manages Buffers, Programs, and Queues
  • Sadly, METAL and GPU (OpenCL) don't have a compiler that can be pulled out from the device itself