Neural Net Compiler:

  
      github.com
  
  
    pytorch/pytorch/blob/6e4de445010ef5e9e0438e4a4c16f6ef3129af14/test/cpp/tensorexpr/tutorial.cpp#L13 60

// This tutorial covers basics of NNC's tensor expressions, shows basic APIs to// work with them, and outlines how they are used in the overall TorchScript// compilation pipeline. This doc is permanently a "work in progress" since NNC// is under active development and things change fast.//// This Tutorial's code is compiled in the standard pytorch build, and the// executable can be found in `build/bin/tutorial_tensorexpr`.//// *** What is NNC ***//// NNC stands for Neural Net Compiler. It is a component of TorchScript JIT// and it performs on-the-fly code generation for kernels, which are often a// combination of multiple aten (torch) operators.//// When the JIT interpreter executes a torchscript model, it automatically// extracts subgraphs from the torchscript IR graph for which specialized code// can be JIT generated. This usually improves performance as the 'combined'// kernel created from the subgraph could avoid unnecessary memory traffic that// is unavoidable when the subgraph is interpreted as-is, operator by operator.// This optimization is often referred to as 'fusion'. Relatedly, the process of// finding and extracting subgraphs suitable for NNC code generation is done by



  
  
    
    
  
  


I’ve written a JIT tutorial on fusers (from a user perspective mostly looking into how things reach the fuser, hopefully online soon) and I standardized on calling them the TensorExpr fuser and the CUDA fuser.
Best regards
Thomas