Development Tips
This section gives you some tips on the Taichi compiler development. Please make sure you have gone through developer installation.
Workflow of the Taichi compiler
Life of a Taichi kernel is a good place to get started, which explains the whole compilation process step by step.
C++ and Python standards
The C++ part of the Taichi compiler is written in C++17, and the Python part in 3.7+. You can assume that C++17 and Python 3.7 features are always available.
Efficient code navigation across Python/C++
If you are working on the language frontend (Python/C++ interface), you may want to navigate across Python/C++ code. ffi-navigator allows you to jump from Python bindings to their definitions in C++. Please follow their README to set up your editor.
Printing IRs in different stages
When creating a Taichi program using
ti.init(arch=desired_arch, **kwargs)
, pass in the following parameters
to make the Taichi compiler print out IRs in different stages:
print_ir=True
: print the Taichi IR transformation process of kernel (excluding accessors) compilation.print_accessor_ir=True
: print the IR transformation process of data accessors, which are special and simple kernels. This is rarely used, unless you are debugging the compilation of data accessors.print_struct_llvm_ir=True
: save the emitted LLVM IR by Taichi struct compilers.print_kernel_llvm_ir=True
: save the emitted LLVM IR by Taichi kernel compilers.print_kernel_llvm_ir_optimized=True
: save the optimized LLVM IR of each kernel.print_kernel_asm=True
: save the emitted assembly code of each kernel (CUDA only).
note
Data accessors in Python-scope are implemented as special Taichi
kernels. For example, x[1, 2, 3] = 3
will call the writing accessor
kernel of x
, and print(y[42])
will call the reading accessor kernel
of y
.