tl.program_id(0) returns: the index of the current parallel block

tl.arange(0, BLOCK_SIZE) creates: a range of indices within the current block

`tl.arange(0, BLOCK_SIZE)` creates a range of indices from 0 to BLOCK_SIZE-1

tl.dot does in Triton: block-level matrix multiply using tensor cores

tl.dot performs block-level matrix multiplication using tensor cores in Triton

BLOCK_SIZE means in Triton: the tile size each program instance processes

BLOCK_SIZE in Triton refers to the size of the data chunk processed by each program instance

tl.load and tl.store do in Triton: read/write tensors from/to GPU global memory

`tl.load` reads tensors from GPU memory; `tl.store` writes tensors to GPU memory

tl.where(mask, x, 0) does: conditional select to handle boundary conditions

`tl.where(mask, x, 0) = x if mask else 0`

Triton differs from CUDA

Triton uses block-level programming, while CUDA uses thread-level programming