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

Triton differs from CUDA

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

Triton auto-tunes BLOCK_SIZE: different sizes optimize for different hardware

Triton auto-tunes BLOCK_SIZE for hardware efficiency, optimizing memory access patterns and computational throughput

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

a Triton kernel is

Triton kernel: Python-based GPU programming that compiles to PTX

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