Instruction-level control with Inline Elementwise ASM in Triton

Triton, a domain-specific language for GPU programming in Python, simplifies the process of writing fast GPU kernels by abstracting complexities like memory management and synchronization while generating optimized code. However, when precise control over device-specific assembly instructions is required, Triton allows users to inject inline elementwise assembly code, particularly useful for operations like bit packing or employing special instructions not natively supported. The blog explores how Triton compiles Python kernels into NVIDIA's PTX assembly code, and demonstrates the use of inline assembly to enhance performance and flexibility, especially in scenarios like elementwise operations and quantization on GPUs. While this technique permits fine-tuned performance optimization similar to hand-crafted CUDA code, it also introduces trade-offs such as increased responsibility for correctness and potential portability issues. The blog suggests a balanced approach, using Triton for most of the kernel code with inline PTX injected strategically to achieve near-CUDA performance while maintaining Python's ease of use.