triton-ascend-example-relu

What problem does it solve?

This skill demonstrates how to implement and validate a Triton Ascend-based elementwise ReLU kernel, providing a concrete example for high-performance kernel development on Ascend hardware.

Core Features & Use Cases

• 1D tiling and BLOCK_SIZE-based processing to maximize throughput.
• Boundary masking to handle arbitrary input lengths safely.
• Interleaved execution and PyTorch integration for easy testing and reuse.
• Use Case: reference for building other elementwise ops on Ascend devices.

Quick Start

Run the triton-ascend-example-relu tutorial to execute the kernel on a sample input tensor.