triton-ascend-case-elemwise-broadcast-3d

Community

Two-stage kernels for fast 3D elementwise broadcast

Authorxchang1121
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This skill targets performance improvements for cross-axis 3D broadcast by employing a two-stage kernel strategy, unlocking better vectorization and parallelism.

Core Features & Use Cases

  • Two-stage kernel approach: first broadcast expansion and reshape to 2D, then a second kernel operates on the flattened dimension for high throughput.
  • Performance uplift: especially effective when the last dimension is very small, improving utilization of hardware cores.
  • Use Case: accelerate 3D broadcast operations on tensors with shapes like (B, H, W) and (1, H, 1).

Quick Start

Run the two-stage kernel workflow on a 3D broadcast task to observe improved throughput.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: triton-ascend-case-elemwise-broadcast-3d
Download link: https://github.com/xchang1121/AutoResearch-CC-hook/archive/main.zip#triton-ascend-case-elemwise-broadcast-3d

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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