cpu-basics

Explain foundational CPU kernel concepts and patterns for AKG operators.

258|48|Updated Jun 22, 2020
One-click install
npx skills add https://github.com/mindspore-ai/akg --skill cpu-basics-mindspore-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cpu-basics
Source: https://github.com/mindspore-ai/akg/tree/main/akg_agents/python/akg_agents/op/resources/skills/cpp/guides/cpu-basics
Command: npx skills add https://github.com/mindspore-ai/akg --skill cpu-basics-mindspore-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides foundational concepts and standard patterns for CPU-based AKG kernels, guiding engineers to structure and implement operators efficiently.

Core Features & Use Cases

  • Kernel concepts: Kernel, tensor handling, memory management, and type safety.
  • Standard five-step kernel structure: sequence from input validation to output creation and type restoration.
  • KernelBench templates and inline C++ guidelines for rapid CPU operator development.

Quick Start

Create a minimal CPU kernel scaffold following the standard five-step pattern to implement your first operator.

Frequently Asked Questions about cpu-basics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is the standard structure for writing a CPU kernel in AKG?▼

The standard CPU kernel structure in AKG follows a five-step sequence progressing from input validation to output creation and type restoration, ensuring contiguous memory handling and type safety.

How do I implement a CPU operator with contiguous memory handling?▼

To implement a CPU operator with contiguous memory handling, apply the standard five-step AKG kernel pattern that sequences input validation, tensor processing, memory management, output creation, and type restoration.

Can I use AKG kernel patterns for both x86_64 and aarch64 architectures?▼

Yes, AKG CPU kernel concepts and patterns are applicable across both x86_64 and aarch64 architectures for performance-focused operator implementations and kernel design.

What's the best way to start developing CPU-backed operator implementations?▼

The best way to start developing CPU-backed operators is by creating a minimal kernel scaffold using KernelBench templates and inline C++ guidelines following the foundational five-step pattern.

Does AKG support type safety and tensor handling for CPU kernels?▼

Yes, AKG supports type safety and tensor handling for CPU kernels by incorporating these concepts directly into the foundational kernel structure and standard implementation patterns.

Why do I need a five-step pattern for CPU kernel design?▼

You need the five-step pattern for CPU kernel design to ensure a simple, consistent startup guide that properly sequences input validation, tensor handling, memory management, output creation, and type restoration.