biren-sudnn

What problem does it solve?

This Skill provides a comprehensive deep learning operator library optimized for wall-rted hardware, enabling efficient training and inference of neural networks.

Core Features & Use Cases

• Neural Network Building Blocks: Offers 42+ operators like convolution, pooling, activation, normalization, and matrix multiplication, essential for deep learning model development.
• Performance Optimization: Supports eager and graph APIs to optimize execution and performance on壁仞 GPUs for model deployment and research.
• Use Case: FAEs and developers can rapidly build, test, and deploy high-performance neural network models for autonomous systems, computer vision, or NLP tasks.

Quick Start

Configure environment variables, initialize API handles, and invoke operators for training or inference workflows.