Cambricon is shaping the future of artificial intelligence by going beyond chip development to build a comprehensive, high-performance AI software ecosystem. As large-scale AI models grow in size and complexity, the demand for powerful yet accessible and reliable infrastructure has never been greater. While Cambricon’s hardware provides the foundational computing power, it is the software that unlocks real-world value—enabling efficient model training and inference, seamless deployment across platforms, and scalable performance.
At the heart of this vision is a deeply integrated hardware-software collaboration. The company has developed five generations of intelligent processors and nine specialized AI chips, backed by a robust software platform that spans deep learning frameworks, compilers, operator libraries, distributed communication tools, and end-to-end solutions. This ecosystem allows users to migrate existing models with minimal effort, achieve high performance on Cambricon hardware, and operate efficiently in complex real-world scenarios—such as large language model inference, image and video generation, search, and recommendation systems.
Cambricon is actively building key software components that prioritize
usability,
performance, and
reliability. In framework development, the team maintains strong compatibility with open-source tools like PyTorch and TensorFlow, enabling developers to reuse existing code and debugging practices across different hardware platforms. They continuously optimize the full AI pipeline—from single-card tuning to large-scale distributed training—delivering performance in extreme conditions such as millisecond-level latency or stable operation at 10,000+ GPUs.
The compiler team is developing next-generation toolchains based on MLIR and LLVM, with support for OpenAI’s Triton language and a custom BangC programming language tailored to Cambricon hardware. These tools allow developers to write efficient, high-performance code that fully leverages the chip's architecture.
To further simplify development, Cambricon has created an intelligent agent powered by the Deepseek model. This agent can answer technical questions, generate optimized operators in Triton or BangC, and assist users throughout the software development lifecycle—dramatically improving productivity for both new and experienced developers.
Across computing libraries, distributed systems, and inference solutions, the team focuses on maximizing performance through deep optimization at every level: from low-level instruction tuning to high-level parallelism strategies. For example, distributed communication is optimized down to microsecond latency using advanced techniques like remote direct memory access and on-network computation. Inference and training solutions support major models such as Qwen3, DeepSeek, and OpenSora, applying innovations in expert parallelism, data flow optimization, and communication-computation co-design.
The driver team works at the most fundamental layer to optimize kernel performance, memory access patterns, and task scheduling—achieving nanosecond-level efficiency. Their work not only improves current systems but also informs future chip designs by identifying bottlenecks that can be translated into design requirements for next-generation SoCs.
Complementing these technical efforts is a strong focus on reliability. Cambricon’s operations platform enables real-time monitoring, rapid fault diagnosis, and automatic recovery in large-scale clusters—allowing users to detect and resolve issues before launching critical workloads. As cluster sizes grow exponentially, the team prepares for future scalability with robust, forward-looking system design.
