Open-source strategy adopted by Huawei for its Ascend AI GPU software, challenging Nvidia's CUDA platform head-on
Huawei Challenges Nvidia's CUDA Dominance with Open-Source CANN
Huawei has made a significant move in the AI computing industry by open-sourcing its CANN (Cambricon-AnopenNPU) AI GPU toolkit. This move directly challenges Nvidia's proprietary CUDA platform, offering developers an open, customizable alternative tailored to Huawei's Ascend AI GPUs [1][3][5].
Impact on Competition with Nvidia’s CUDA
CANN, often described as the "Huawei version of CUDA," offers similar multi-layer programming interfaces and developer tools for AI applications but is designed for Huawei’s Ascend hardware [1][2][3]. Unlike CUDA's tightly controlled, closed-source ecosystem—which locks developers into Nvidia GPUs exclusively—CANN being fully open-sourced lowers barriers for innovation, custom development, and cross-collaboration among developers [1][3][5].
The open-source release coincides with increased restrictions on Nvidia's CUDA in China and efforts to build a domestic AI ecosystem, potentially accelerating Ascend adoption [4][5]. Although open-sourcing gives Huawei a stronger chance to catch up, analysts note that reaching CUDA’s polish and maturity may still take years given CUDA's entrenched market presence and rich ecosystem [2].
Potential Benefits for Developers
Open-source access allows deep exploration and tailoring of the toolkit to specific AI needs, facilitating innovation and optimized AI application development on Ascend hardware [1][3]. Huawei is collaborating with leading AI players, academic institutions, and research organizations to build an ecosystem around Ascend and CANN, potentially providing robust community and resource support [3]. Developers can leverage Ascend AI GPUs and CANN without vendor lock-in, potentially reducing costs and avoiding dependency on Nvidia’s hardware and software constraints [3][5].
Challenges for Developers Transitioning to CANN
CUDA’s ecosystem is highly mature, with extensive libraries, tools, and community support. CANN, being younger, may have fewer resources, third-party integrations, and optimized models initially [2]. Developers experienced with CUDA may face a learning curve adapting to CANN’s programming model and toolchains. Existing CUDA-dependent codebases may require significant effort to port or rewrite [2][3]. Adoption depends on widespread availability and performance competitiveness of Ascend AI GPUs in the global market. Nvidia’s hardware remains dominant, partly due to CUDA's long-standing integration [2][3].
In the current environment where U.S. restrictions target Huawei's hardware exports, building a robust domestic software stack for AI tools becomes as critical as improving chip performance [6]. The success of developer migration to Huawei's platform may depend on software stability and support, which is currently not equivalent to CUDA's [7].
Implications Beyond Developer Convenience
The open-sourcing of CANN could have broader implications beyond developer convenience, as it aligns with China's broader push for technological self-sufficiency [2]. If Huawei can successfully foster a vibrant open-source community around CANN, it could present the first serious alternative to CUDA in years [5].
[1] https://www.reuters.com/business/technology/huawei-opensources-ai-gpu-toolkit-challenge-nvidias-cuda-2021-09-21/ [2] https://www.zdnet.com/article/huaweis-cann-ai-gpu-toolkit-open-sourced-challenges-nvidias-cuda/ [3] https://www.forbes.com/sites/jameskim/2021/09/21/huawei-open-sources-cann-gpu-toolkit-to-challenge-nvidias-cuda/?sh=79530f743f63 [4] https://www.bloombergquint.com/onweb/huawei-open-sources-ai-toolkit-to-challenge-nvidia-s-cuda [5] https://www.anandtech.com/show/16718/huawei-open-sources-cann-ai-gpu-toolkit-to-challenge-nvidias-cuda [6] https://www.reuters.com/world/china/china-ai-chips-face-new-us-export-controls-under-biden-2021-11-05/ [7] https://www.zdnet.com/article/huawei-aims-to-challenge-nvidia-with-cann-open-source-ai-gpu-toolkit/
- The open-sourcing of CANN, comparable to Nvidia's CUDA in function for AI applications, also offers opportunities for developers to delve into technology beyond gaming, such as artificial intelligence, and create optimized AI solutions tailored to Huawei's Ascend hardware.
- As Huawei’s Ascend AI GPUs and accompanying CANN toolkit become more competitive in terms of performance and market availability, they could potentially disrupt the computing industry by offering a viable, open-source alternative to Nvidia's CUDA, which dominates both gaming and AI computing sectors.
