Today Qualcomm is announcing its AI unification offering. The Qualcomm AI Stack is designed to allow developers to build software that works across the company’s silicon offerings. This is a feature many other companies already have been working towards, but Qualcomm has a unique set of silicon solutions.
Qualcomm AI Stack Aims to Achieve Parity with NVIDIA Intel and Others
The basic idea behind the Qualcomm AI Stack is to unify some of the front-end SDKs for developers. Most of these AI frameworks, like CUDA for NVIDIA, OneAPI for Intel, AMD AI Stack, and so forth, are to allow programmers to work in environments like TensorFlow and PyTorch and then optimize and run on many different silicon platforms. Qualcomm has markets that tend to be focused more on edge devices. As a result, the AI Stack is designed to help applications run across different segments.
One of the fun features of the Qualcomm slide is that it still has CentOS. Red Hat Goes Full IBM and announced it would discontinue CentOS in 2020 and finally discontinued CentOS many months ago. We have not seen many recent software announcements trumpeting CentOS support because of this.
An example of where this may be used is that a facial recognition application may be built to unlock a device. Qualcomm’s AI Stack will then help make that application run on the company’s chips in phones, ACPCs, and perhaps even automobiles.
Most AI companies are working on some sort of abstraction, but many silicon vendors that have broad portfolios realize they need unified software tools to help cross-platform sales. Intel is a great example of this where they are enabling AI across a range of architectures, form factors, and platforms. Intel started on its OneAPI journey years ago, and it is still ongoing. NVIDIA has offered CUDA tools to make this a baseline capability for years. Developers working in NVIDIA CUDA can run software on the company’s supercomputer GPUs all the way down to <$100 Jetson embedded devices.
Overall, this is the right direction for Qualcomm. The company needs something like this to remain competitive in AI, especially as it targets customers that are using different types of chips. In the future, the vast majority of computing devices will have some sort of AI acceleration but the diversity will necessitate tools like this.