NVIDIA CUDA

Yes. The CUDA 13.4 preview adds "Cross-compiling Windows Arm64 CUDA applications using the Windows x86_64 Toolkit," and NVIDIA's Developer Preview drivers and CUDA release let developers build and test Arm64 builds without RTX Spark hardware by using existing Windows on Arm development systems. Answered

Earlier this week at GTC Taipei, NVIDIA unveiled the NVIDIA RTX Spark product family, including small form factor desktops and laptops built for the age of personal assistants. These desktops and laptops deliver 1 petaflop of AI power, up to 128 GB of memory, and CUDA-accelerated AI frameworks for running large models alongside everyday work.  Microsoft is creating an RTX Spark special developer edition—the Microsoft Surface NVIDIA RTX Spark Dev Box—preloaded with a modified Windows configured for developers and the top developer tools you need to get started. To learn more, see Building the n

At the front end, GPU-accelerated simulations expand the design space, giving materials engineers a powerful advantage in developing next-generation devices. In the middle, physics-based modeling speeds up chamber and recipe development. At the back end, AI-driven digital twins predict fab performance before changes hit the production floor. Putting these together creates a continuous flow of insights that drives faster progress from atoms to fabs.

Agentic AI infrastructure must optimize more than individual GPUs; it must make effective use of power, cooling, networking, and rack-level resources across the entire AI factory. NVIDIA Vera Rubin NVL72 extends the GPU architecture into an integrated, resilient rack-scale execution domain. This section examines how NVIDIA approaches power efficiency, operational scalability, and system-level reliability.