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China's IC design industry is nearing CNY1 trillion (approx. US$150 billion) ahead of schedule, but AI is exposing deeper gaps in computing architecture, high-end talent, and ecosystem control.

PRESS RELEASE — The Eclipse Qrisp developer community has integrated Eclipse Qrisp – the open-source framework for quantum programming initiated by Fraunhofer FOKUS – with the NVIDIA CUDA-Q platform for hybrid quantum-classical computing. The integration will be made publicly available later this year. The integration enables a straightforward workflow: developers write quantum programmes in Qris

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PRESS RELEASE — Qilimanjaro Quantum Tech’s software development toolbox QiliSDK is now integrated with NVIDIA CUDA-Q – the platform for quantum-classical computing. This upgrade provides researchers with GPU acceleration for production-scale emulation of quantum workflows on classical hardware. Qilimanjaro’s unique multimodal approach now extends across classical and quantum backends, from CPUs an

AMD's Lemonade SDK For Local AI Adds NVIDIA CUDA Support Written by Michael Larabel in AMD on 10 June 2026 at 12:25 PM EDT. Add A Comment Lemonade, the local AI server solution developed by AMD that is designed to work across their CPUs, GPUs, and NPUs, is out with a new version today that also adds NVIDIA CUDA support. THe Lemonade SDK provides local AI server capabilities in an API-compliant ma

NVIDIA CUDA 13.3 Rolls Out CUDA Python 1.0, CUDA Tile For C++ Written by Michael Larabel in NVIDIA on 27 May 2026 at 04:22 PM EDT. Add A Comment NVIDIA on Tuesday released CUDA 13.3 as another significant advancement for their unified GPU programming stack for NVIDIA hardware. For those wanting to tap the power of CUDA from the Python programming language, CUDA 13.3 marks the CUDA Python 1.0 mile

NVIDIA CUDA 13.3 brings new capabilities and performance optimizations to developers across the CUDA ecosystem. The launch of NVIDIA CUDA Tile programming in C++, enables high-level, tile-based kernel development that automatically manages complex low-level GPU details for optimal performance and portability. Additionally, CUDA Tile programming is now supported on Compute Capability 9.0 (NVIDIA Ho

Developers can now use NVIDIA CUDA Tile programming within large existing C++  GPU codebases to develop highly optimized GPU kernels using tile-based abstractions.  NVIDIA CUDA Tile, launched with NVIDIA CUDA 13.1, introduced tile-based programming for GPUs. Designed with a top-level language layer and another intermediate layer that any high-level programming language can target, CUDA Tile autom