Source URL: https://hardware.slashdot.org/story/25/07/22/2042234/nvidias-cuda-platform-now-support-risc-v?utm_source=rss1.0mainlinkanon&utm_medium=feed
Source: Slashdot
Title: Nvidia’s CUDA Platform Now Support RISC-V
Feedly Summary:
AI Summary and Description: Yes
Summary: Nvidia’s announcement at the 2025 RISC-V Summit about CUDA compatibility with the RISC-V instruction set architecture signifies a pivotal shift in leveraging open processors within AI-related applications. This move enables RISC-V CPUs to play a central role in heterogeneous computing environments, particularly for edge devices and potentially in data centers, enhancing the landscape of computation and deployment for AI workloads.
Detailed Description:
– Nvidia has officially declared that its CUDA software platform will support the RISC-V instruction set architecture (ISA), which marks a significant milestone for the RISC-V ecosystem.
– The presentation occurred during the 2025 RISC-V Summit in China, underscoring Nvidia’s commitment to integrating its technologies with open architectures.
– **Key Points & Implications**:
– **CUDA Compatibility**: This allows RISC-V CPUs to be fully integrated into CUDA-based systems, traditionally dominated by x86 or Arm architectures, thus broadening computational diversity.
– **Applications in Edge Computing**: While RISC-V may not yet be prevalent in hyperscale data centers, its compatibility with Nvidia’s edge devices (like Jetson modules) suggests it will play a notable role in edge computing applications, especially for AI-related tasks.
– **Heterogeneous Computing Vision**: The diagram showcased during the presentation illustrates a computing architecture where the GPU is responsible for handling parallel workloads, while the RISC-V CPU manages system drivers, application logic, and the operating system, demonstrating Nvidia’s vision for multiple processors working together efficiently.
– **Inclusion of DPUs**: The presence of a data processing unit (DPU) handling networking tasks indicates Nvidia’s holistic approach, integrating different components (GPU, CPU, DPU) to manage workloads more effectively.
– **Open vs. Proprietary Dynamics**: By bridging its proprietary CUDA framework to an open architecture like RISC-V, Nvidia is navigating the complexities of global markets, particularly given its inability to ship certain products to China. This strategic pivot could prevent isolation in a rapidly evolving tech landscape and foster innovations aligned with the industry’s shift toward open standards.
In conclusion, this development could significantly impact how AI workloads are orchestrated and processed, making it essential for professionals in AI, cloud, and infrastructure security to stay informed about the implications of RISC-V’s growing role in the computational architecture.