英伟达computeX 大会--NVLink Fusion

Core Viewpoint - Nvidia's introduction of NVLink Fusion aims to enhance flexibility and customization in AI infrastructure while maintaining its technological advantage in the market [8][17]. Group 1: Nvidia's Development and Products - Nvidia has evolved from focusing on GPUs to becoming a giant in AI infrastructure, with significant milestones such as the launch of CUDA in 2006 [1]. - The GB300 chip, set to launch in Q3, boasts a 1.5x improvement in inference performance, HBM memory, and a 2x increase in network bandwidth, while maintaining physical compatibility with previous generations [6]. - The Project DIGITS personal AI computer, DGX Spark, is now in full production, with availability expected by Christmas [6]. Group 2: NVLink Fusion Technology - NVLink Fusion extends Nvidia's NVLink technology to third-party CPUs and accelerators, allowing for a more open ecosystem while still requiring Nvidia chips in the system [8][10]. - The technology includes two components: a semi-custom CPU connection via NVLink C2C and the integration of NVLink 5 Chiplet into third-party accelerators [9][10]. - NVLink Fusion is designed as a "either/or" technology, allowing for either a semi-custom CPU or GPU but not both simultaneously, ensuring Nvidia's presence in the system [10]. Group 3: Market Implications and Partnerships - Current partners for NVLink Fusion include Alchip and AsteraLabs, with Fujitsu and Qualcomm developing new CPUs compatible with Nvidia GPUs [11]. - The limited openness of NVLink Fusion may accelerate diversification in AI computing infrastructure and provide pathways for third-party chips to enter the high-performance computing market [11][17]. - Nvidia's strategy reflects an understanding that a fully closed NVLink could limit market expansion, particularly among cloud service providers and sovereign AI projects [17]. Group 4: NVLink Advantages - NVLink 5 offers a dual bandwidth of 1.8 TB/s, significantly outperforming PCIe 5.0, which is crucial for scaling AI model training and inference [20]. - The NVLink Switch chip enables rack-level scalability, supporting up to 72 GPUs with a total bandwidth of 130 TB/s, a capability that competitors struggle to match [20]. - The integration of NVLink with Nvidia's SHARP protocol and Mission Control software optimizes AI workload throughput and latency, enhancing overall performance [20].