Orient Securities has released a research report stating that in the short term for communications, a single-layer scale-up domain using copper cables remains a preferable solution. If a dual-layer architecture is adopted for the scale-up domain, a combination of copper and optical solutions will be used. For the high-computing-density Kyber architecture, orthogonal backplanes are gradually becoming prominent. In scale-out scenarios, Co-Packaged Optics (CPO) solutions are maturing. Regarding cooling, all five different racks in the Vera Rubin POD utilize 100% liquid cooling. For power supply, 800V High Voltage Direct Current (HVDC) is transitioning from an optional feature to a standard for AI Data Centers (AIDC). In space computing, NVIDIA's involvement is expected to accelerate the maturation of the ecosystem.

Key viewpoints from Orient Securities are as follows:

The inference-optimized Groq 3 LPX has been launched, focusing on low-latency tasks with significant commercial benefits. On March 17, the 2026 GTC conference commenced, where NVIDIA unveiled the LPX rack. The Groq 3 LPX specializes in inference acceleration. The core of the LPX rack consists of the Groq 3 LP30 LPU (Language Processing Unit). The LPU features a flat, SRAM-dominated memory architecture designed for fast and predictable token generation. A single Groq 3 LPX rack contains 32 liquid-cooled 1U compute trays, collectively delivering 315 PFLOPS of AI inference computing power, 128GB of total SRAM capacity, and 640TB/s of total scale-up bandwidth. When paired with the LPX, the Rubin rack offers over 35 times more tokens processed per megawatt for trillion-parameter models and over 10 times greater revenue opportunities compared to the Blackwell architecture. The report suggests that the introduction of the LPU addresses the high cost issues of single-GPU systems in current high-end model inference scenarios. Deploying the Rubin+LPX combination is expected to indirectly improve the profitability of cloud providers, accelerate the adoption of low-latency AI inference applications, gradually activate the vast inference demand market, and further drive demand for PCBs, liquid cooling, power supply, optical communication, and copper cables.

Vera CPU Rack: The Foundation for Large-Scale AI Agents and Reinforcement Learning NVIDIA has introduced the Vera CPU rack, which contains 32 liquid-cooled Vera CPU trays. A single rack comprises 8 CPUs and 2 BlueField DPUs. The Vera CPU features the Olympus core, delivering a 50% improvement in single-thread performance compared to traditional x86 CPUs. Each rack contains 256 CPUs, providing 400TB of memory and 300TB/s of memory bandwidth, utilizing liquid cooling and Ethernet connectivity. A single CPU rack can support over 22,500 concurrent reinforcement learning or Agentic sandbox environments, offering twice the efficiency and 50% faster performance compared to traditional rack-scale CPUs. It can test, execute, and validate results from the Vera Rubin NVL72 and LPX racks, thereby advancing Agent AI development. The report indicates that CPUs are crucial for the deployment and inference of AI Agents. The Vera CPU's strong single-thread performance can adequately support frequent tool invocations and other tasks in AI Agent scenarios. The launch of the Vera CPU rack is expected to initiate large-scale deployment of AI agents, helping AI progress from "providing" suggestions to the "execution" of tasks.

Space-1 Computing Module Unveiled; Rubin Ultra Adopts Orthogonal Backplane NVIDIA is collaborating with partners to develop the Space-1 Vera Rubin Module, an AI computing module optimized for space, which is anticipated to accelerate the development of future space data centers. Furthermore, NVIDIA announced the Rubin Ultra Kyber architecture, which uses an orthogonal backplane for interconnection between the compute and switch boards. The Kyber NVL144 supports scaling up to NVL1152 through optical interconnects.

Related investment targets include: PCB manufacturers such as Shennan Circuits and others; CPO-related companies like Accelink Technologies and others; liquid cooling solution providers such as AVC and others; and space computing-related firms like Fudan Microelectronics and others.

Risks include potential slower-than-expected AI development, intensified industry competition, and geopolitical risks.