A top-tier financial securities firm based in the United States, which operates a global trading platform and manages a massive scale of assets management, is committed to leveraging cutting-edge technology to maintain market integrity and enhance risk control efficiency. The company plans to deploy 128 NVIDIA B200 GPUs to build an ultra-high-speed interconnect network, creating a unified AI computing platform. This platform will train its proprietary financial industry-specific language model (Fin-LLM) to automatically detect anomalous trading patterns and potential market manipulation.

The client expects AICPLIGHT to provide a complete solution design and end-to-end delivery, while taking the lead in project execution to significantly minimize internal team involvement and overhead.

The client requires the solution to ensure maximum performance while simultaneously enabling rapid deployment to strictly meet critical project timelines and cost budget constraints.

Prior to final delivery, the client demands rigorous testing and validation of the new supplier's products to conclusively confirm critical parameters, including overall system performance, component compatibility, and long-term operational stability.

The InfiniBand NDR network architecture, powered by the NVIDIA Quantum™-2 platform, delivers high bandwidth, low latency, and lossless transmission for 128 B200 GPUs. AICPLIGHT's technical team designs end-to-end topology tailored to the client's data center environment and rack layout, ensuring optimal GPU cluster training efficiency.

The storage side adopts NVIDIA Quantum's InfiniBand HDR solution, with compatibility analysis for the client's existing storage architecture. Read/write traffic distribution strategies are designed to maintain sustained high throughput for large-scale training data access and scheduling.

Both computing and storage networks are managed uniformly via NVIDIA UFM. AICPLIGHT handles UFM deployment, tuning, and policy planning, enabling topology visualization, link status monitoring, performance analysis, and automated fault diagnosis. This empowers clients to establish a controllable, maintainable network management system post-platform deployment.

AICPLIGHT's self-developed switches build the client's management network. Paired with proprietary optical modules, these switches offer long-term stability and meet diverse bandwidth needs across management domains.

Utilizes AICPLIGHT's self-developed 800G OSFP NDR optical modules and 400G OSFP NDR optical modules. Products undergo multiple rounds of compatibility testing on NVIDIA hardware platforms, achieving a pre-FEC error rate of 1E-10 and post-FEC error-free transmission, ensuring stable and reliable GPU cluster communication.

Utilizes AICPLIGHT's proprietary 200G QSFP56 AOC cables with integrated DSP chips. This effectively eliminates link flap instability issues encountered with CDR-based AOC solutions on NVIDIA Quantum platforms, enhancing overall interconnect reliability.

AICPLIGHT's technical team customizes primary and backup solutions based on the client's existing network conditions, offering diversified options in cost, delivery time, performance, and space utilization, enabling optimal decision-making while fully meeting project timelines and budgets.

Throughout the design process, AICPLIGHT provides professional technical support, rapidly adapts to requirement changes, delivers detailed design documentation, and conducts multiple rounds of meetings for solution analysis and presentation—ensuring clear client understanding of the solution's value and accelerating project execution.

Through this project, AICPLIGHT leveraged its leading high-speed interconnect technology, proprietary optical modules and network equipment, and deep architectural expertise to build a high-performance, low-latency, ultra-stable AI computing platform for the client.

AICPLIGHT not only met the client's stringent requirements in architecture design, delivery cycle, and performance stability, but also significantly reduced the client's internal resource investment through end-to-end project management. This allowed the client to focus on core algorithm development and financial model optimization.

AICPLIGHT delivered more than just a hardware solution—it provided a mass-producible, evolvable, and continuously optimizable AI infrastructure system. This maximized the computational value of the NVIDIA B200 GPU cluster, accelerating the innovative implementation of Fin-LLM in financial risk management.