Solutions for Diverse Business Scenarios
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High-Speed Switches
As AI adoption and AI data center construction accelerate rapidly, deploying large-scale compute networks introduces challenges such as legacy bandwidth bottlenecks, high-concurrency data congestion, compute silos, and inefficient data transmission. These pain points present severe obstacles to the rapid evolution of AI large model training and the intelligent computing industry.
To address current AI networking demands, Blue Spider Technology leverages next-generation 400G/800G/1.6T high-speed switching silicon to develop proprietary high-speed switches. Engineered for AI data centers and cloud service providers across all scales, these platforms deliver ultra-high bandwidth, microsecond-level low latency, and zero-loss data switching—enabling seamless interconnectivity and efficient collaboration across compute resources. This accelerates massive data throughput and distributed training for AI enterprises and research institutions, driving a full-scale upgrade of modern AI computing infrastructure.
• Blue Spider Technology Solution Objectives:
1. Elevate overall AI data center network standards across high throughput, low latency, intelligent management, and automated O&M.
2. Eliminate network congestion and packet loss bottlenecks to ensure maximum stability and efficiency for AI large model training and inference workloads.
3. Gain direct access to real-time network traffic and compute scheduling data to obtain holistic visibility into operational dynamics and make data-driven architecture optimizations.
4. Integrate compute and network resources into a high-performance AI interconnect foundation, establishing efficient data-sharing mechanisms for unified global management and collaborative computing.
Network Operating System (NOS)
Traditional closed, black-box network operating systems can no longer meet the requirements of modern AI data centers and large models for high concurrency, low latency, and flexible scheduling. In cutting-edge technology, Open Networking has emerged as a key architectural paradigm. Its defining advantage is freedom from single-vendor hardware lock-in, enabling customized Network Operating Systems (NOS) to run on standardized white-box switches according to user-defined designs—delivering high efficiency, agility, and cost-effectiveness. In recent years, intelligent NOS and Open Networking have advanced rapidly, becoming a dominant trend in AI networking.
Addressing current AI data center networking demands, Blue Spider Technology leverages next-generation AI and automation technologies to deeply customize and intelligently manage the switch Network Operating System (NOS). For AI computing clusters, NOS monitoring and control scope covers port traffic, queue congestion, optical module status, routing forwarding efficiency, RoCEv2 lossless network parameters, ECN marking thresholds, PFC deadlock detection, and microburst telemetry data collection. External integration encompasses SDN controller synchronization, AI compute scheduling platform integration, and automated O&M script execution. Big data analytics powered by Intelligent NOS delivers significant cost savings to network administrators, improves network utilization, reduces operational workload, and provides seamless support for AI large model training.
• Compared to traditional proprietary network systems, Blue Spider Technology's Intelligent NOS Solution offers the following key advantages:
1. Simplified Deployment & Maintenance: Supports automated configuration and containerized deployment. Hardware-software disaggregation keeps costs fully controllable.
2. Data-Driven Decision Making: Gains direct access to real-time telemetry data to enable intelligent congestion control, maximize network throughput, and significantly reduce engineering overhead.
3. Centralized NOS Big Data Hub: Integrates network resources into a NOS big data engine, creating information-sharing and automated O&M mechanisms for global network visibility and collaborative scheduling.
AI Chip Interconnect
• The traditional general-purpose computing market is undergoing a fundamental transformation, as AI chips and compute cards transcend standard data processing and basic logic operations to become the key drivers for AI large model training, complex intelligent inference, and computing innovation.
• Blue Spider Technology's innovative AI Chip & Compute Card Interconnect technology empowers robust AI compute infrastructure, effectively supporting large model distributed training, dynamic compute scheduling, GPU memory bandwidth optimization, heterogeneous compute acceleration, model inference acceleration, high-concurrency data throughput, low-power intelligent control, real-time compute node monitoring, energy efficiency reporting, chip core temperature monitoring, compute cluster anomaly alerts, and centralized cluster-wide compute management.
Lossless Networks & AIOps
• Traditional AI Computing Network Challenges & Pain Points:
a. Extremely complex AI data center network topologies make traffic scheduling and congestion control highly challenging in hyper-scale clusters.
b. Massive microburst traffic generated by AI large model training overwhelms traditional network architectures, leading to severe congestion and packet loss.
c. Network performance bottlenecks and latent faults are highly elusive, exhibiting significant spatial and temporal randomness that makes them hard to predict.
d. Lack of global network visibility forces reliance on manual packet captures for troubleshooting, resulting in low O&M efficiency and high operational costs.
e. Traditional network equipment lacks fine-grained telemetry capabilities, failing to guarantee the absolute zero-loss transmission environment required for AI training.
f. Dependence on offline log analysis makes it difficult to reliably capture network deadlocks, packet drops, or performance degradation events in real time.
• Blue Spider Technology's Lossless Networks & AIOps Solution Features:
1. Intelligent Lossless Network Architecture: Leverages advanced RoCEv2 protocols and dynamic congestion control algorithms to achieve zero packet loss for AI compute workloads.
2. In-band Network Telemetry (INT): Provides microsecond-level traffic visibility, queue depth monitoring, and precise link state awareness.
3. AIOps Smart Management: Combines AI algorithms for traffic prediction and fault self-healing, delivering 24/7 automated network health assurance.
4. Automated Orchestration & Control: Supports one-click policy pushing and centralized management for rapid deployment and simplified maintenance.
5. Real-Time Network Early Warning: Enables full-volume online data collection, big data root cause analysis (RCA), and instant anomaly alerts to ensure continuous AI business operations.
AI Infrastructure Integration
• Innovation drives the core of AI and high-performance computing. Key development trends include scalable compute power, green and low-carbon operation, architecture optimization, and elastic resource scheduling. Traditionally, enterprises relied on fragmented IT hardware and legacy data centers. While general-purpose cloud computing has grown in recent years, traditional IT architectures fall significantly short in compute density, interconnect bandwidth, and Power Usage Effectiveness (PUE) when faced with explosive demand for AI large model training and inference.
• Blue Spider Technology's AI Infrastructure Integration solution delivers end-to-end, seamless deployment—from underlying hardware (compute servers, high-speed networking, storage) to upper-layer software (Intelligent NOS, compute scheduling platform)—enabling real-time resource scheduling, efficient collaboration, centralized analytics, and intelligent management.
• Comprehensive upgrade path from traditional IT architecture to modern AI data centers, enhancing overall compute efficiency and automated operations (e.g., upgrading legacy server rooms to high-density AI clusters, transitioning network architectures to 400G/800G lossless interconnects, and achieving centralized monitoring with AIOps smart management across the full infrastructure stack).
matt@blue-spider.cn
18257131029
Room 727, Building 3, Dongfang Minglou, Qiantang District, Hangzhou, Zhejiang Province