Limitations of Current Networking Technologies
As AI and high-performance computing (HPC) workloads continue to scale, the networking infrastructure supporting them has become a bottleneck, hampering progress toward true AI advancements such as Artificial General Intelligence (AGI). Today’s most common networking solutions—TCP/IP over Ethernet, RDMA over InfiniBand (IB), and Nvidia’s NVLink—all present significant limitations when it comes to meeting the performance needs of modern AI and HPC environments.
- TCP/IP over Ethernet, while the most widely used protocol, was not designed for the low-latency, high-throughput demands of AI workloads. Its reliance on complex networking layers introduces delays and inefficiencies, which severely limits performance in large-scale distributed AI models.
- RDMA over InfiniBand, though it offers improvements in latency and bandwidth compared to TCP/IP, suffers from scalability issues. In large data center environments, managing and maintaining InfiniBand becomes complex and costly. Its limited compatibility with mainstream hardware platforms further constrains its utility, especially as AI systems demand more diverse and scalable infrastructure.
- Nvidia’s NVLink, on the other hand, provides a specialized solution for intra-node communication in GPU-accelerated systems. However, its load/store semantics are inherently blocking, making AI model programming more complex. This results in suboptimal resource utilization, especially in environments where latency-sensitive and large-scale AI applications require both blocking and non-blocking operations.
These limitations collectively hinder the development of AI systems that require high levels of parallelism, data sharing, and scalability, delaying the journey toward AGI and other advanced computing goals.
Journey to AGI on Future Networking
As the demand for more powerful and scalable AI systems grows, the need for an efficient, flexible, and cost-effective networking solution becomes critical. At NUPA LAB, our vision is to transform AI and high-performance computing (HPC) infrastructures by delivering scalable, low-latency solutions that drive us toward the realization of Artificial General Intelligence (AGI). We believe the future of AGI depends on revolutionary networking protocols that can meet the massive data and performance demands of AI systems.
Our innovative solution, RDMA over CXL, is designed to address these challenges directly. Unlike traditional, costly networking technologies, RDMA over CXL leverages standard hardware, ensuring that businesses are not locked into expensive, proprietary systems like InfiniBand. By offering both blocking and non-blocking capabilities, we tailor our protocol to maximize the efficiency of AI workloads, enhancing system performance and scalability.
This dual approach enables seamless data flow between CPUs, GPUs, and accelerators, allowing AI models to operate at peak performance without bottlenecks or interruptions. Importantly, our solution also provides a significant cost advantage, making it far more affordable to scale AI infrastructures without sacrificing speed or flexibility.
At NUPA LAB, our vision is to lead the networking revolution necessary for AGI. Our RDMA over CXL protocol is central to this future, providing the robust, scalable, and high-performance networks that will enable intelligent systems to evolve and thrive. Together, we are building the infrastructure that will drive the intelligent systems of tomorrow, and in doing so, we’re accelerating the journey to AGI.
Explore Our Services
GPU Optimization
At NUPA LAB, we fine-tune GPU boards to maximize performance for AI and HPC workloads. By customizing memory, clock speeds, and power settings, we ensure GPUs are fully optimized for tasks like AI model training and real-time processing, giving clients a competitive edge.
RDMA Networking
Our RDMA over CXL protocol enables seamless, scalable connections between GPUs, CPUs, and accelerators. This ensures ultra-low latency and high throughput, allowing large-scale GPU clusters to handle growing AI workloads without performance bottlenecks.
Customized Design
We design custom PCB boards and systems to meet each client’s unique needs. From high-performance circuit boards to entire systems, we deliver tailored solutions that are efficient, reliable, and optimized for specific applications.
Step into a New Era
At NUPA LAB, we believe we are on the brink of a transformative shift in AI and high-performance computing (HPC). The future of intelligent systems, Artificial General Intelligence (AGI), and large-scale AI applications depends on innovative, scalable, and high-performance networking solutions. Our work in developing RDMA over CXL is not just about enhancing today’s systems—it’s about building the foundation for tomorrow’s AI-driven world.
For our customers, we offer a future where performance, scalability, and cost-efficiency go hand-in-hand. By eliminating bottlenecks, optimizing GPU performance, and providing custom-designed systems, we enable you to harness the full potential of AI for your applications—whether it’s research, industrial operations, or real-time AI solutions. Together, we can push the limits of what’s possible.
For our investors, this is an opportunity to be part of a groundbreaking venture poised to lead the next evolution in AI networking. The demand for advanced computing infrastructure is skyrocketing, and NUPA LAB is at the forefront, providing innovative solutions that will drive the future of AI and HPC. Your support will not only fuel the development of cutting-edge technologies but also help shape the technological landscape for the next decade and beyond.
Step into a new era of AI networking with NUPA LAB, where we build the infrastructure for the intelligent systems that will define our future.
