How to Achieve Low-Latency Networks for High-Performance Computing?
Updated at Mar 14th 20241 min read
High-performance computing (HPC) refers to the use of powerful computing systems to process and analyze large volumes of data at exceptional speeds. In the realm of high-performance computing (HPC), low latency network is a cornerstone of efficient and effective system performance. With applications ranging from AI training to scientific simulations, achieving minimal delays in data transmission is vital. This article explores strategies and technologies for building low-latency networks tailored for HPC environments.
The impact of Latency Networks on HPC
High-performance network applications, such as simulations, data analytics, and scientific research, depend on efficient data transfer between nodes. Latency in these systems can significantly impact performance and efficiency, leading to:
Decreased application performance: Higher latency slows down application execution, extending simulation times and reducing overall productivity.
Higher energy consumption: Increased latency forces nodes to wait longer for data, leading to greater power usage and heat generation.
Rising operational costs: Prolonged latency can necessitate re-running or re-scheduling applications, resulting in wasted resources and elevated maintenance expenses.
The Importance of Low-Latency Networks on HPC
Low latency in HPC networks directly impacts computational efficiency, scalability, and overall system throughput. As HPC environments typically involve thousands of compute nodes working in unison to solve complex problems, communication delays between these nodes can have a compounding effect, severely hindering performance. Here are some key reasons why low latency is crucial:
Efficient Task Synchronization
HPC workloads often rely on distributed computing, where tasks are split across multiple nodes and must frequently exchange intermediate results. Low latency ensures rapid synchronization between nodes, reducing idle times and enhancing overall workflow efficiency. For instance, in AI training, where gradient exchanges occur across GPUs, delays can exponentially increase training times.
Improved Scalability
As the scale of HPC systems grows, maintaining low latency becomes increasingly challenging but vital. High latency can limit the number of nodes that can effectively work together, constraining the scalability of applications. Low-latency networks ensure that even large-scale HPC clusters can operate efficiently without performance degradation.
Enhanced Application Performance
Many scientific simulations, financial modeling, and real-time analytics require near-instantaneous data exchange to maintain accuracy and relevance. For example, real-time weather forecasting models need low-latency networks to process vast datasets quickly and provide timely predictions. Any delay in data transmission can compromise the quality of results.
How to Achieve Low-Latency Networks?
Achieving low-latency networks in high-performance computing involves employing advanced technologies and optimizing various network components. Here are some key factors contributing to the attainment of low-latency networks:
High-Speed Ethernet
Ethernet, with its inherent advantages of simplicity, user-friendliness, cost-effectiveness, and scalability, finds widespread application across diverse domains. Since its inception, Ethernet technology and protocols have undergone continuous evolution. Starting from the initial 10 Mbps rate, Ethernet bandwidth has progressively escalated to 10G, 25G, 40G, and 100G, with a further surge to 400G and even 800G, adeptly addressing the bandwidth-intensive demands of expansive data centers and cloud computing.
FS offers a comprehensive suite of high-speed Ethernet solutions tailored to meet the demands of modern networking and HPC environments. These include ethernet transceivers、switches、networking adapters. Furthermore, high-speed Ethernet can reduce latency through traffic management and optimization of packet processing and routing. High-speed Ethernet technology meets the stringent network performance requirements of HPC systems, enabling them to keep pace with the ever-growing computational demands of modern applications.

InfiniBand
InfiniBand provides high data transfer rates and low communication overhead, making it well-suited for parallel processing and large-scale computations. finiBand technology achieves low-latency networking primarily through the following key features:
Point-to-point Direct-connection Architecture: Each device, such as servers, storage devices, or other computing resources, directly connects to the network via an InfiniBand adapter, forming a point-to-point communication structure.
Remote Direct Memory Access (RDMA): RDMA enables applications to access and exchange data directly in memory without involving the operating system. Through RDMA, the InfiniBand network eliminates intermediary steps present in traditional network structures, resulting in a substantial reduction in data transfer latency.
FS offers a series of Infiniband devices, such as InfiniBand modules and InfiniBand switches, which have evolved to high-speed rates of 400G and 800G. The combination of high bandwidth and low latency makes InfiniBand a crucial component in achieving optimal network performance for HPC applications.

Optimized Network Topology
The topology of the network, or how nodes are interconnected, plays a vital role in minimizing latency. Network topologies, such as fat-tree、Dragonfly、torus、 hypercube, are commonly used in HPC environments to provide efficient communication paths between nodes. Optimized network topology ensures that data can traverse the network with minimal delays, enhancing the overall performance of the HPC system.

For smaller scales, it is recommended to use a 2-layer fat-tree topology. For larger scales, a 3-layer fat-tree network topology can be employed. Beyond a certain scale, adopting a Dragonfly+ topology can save some costs.

Network Protocols
To further reduce network latency, specialized network protocols and algorithms, such as MPI (Message Passing Interface) and RDMA (Remote Direct Memory Access) mentioned above, can optimize data transfer and communication efficiency. MPI serves as a standard interface for message passing in parallel computing, enhancing collaborative work efficiency among nodes through effective message exchange patterns. RDMA is often implemented in conjunction with high-speed interconnect technologies,further enhancing the low-latency capabilities of HPC networks.
For more information: RDMA NIC: Features and How to Choose?
Conclusion
In conclusion, the importance of low-latency networks in high-performance computing cannot be overstated. As high-performance computing applications evolve, demanding more computational power and efficiency, the interconnection networks must keep pace to ensure optimal performance. Technologies like high-speed Ethernet, InfiniBand, optimized network topology, and RDMA are pivotal in achieving low-latency networks for HPC systems. By focusing on these advancements, researchers and scientists can harness the full potential of high-performance computing, enabling groundbreaking discoveries and advancements across various domains.