Touted as a likely replacement for Ethernet and Fibre Channel when it was introduced more than two decades ago, InfiniBand was all but abandoned by most leading technology companies within just a few years. However, the high-speed interconnect technology is back in the spotlight as a key enabler of artificial intelligence (AI) networks.
Offering speeds up to 600Gbps, InfiniBand delivers the raw bandwidth necessary for the massive data transfers required by AI workloads. It has become the most widely adopted connectivity option for all AI applications. According to a recent analysis, the InfiniBand market is expected to grow at a whopping 40 percent CAGR through 2029, when it will reach a total value of nearly $100 billion.
Much of that growth stems from AI’s move into the mainstream. Organizations in every industry are exploring new ways to use AI for analytics, automation, code generation, predictive maintenance and many other exciting use cases. As they grow their AI capabilities, however, most organizations quickly discover that AI’s enormous data and networking requirements push the limits of traditional network interconnect solutions.
Enter InfiniBand
Introduced in 2000, InfiniBand’s switched fabric input/output (I/O) technology was designed specifically to improve throughput between servers, storage and other network devices. Early backers included Intel, Microsoft, Cisco, HP and IBM. However, industry support gradually dwindled due to cost and complexity issues — as well as continued improvements with the more familiar Ethernet standard.
Still, InfiniBand has remained a popular choice for niche uses such as high-performance computing (HPC) applications. It provides the interconnections for 63 of the world’s 100 fastest supercomputers, with 200 InfiniBand-connected systems appearing on the June 2023 TOP500 list of the world’s most powerful supercomputers.
The Right Choice for AI
As it turns out, the features that support HPC are also exactly right for AI networks. The technology’s bandwidth advantages are particularly important for machine-learning applications that require terabytes of data to train deep-learning algorithms.
InfiniBand is also extremely fast, with port-to-port latencies of about 100 nanoseconds (ns), or about 100 billionths of a second. Low latency ensures minimal delay in communication between compute nodes, storage devices, graphics processing units (GPUs), specialized AI accelerators and other components. This is critical for delivering the real-time responses needed for autonomous vehicles, healthcare diagnostics, financial trading and other AI applications.
Scalability is another important InfiniBand characteristic. Its modular and flexible architecture can scale up to thousands of nodes while maintaining low latency and high bandwidth. This scalability is essential for AI workloads that often require distributed computing setups with multiple GPUs and CPUs working together to process data-intensive tasks.
InfiniBand also supports Remote Direct Memory Access (RDMA), which allows for efficient data transfers between nodes without involving the CPU. This offloads data movement tasks from the CPU to InfiniBand hardware, allowing CPU time to be devoted to application processing and improving overall system performance.
Other Options
InfiniBand and Ethernet aren’t the only interconnect options for AI networks. Specialized optical interconnects also feature high bandwidth and low latency, but they often require specialized hardware. Other types of interconnects create dedicated connections between GPUs, allowing them to share data and work collaboratively on complex AI tasks. However, these tend to be proprietary solutions that only work with specific types of hardware.
The choice of interconnect depends on various factors, including specific workloads, budget and available hardware. In some cases, a combination of interconnect options may be appropriate. Infrastructure upgrades may also be required to support the increased data traffic and high bandwidth demands of AI workloads. That’s why all organizations should develop a comprehensive network strategy to address their AI objectives and other emerging trends and technologies. Contact us to learn more about InfiniBand and other interconnect options for AI networks.
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