Testing for AI Data Center Networking

The surge of AI and cloud computing has catapulted Ethernet into the forefront of networking innovation, driving demand for faster, more efficient high-speed Ethernet solutions. As organizations scale their infrastructures to support these emerging technologies, the need for robust, future-proof Ethernet solutions is more critical than ever. This __Spirent Impact Report__ provides valuable insights into the rapidly evolving high-speed Ethernet (HSE) market, covering the latest trends, demand drivers, and technological advancements shaping the data center, telecom, and enterprise networking landscapes. The report highlights the transformative role that AI is playing in Ethernet's evolution and how hyperscalers, service providers, and enterprises are adapting to meet the challenge.

Artificial intelligence and machine learning has been moving into many aspects of network testing, from the field to service assurance, to fuel automation and increased efficiency. So where exactly is AI/ML being applied in network testing and assurance today, how is it proving its value, and what does this mean for the field workforce and for carrier operations? In this *RCR Wireless News* webinar, Spirent and industry experts will share an update on the progress towards more intelligent and automated, AI-driven networks in the future to provide viewers with insights into how AI is reshaping the network testing and assurance landscape.

Spirent AI Data Center Test Solution Scoops Grand Prize at Interop Tokyo 2024

The AI data center journey is just starting and expected to evolve dramatically with the technology. There is an urgent need to evaluate new data center architectures to ensure they are future-proof and optimized for maximum efficiency, to ensure a return on AI network investments. A new Spirent infographic compiles the latest AI data center market trends, architecture details, dynamic AI fabric requirements and new testing strategies and solutions required for ensuring AI Ethernet fabric performance and resiliency.

Innovative testing approaches in preparation for the AI revolution

The scale of artificial intelligence (AI) applications is skyrocketing with the number of model parameters growing at a blistering 1000x pace every 3 years. The growing complexity and size of AI applications is driving a need for increasing numbers of AI accelerators, which in turn dictate the type and scale of the networking fabric required to interconnect the accelerators with each other and compute and memory resources. As AI applications move from small apps with hundreds of AI accelerators to large apps that require tens of thousands of AI accelerators, the networking architectures grow more complex. As we grow to over ten thousand accelerators, a data center scale architecture is required with a routable fabric and AI spine.

Spirent Moves Testing into the AI Fast Lane with Industry’s First AI Traffic Emulation Platform for Ethernet

In today’s rapidly evolving technological landscape, Enterprise and data center networking has undergone significant advancements. With the widespread adoption of AI/ML, edge computing, and high-performance computing (HPC) systems, modern data centers demand a network that delivers exceptional performance and minimal latency. This network must also seamlessly adapt to accommodate the tremendous surge in data transfer demands driven by data-intensive and compute-intensive applications.