Keysight Technologies, a leader in test and performance measurement, has introduced Keysight Artificial Intelligence (KAI), a solution designed to detect performance inhibitors in large-scale GPU deployments. Instead of relying on actual hardware, KAI emulates workload profiles to accurately identify bottlenecks.

Figure 1. Boosting Data Center Efficiency with Keysight Tools.

According to Keysight, scaling AI data centers requires end-to-end validation across the entire infrastructure—including chips, cables, interconnects, switches, servers, and GPUs. KAI examines everything from the physical to the application layer, uncovering weak links that can degrade performance. It helps validate and fine-tune system-level operations to ensure scalability and maximize throughput. Figure 1 shows Boosting Data Center Efficiency with Keysight Tools.

AI service providers, semiconductor manufacturers, and network equipment vendors can leverage KAI to speed up design, development, deployment, and ongoing operations by detecting and resolving issues before reaching production.

The KAI framework includes the newly launched KAI Data Center Builder, which simulates large-scale AI workloads. It also features four integrated product suites that support data center design from early simulation to post-deployment testing and troubleshooting:

• KAI Compute – Enhances digital design for next-generation AI chip development
• KAI Interconnect – Validates both optical and electrical data transmission paths
• KAI Network – Measures and benchmarks AI network performance
• KAI Power – Improves energy efficiency and power management across all components of the data center

“Scaling AI data centers takes more than just validating individual components. True performance, interoperability, and efficiency are system-wide metrics that must be assessed under real-world network conditions,” said Ram Periakaruppan, vice president and general manager of Network Test and Security Solutions at Keysight. “Keysight’s AI solutions draw on our extensive expertise in traffic emulation, component and network compliance, and the latest industry standards to emulate all aspects of data center performance—compute, networking, interconnects, and power—ensuring AI infrastructure is ready to meet evolving demands.”

Simulating Real-World Workloads with KAI

Keysight’s KAI (Keysight Artificial Intelligence) platform plays a crucial role in improving deployment efficiency by simulating real-world AI workloads. Instead of using physical hardware for every test, KAI emulates workload profiles to detect performance bottlenecks early. This proactive approach helps identify issues before they impact production, saving time and resources during deployment.

System-Wide Validation Across the Stack

AI data center performance isn’t just about individual components—it’s about how the entire system works together. Keysight tools validate performance from the physical layer (like chips and cables) to the application layer (such as AI models and services). By analyzing every link in the chain—including servers, switches, and interconnects—Keysight ensures smooth interoperability and optimal system-level performance.

Accelerating Design and Development Cycles

With tools like KAI Compute, Keysight accelerates AI chip design and validation through pre-silicon simulation and post-silicon testing. This helps semiconductor manufacturers catch design flaws early, iterate faster, and reduce time to market. The result? A more efficient path from concept to deployment in AI-driven data centers.

Power and Network Optimization for Scalability

Scalability depends on two critical factors: efficient power use and high network throughput. KAI Power focuses on energy management across data center components, while KAI Network benchmarks performance and identifies networking bottlenecks. Together, they help AI providers scale infrastructure effectively while keeping operational costs in check.

From Deployment to Ongoing Operations

Keysight’s tools don’t stop at deployment. With comprehensive post-deployment testing and troubleshooting capabilities, KAI continues to deliver value throughout the data center lifecycle. It enables continuous validation, performance monitoring, and rapid issue resolution—ensuring long-term efficiency and reliability of AI infrastructure.

Source: NETWORK WORLD

Cite this article:

Priyadharshini S (2025), Keysight Tools Enhance Efficiency in Data Center Deployment, AnaTechMaz, pp.122