Keysight Introduces Scale-Up Validation Solutions for AI Data Centers

Core Insights - Keysight Technologies has introduced a new portfolio of scale-up validation solutions aimed at helping AI data center operators tackle challenges related to bandwidth, latency, and interoperability as AI infrastructure scales [1] Group 1: Product Offerings - The new solutions support both emerging and established interconnect standards, including UAlink™200G, PCIe® 7.0, PCIe® 6.0, PCIe® 5.0, and CXL™ 3, facilitating faster deployment of high-performance AI infrastructure [1] - Keysight's Receiver Conformance Test Software for UALink 200G accelerates validation of UALink™ 200 Gb/s interfaces, integrating with the M8050A 120 Gbd High-Performance BERT and Infiniium UXR Real-Time Oscilloscope for comprehensive testing [1] - The PCIe 7.0 Transmitter Test solution enables compliance testing at speeds up to 128GT/s, addressing the growing demand for ultra-high bandwidth interconnects in AI and machine learning workloads [1] - Keysight's PCIe 6.0 Protocol Compliance Test Suite provides end-to-end validation at speeds up to 64 GT/s, streamlining compliance testing for next-generation designs [1] - The CXL 3 Protocol Exerciser and Analyzer Test Solution expands memory capacity and bandwidth, enabling efficient resource utilization across heterogeneous compute platforms [1] - The PCIe 5.0 Protocol Link and Transaction Compliance Solution, certified by PCI-SIG, accelerates standards-based validation for high-density compute environments [1] Group 2: Market Context - Rapid adoption of AI is driving unprecedented demand for high-density compute, real-time data movement, and low-latency memory access, making reliable validation of high-speed interconnects critical [1] - As hyperscalers and enterprises scale up AI infrastructure, the need for efficient and interoperable high-bandwidth, low-latency interconnects becomes increasingly important [1] - Keysight's solutions aim to help the industry validate performance, energy efficiency, and reliability across standards before deployment, addressing the challenges posed by the rapid growth of AI demand [1]