Rethinking AI-Scale Data Center Validation


The rapid growth of AI workloads is transforming AI data center networking, exposing critical limitations in traditional Ethernet validation and network testing methodologies. As data centers adopt 1.6T Ethernet, 224G SerDes and optical lanes, and tightly coupled GPU fabrics, networks must deliver ultra-high bandwidth, low latency, and predictable performance under dynamic east-west traffic con... » read more

Alleviating the DRAM Capacity Bottleneck in Consumer Devices with NVMs


A new technical paper titled "Extending Memory Capacity in Modern Consumer Systems With Emerging Non-Volatile Memory: Experimental Analysis and Characterization Using the Intel Optane SSD" was published by researchers at ETH Zurich, University of Illinois Urbana-Champaign, Google, and Rivos. Abstract Excerpt "DRAM scalability is becoming a limiting factor to the available memory capacity in... » read more