Uploaded August 2026 | Updated September 2026, 1 week ago
Physical network design—deciding how thousands of network devices and millions of fibers are distributed across data centers, racks, and failure domains—has traditionally been a manual, time-consuming process performed by design engineers.
Yet we are seeing exponentially increasing demand to fulfill the capacity required by AI workloads. At Meta, we developed Loom, a system to automate and optimize the end-to-end physical network design pipeline. Loom orchestrates two core components: a device placement component (Planogram) which places network devices across the physical floorplan subject to dimensional and failure-domain constraints; and a fiber design component, which generates end-to-end fiber connectivity satisfying the variety of connectivity patterns driven by physical constraints.
Together, these components accelerate end-to-end physical network design from months to hours, allowing us to produce more complex and efficient designs with fewer resources.
Learn more about the @Scale conference here: atscaleconference.com
Physical network design—deciding how thousands of network devices and millions of fibers are distributed across data centers, racks, and failure domains—has traditionally been a manual, time-consuming process performed by design engineers.
Yet we are seeing exponentially increasing demand to fulfill the capacity required by AI workloads. At Meta, we developed Loom, a system to automate and optimize the end-to-end physical network design pipeline. Loom orchestrates two core components: a device placement component (Planogram) which places network devices across the physical floorplan subject to dimensional and failure-domain constraints; and a fiber design component, which generates end-to-end fiber connectivity satisfying the variety of connectivity patterns driven by physical constraints.
Together, these components accelerate end-to-end physical network design from months to hours, allowing us to produce more complex and efficient designs with fewer resources.
Learn more about the @Scale conference here: atscaleconference.com
