Edgecore Networks, the leader in open networking solutions, today announced an 800G-optimized switch, the DCS560, which can provide an Ethernet-based fabric for AI/ML workloads. The DCS560 is a 2RU 51.2 Tbps system with 64x800G ports that is available in two variants, providing a choice of either OSFP800 or QSFP-DD800 interfaces.
Generative AI has drastically accelerated the size and network bandwidth required in AI/ML clusters with the number of compute nodes and accelerators growing significantly. AI networks require high-capacity systems in a flat architecture that can handle large amounts of data with low latency and high throughput. To meet the demands of AI/ML workloads, Ethernet-based fabrics are now being adopted to reduce job completion time.
Edgecore’s 51.2 Tbps Broadcom StrataXGS® Tomahawk® 5 series-based system with 64x800G ports provides a high-radix, deployment-friendly Ethernet-fabric. The 2RU system design is robust and packed in a compact form factor with power and fan tray redundancy to achieve five-nines high availability and a wide environmental operating range for data center cloud applications. With a load-balanced port mapping design, the system offers known good system quality and reliability while preserving the port assignment flexibility for customers. The platform comes in two variants, OSFP800 or QSFP-DD800 interface options, for flexible deployment supporting passive copper DAC on all ports and long-distance ZR+ optics. Each system provides high-radix connectivity to accelerators and compute nodes in a flat architecture that reduces latency and required power, which enables networks to be scaled-out sustainably.
At Starview Technologies, we take pride in our role as the distributor of Edgecore Networks, a leader in cutting-edge networking solutions. Our commitment to pushing the boundaries of technology aligns perfectly with Edgecore’s dedication to delivering high-performance products. We specialize in building high-speed communications infrastructure and private clouds, aiming to power the most demanding workloads while breaking down barriers in terms of price and performance.