At this week's OFC event in San Diego, Ranovus will demonstrated its Co-Packaged Optics (CPO) 2.0 integration featuing a Xilinx Versal ACAP its own Ranovus Odin 800Gbps optical engine. The integration eliminates the need for the retimer, resulting in 75% smaller footprint and 40% cost and power consumption savings in the Optical Interconnect.
RANOVUS’ Odin is a low latency, high density, and protocol agnostic optical engine that delivers massive optical interconnect bandwidth, scaling from 800Gbps to 3.2Tbps in the same footprint. It leverages Ranovus’ 100Gbps per lambda monolithic Electro-Photonic Integrated Circuit (EPIC) IP, laser platform, and advanced packaging technologies.
“We announced our Odin Analog Drive CPO 2.0 platform at OFC 2021 for Ethernet switch and module applications and are thrilled to showcase our platform with a Versal ACAP for ML/AI workloads” said Hamid Arabzadeh, Chairman and Chief Executive Officer of RANOVUS. “We have been at the forefront of the CPO movement since 2018 and are delighted to share our multi disciplinary IP cores with our customers who want to accelerate the adoption of Analog Drive CPO in data centers.”
CPO is an innovative approach that provides Nx100Gbps PAM4 Optical I/O channels for Ethernet switch and ML/AI silicon in a single packaged assembly, which significantly reduces the cost and power consumption of the complete system.
“We’re proud of our collaboration with Ranovus that helped achieve record performance levels while at the same time reducing power and overall footprint of the complete solution,” said Dan Mansur, vice president, Adaptable and Embedded Computing Group, AMD (formerly Xilinx). “This CPO demonstration highlights the versatility of the Versal GTM SERDES to operate over anything from long-reach copper to directly driving the Ranovus Analog-Drive CPO 2.0 optical engine. Co-packaging Ranovus Odin™ with Xilinx Versal is a significant advancement which enables data center customers to build highly efficient and cost-effective systems for next-generation workloads.”