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Pensando, Xilinx Debut Smart NICs

June 16, 2020

Author: Bob Wheeler

For merchant vendors, the smart-NIC market has fallen short of the hype. Most vendors hoped that adoption of captive designs at Amazon and Microsoft would create pull for smart NICs at other leading cloud-service providers (CSPs). Of the seven largest CSPs, however, we believe only Baidu and Tencent purchased merchant smart NICs last year, whereas the remainder used a mix of standard NICs and captive smart NICs. Given limited opportunity at the highest-volume customers, merchant vendors are looking to other segments for growth: second-tier CSPs, enterprise data centers (private clouds), and telecommunications-service providers.

To address this broader market, two new entrants are developing more software than incumbent smart-NIC vendors, which typically deliver little more than drivers and a software-development kit. If their solutions provide higher-value services, they can charge higher prices that more than offset the lower volumes available. This reasoning explains how startup Pensando raised a whopping $278 million and why Xilinx paid $400 million for Solarflare.

Shipping since 3Q19, Pensando’s initial offering includes a choice of dual-port 25G Ethernet or 100G Ethernet adapters, which the company calls distributed services cards (DSCs). To centrally manage up to 1,000 DSCs, policy- and services-manager (PSM) software runs on a separate high-availability server cluster. In addition to network and storage virtualization, the startup delivers networking, security, and telemetry services that traditionally required specialized appliances.

The first smart NIC from Xilinx, scheduled for general availability in 3Q20, is the Alveo U25, a dual-port 25G Ethernet adapter combining an FPGA with a Solarflare ASIC. Initial services will include Open vSwitch (OVS), IPSec, TLS, and firewall offloads, and the card works with Solarflare’s low-latency TCP/IP stack. The U25 has dual PCIe interfaces, enabling the host to directly access the FPGA to accelerate compute workloads such as machine learning and video transcoding.

Subscribers can view the full article in the Microprocessor Report.

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