Learn

In the digital age, the need for a quicker, more efficient, and scalable network has never been more vital. Traditional TCP/IP Ethernet connections, which are CPU intensive and involve additional data processing and copying, are no longer able to fulfill modern network traffic. In this context, the world’s most powerful supercomputers and data centers need transformative networking technology — RDMA over Converged Ethernet (RoCE).

Network complexity is rising with the diversification of devices, services, and connectivity technologies (mainly Ethernet, Wi-Fi, PLC, and MoCA), additionally, with the various application types generated day-after-day. When a service degrades in this setting, neither the end-user nor the ISP support desk can immediately resolve the problem. Thus, effective technologies for traffic monitoring that enable the observation and identification of network flows are critical to making diagnostic improvements and network performance optimization.

Combining network analyzer with firewall and DPI features, GROVF offers WireHex — Deep Packet Inspection & Analysis Tool that achieves exceptional efficiency for the analysis of 100 Gbps network traffic with a single server. As for the accuracy of data capture and the depth of analytics, WireHex allows 100 Gbps real-time bandwidth with 99 percent data retrieval precision.

DPI hardly keeps up with a high-speed network when it comes to traffic processing. This stems from the fact that DPI servers need ASIC-based decoding and regular expression engines to support 100Gbps+ rates as modern CPUs are not able to handle this in-line. Organizations wishing to leverage the benefits of DPI, therefore, require extra solutions to improve its functionality and maximize data computing performance.

The emerging turnovers in the spheres of IoT and Big Data reshape the future of the database industry. With a view to efficiently store and retrieve cached data, Grovf offers an FPGA-based key-value store — Grovf GCache. The main goals of our design are to drastically boost database performance, minimize latency and power consumption.

With a growing speed of networks and an increasing number of Regular Expressions (RE), existing DPIs require more thorough solutions, namely hardware acceleration to process the traffic at the line speed. FPGAs can be quite promising devices in the sphere of DPIs and we use them at Grovf to provide direct interaction with the network traffic in chip and process it without the need of transferring the data to the software layer.

Fast analysis of unstructured textual data, such as system logs, network traffic, social media posts, emails, or news articles, is growing ever more important in technical and business data analytics applications. Nearly 85% of business data is in the form of unstructured textual logs. Rapidly extracting information from these text sources is critical for business decision making.

Nowadays computing systems used in data-centers face huge challenges which are exposed here. The heterogeneous computing units consisting of CPU and FPGA pairs may just be that winning platform, especially in database acceleration. In data centers, IP developed by Grovf scales computing units vertically (adding more computing power to an existing machine) while preserving their horizontal scaling property (adding more machines into your pool of resources).