Machine-generated log data is growing exponentially making it extremely hard for cybersecurity software to provide real-time defense for the infrastructure. The software needs to analyze the Terabytes of data every day generated by servers, applications, and firewalls. Due to Grovf massively parallel FPGA cores companies analyze and prevent the cyber threat 15x faster, saving critical time for organizations to detect penetration and counteract almost in real-time.
Grovf offers products that accelerate big-data analytics and enable organizations to search and analyze the most critical data at speeds approaching real-time.
The Grovf platform takes advantage of the versatile FPGA HWs to accelerate the processing of computationally intensive big-data. We do this by accelerating middleware, so applications running on top of middleware get an automatic boost without any changes on the user application.
GCache is an FPGA-based key-value database to efficiently store and retrieve cached data. Network stacks are implemented on FPGA to receive data from fast speed networks completely bypassing any type of operating systems and software layers. Key-value store algorithms are implemented completely on FPGA to handle Memcached compatible operations. Direct connection with DRAM from FPGA is used to stream data to memory for storage and retrieve the data on demand.
Regular expressions are specially encoded text strings used as patterns for matching sets of strings. GRegeX is an implementation of standard regular expression algorithm on FPGA chip achieving 12.8 GB/s throughput with a single IP core. Wide range of supported regular expression functions allows developers configure desired rules which can be handled in a chip without reducing the throughput. The target applications include: Smart firewalls, Security and Log Text analysis.