10x
Faster Insights
Real Time Infrastructure
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Save on TCO
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Power Saving
Use cases
High Performance Computing
As more computer activities migrate to cloud platforms and software systems become more standardized, companies are seeking methods to include HPC into their data operations.
To execute HPC, data centers require computers and servers ready to handle large-scale data, as well as a nearly failsafe networking solution between them. The HPC cluster will be performing quadrillions of calculations per second, and the network infrastructure must be able to immediately sequence and analyze data
Storage Clustering and Disaggregation
The performance of local storage is combined with the flexibility of storage area networks in disaggregated storage. Modern storage clusters are moving forward to meet 100Gbps network infrastructure as the demand for data access performance and latency grows. High-performance links between storage nodes are a key component for building a disaggregated storage cluster solution. With this saying, RoCE V2 is a technology that enables data movement between servers providing both flexibility and performance at scale.
Memory Pooling
Memory pooling is a key component when building multi-master node computing servers to perform database operations. Often database systems have to make tradeoffs between data validity, availability, atomicity and read/write performance. This is due to the fact that generally database systems are designed with a single master node and there is no single memory pool that can enable multi-master node architecture.
Deep packet inspection (DPI) acceleration
Deep packet inspection (DPI) is an advanced method of examining and managing network traffic. It is a form of packet filtering that locates, identifies, classifies, routes, or blocks packets with specific data or code payloads that conventional packet filtering, which examines only packet headers, cannot detect.
DPI combines the functionality of an intrusion detection system (IDS) and an Intrusion prevention system (IPS) with a traditional stateful firewall. This combination makes it possible to detect certain attacks that neither the IDS/IPS nor the stateful firewall can catch on their own. Stateful firewalls, while able to see the beginning and end of a packet flow, cannot catch events on their own that would be out of bounds for a particular application
MongoDB Acceleration via Grovf MonetX
Databases provide a wealth of functionality to a wide range of applications. Yet, there are tasks for which they are less than optimal, for instance when processing becomes more complex or the data is less structured. As data is exploding exponentially only CPU based systems no longer provide real-time insights to businesses in a cost-effective way. At Grovf we designed a Monet – A FPGA based smart memory extension for near memory data processing. Monet implemented on top of Xilinx’s Alveo U50 acceleration card and once plugged into server’s PCIe bus acts as a standard RAM memory for the Linux operating system with in-memory compute API capability.
Security Log Analytics
Considering how fast new threats and attacks emerge, Big Data performance and new approaches to data analytics acceleration are becoming more vital.
Grovf offers hardware acceleration in the form of text processing FPGA cores and Open source software SDK, offering an effortless way to use powerful FPGA devices for vast amounts of security log analysis.
FPGA reconfigurable chip, powered with Grovf's Regex, Exact Search and Similarity Search functions, allows organizations to analyze hundreds of megabytes of data in real-time and detect security alerts maximizing their time-efficiency.
Financial Fraud/Risk Analytics
Through our financial data analytics acceleration, time resources maximization and cost-efficiency, Grovf helps financial sectors data engineers achieve incomparably better performance. As a result, the client companies make informed decisions, gain more predictable risk outcomes, save time, and establish a fraud-less trusted environment.
User Sentiment Analytics
The applications of sentiment analysis are broad and powerful, differing from voice of customer (VoC) to social media and brand monitoring, from customer service to market research. The growing complexity of such cross-sectional analysis and the unstructured format of generated customer data make this domain a subject of IT involvement. Grovf helps you leverage your data analytics capabilities and achieve real-time performance for customer-centric and insight-driven decision making.