GCache
Currently, there are more devices connected to the Internet than there are people in the world. The Internet of Things (IoT) evolves exponentially and as a result, increases the physical representations of data accessible via Internet systems.
In view of the limitations of application memory size and their random-access nature, processors considerably lack energy-efficiency. Therefore, arises the need for dedicated hardware for IoT-generated data storage, effectively replacing software to accelerate the overall system.
Grovf offers GCache - an FPGA-based key-value store designed to efficiently store and retrieve cached data.
- Full line-rate processing up to 10Gbps in network applications
- Increased efficiency of hash table memory usage
- Reduced number of PCIs and eliminated processing overhead
- 10X performance boost compared to Redis (100B packet size)
- 5-20X lower latency in comparison with Redis
GRegex
Overview
Fast analysis of semi-structured or unstructured data is crucial for business decision making.
The amount of information, having no standard format (images, emails, text, XML, videos, etc.) continues to grow due to the high reliance on digital content in computer systems and makes searching/analysis more complex.
According to IDC predictions, 85% of the generated data will be unstructured by 2025 and much of this will be in a textual form. As the largest data source, unstructured data becomes a large ground for analytics and deploying AI applications in the company.
To do analytical processing against unstructured textual data, companies usually confront several obstacles and need to use specific approaches to handle them, such as Regular expression algorithms.
Grovf offers GRegeX IP- implementation of a standard regular expression algorithm on FPGA chip achieving 12.8 GB/s throughput with a single IP core. A wide range of supported regular expression functions allows developers to configure desired rules which can be handled in a chip without reducing the throughput.
Key Benefits
- 12.8 GB/s throughput
- PCRE compatible
- Customizable
- Host drivers and reference examples for using in C
- Deployable both on Premise and on Cloud
MonetX
The enormous growth in data constantly challenges computing technologies and traditional approaches we used to demonstrate. Memories barely keep pace with current tremendous growth of data and processors advancements, turning into a core bottleneck for computational systems.
Though computer technology has made incredible progress throughout the time, the dropping efficiency of modern computing points towards much more constructive changes in architecture design, known as memory-centric architecture.
Aiming to get the most out of memory-centric architecture, Grovf develops MonetX technology that expands the memory of the existing servers to several TBs per server while accelerating the near memory computing workloads. The flexible and cost-effective nature of MonetX platform makes it a revolutionary solution for datacenter hyperscalers.
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