Expanded memory for near memory computing

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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MongoDB Acceleration via Grovf MonetX

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.