Self-encrypting hardware, such as Mercury’s portfolio of secure solid-state drives (SSD), provide the ultimate data security. This tech brief explores Mercury’s “five S’s” of secure data storage for military embedded systems: SWaP (size, weight, and power), Speed, Security, Sanitize and Self-Destruct.
The recent tri-service memorandum requiring modular open system approaches to be deployed in all future def...
Disaggregating processing is now enabling low-latency, network-attached everything at the edge with high-speed Ethernet connectivity, from GPU servers to NVMe-over-fabric storage devices.
For the first time in the market, there is an optimized network-attached rugged distributed GPU processing system purpose-built for challenging AI edge workloads. Join NVIDIA & Mercury to learn more.
Live from the International Armored Vehicle Show in Austin, Texas, discover how Mercury is enabling the #army to get higher performance and #SWaP optimization in a smaller footprint when 3U VPX is not
Optimized networked-attached GPU distributed processing architecture delivers NVIDIA A100 GPU parallel computing resources over dual 100 Gbit Ethernet network connections without requiring an x86 host
Learn all about how Mercury helped the U.S. Coast Guard perform their maritime duties with solutions that processed vast amounts of sensor-generated data to deliver real-time mission-critical insights
Mercury Systems and VAST Federal work closely to deliver a rugged data center-class all-Flash network-attached storage (NAS) system for edge-based data capture and real-time AI application use.
Our servers are designed from the ground up for C5ISR and other mission-critical applications where performance, reliability and availability are crucial. View our entire rugged server offering.
Xilinx and Mercury are working together to deliver up to 20× more processing power closer to the edge. Join our webinar, moderated by John McHale from Military Embedded Systems, read abstract-
Discover how technologies developed by Mercury Systems and NVIDIA scale the best AI-enabling data center processing capabilities to the edge for real-time decision-making.
Cloud-scalable cross-domain solution methodologies, challenges and implementations for rapid, secure and correct information transfer between multiple security domains.
SBIR-to-transition successes include the Joint Avionics Reconfigurable Virtual Information System (JARVIS) mission computer and the Digital Data Set (DDS) Systems for the Navy's T-45, read more-
Handling AI, SIGINT or compute-heavy workloads that require moving data at real-time speeds? Learn about our all-new RES XR7 rugged rack servers with Intel’s latest 3rd gen Xeon Scalable processors.
Cloud, Fog and Edge Computing for Defense Applications.
PCIe Gen 4 technologies increase application efficiency by eliminating bottlenecks and increasing throughput for multi-domain, compute-intensive applications at the edge.
In this webinar, you will learn how Mercury Systems, NVIDIA and SigmaX are securing machine learning for multi-domain operations with agile edge servers and cloud-native open software stacks.
Eliminate bottlenecks, process, store and move huge volumes of sensor data at 5G speeds and accelerate time to insight for all of your compute-hungry applications with RES XR7 rugged rack servers.
By utilizing the NVIDIA EGX edge AI platform for edge computing, coupled with open software stacks, machine learning (ML) data can be deployed and accelerated to retain operational advantage....
Learn how commercial open computing strategies used by social media giants and advanced manufacturing practices employed by the automotive and logistics industries can be leveraged by the Navy.
Only by understanding the mechanics of the various key management mode methodologies can the military system architect choose the optimal strategy for each mission or program.
To handle extreme workload, system architects must design boards using the fastest FPGA devices & Intel multicore processors. These devices cannot provide peak performance with high-speed DDR4 memory.