Today’s autonomous and artificial intelligence (AI) military systems process an ever-growing amount of sensor data. To handle this extreme workload, system architects must design boards using the fastest FPGA [field-programmable gate array] devices and Intel multicore processors. These devices cannot provide peak performance without massive amounts of high-speed double-data rate fourth generation (DDR4) memory for resident data and real-time execution
This white paper explains why OpenRFM can change the game in building modular, interoperable and affordable...
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
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.
Enterprises supporting the DoD can leverage commercial investment, open systems architectures and internal R&D to speed technology innovation and reduce overall sustainment and investment cost.
Technology is evolving faster than ever. Mercury's business model leverages open standards, commercial technology and R&D investment to drive innovation at a lower cost.
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.
Mercury Systems is partnering with Intel to develop high-performance, ruggedized, and secure edge computing solutions that enable mission-critical applications in the harshest environments.
SWaP-optimized and ruggedized for operation in harsh environments, learn how Mercury ’s ACAP-based solutions will bring new levels of application capability to the tactical edge.
This paper first discusses advanced capabilities that enhance LCD technology and then reviews business factors to consider when selecting or specifying display systems.
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.
Military Embedded Systems interviews Rodger Hosking and Neal Austin from Mercury Systems about the Pentek acquisition and how it impacts Mercury's SOSA portfolio.
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.
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.
Artificial Intelligence (AI) is rapidly transforming the defense industry by broadening the scope of machine applications and leveling the playing field for nation states looking to gain power.
Mercury extends EA jammer training system technology to a new platform in fewer than four months
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.
PCIe Gen 4 technologies increase application efficiency by eliminating bottlenecks and increasing throughput for multi-domain, compute-intensive applications at the edge.
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....
The inability to field the latest AI technologies at the pace of one’s adversaries often means the loss of tactical or operational advantages. Learn how Mercury’s open and modular design approach...
Our mission-critical displays are engineered to deliver unparalleled performance across multiple domains, in the most extreme environments. Hear how Mercury uses LG technology to tackle challenges...
Data center GPU coprocessing for aerospace and defense: High-performance computing has evolved into high-performance embedded edge computing.