Category Archive: Uncategorized

4 Great Questions To Ask When Choosing Your Industrial PC Supplier

When choosing an industrial PC supplier for your mission-critical product design, consider these four questions before you pull the trigger.

4 Key questions to ask when selecting a supplier for embedded computing:

  1. Can they prioritize smart purchase lifecycles? Choose a partner that understands the long-life demands of embedded, compute-intensive design.
  2. Proactive Change Management – Can they speak to best practices for eliminating unnecessary, and costly changes?
  3. Collaboration – Do they offer the design expertise and personal attention to help get your product to market?
  4. Do they understand the mission-critical value of your product — offering market that fuels a time-to-market advantage?

Build For Life

If you’re an OEM developing life-improving and life-saving devices, each computing problem you solve directly impacts the quality of your product and customer satisfaction. Partnering with an ODM will save you valuable resources that you can apply to developing other critically important products. Strategic partnerships with ODMs offer:

The PC Supplier Check List For OEMs
  • Intelligent lifecycle management: Choose ODMs that anticipate embedded technology availability for up to 7–10 years in the future, serving the long-life demands of highly regulated medical and life science–related systems
  • Proactive change management: Distinguish ODMs by their proactive change management strategies  that reduce risk and eliminate unnecessary or costly changes by providing product modularity and easier design adaptation for future iterations
  • Smart, collaborative design: An ODM should configure and validate systems early in product design, helping OEMs avoid issues later on and smoothing out production issues in the long run
  • Application-specific value: The ODM should work with the OEM to provide comprehensive hardware, software, and service solutions for each specific market vertical

Click the image above or click HERE to read more.

Dedicated Computing

Choosing the right ODM partner to develop your specialized products can save you time, money, and headaches throughout their life cycle.

Contact us to discover how Dedicated Computing can help launch your products and manage ongoing change in ways that will benefit your bottom line and ensure great customer experiences.

Understanding Cloud-Based Visual System Architectures

Written by: Jeanette Ling

The Government’s “Cloud First” policy of 2011 set an accelerated course of government technology migration to cloud resources. The benefits of cloud services and infrastructure are appealing for use in simulation and training for many reasons, including the ability to provide point-of-need (PoN) simulation, freedom from hardware maintenance and upgrades, reduction of capital expenditure and hardware footprint, and practically limitless resources that allow ease of scalability. Evaluation of the fitness of visual system service for migration to the cloud as per the cloud-first guidance of readiness and value is highly dependent on the intended use case and architecture of a cloud-based simulator.

While attractive in concept, serious limitations in training quality and effectiveness can exist depending on the implementation strategy of a cloud-based visual system. This paper explores the technical challenges and functional ramifications of distributing visual system components across the cloud compared to on-premises resources.

Topics include: Latency, performance, distributed visual system architectures, latency tolerance of basic visual system components, and edge device computing.

A wide spectrum of use cases exist within the simulation and training realm, and cloud-based visual systems must provide a flexible and adaptable hybrid cloud architecture to achieve required goals across very diverse training needs and physical infrastructure.

To read the full white paper CLICK HERE

About the author

Jeanette Ling is a Principal Software Engineer in the Visual Systems group of Rockwell Collins with 30 years of experience in the industry. Her career has focused on personal computer (PC)-based visual systems that use consumer-off-the-shelf (COTS) graphics cards, and includes pioneering work on some of the first true 3D graphics cards available for PCs as an engineer with Evans & Sutherland. Ms. Ling has held primary engineering roles in producing visual systems for key military programs that span the range from fast-jet to ground vehicles, including full mission simulator (FMS) dome systems for the F-35 Joint Strike Fighter (JSF), helicopter simulators for Aviation Combined Arms Tactical Trainer (AVCATT), and ground warfare training systems for Close Combat Tactical Trainer (CCTT). Ms. Ling holds a B.S. in Computer Science and has a patent pending related to visual system render performance improvements.

To stay up to date with all the latest Dedicated Computing content, stop by the Dedicated Computing Library to read additional white papers.

Embedded Computing Systems in the Simulated Training Environment

A highly engineered, embedded computing system is critical to powering the simulated training industry. Compute systems and the integration teams require the necessary understanding of the product dynamics, modeling, image generation,content, and the hardware driving the simulator.

These advanced simulation systems power 3D content to produce a synthetic environment to realistically represent the types of challenges faced by a user. The use of embedded computing in simulation enables product engineers to carry out extensive training exercises without losing time and resources to preparation and execution failures. Consider the risks for sending a young pilot on a training exercise in real aircraft. The risks are obvious for life safety and costs.

Considerations for Military Training and Simulation Systems

Earlier simulation systems used for military training relied on inefficient coding that made them expensive and inflexible. Technological advances such as embedded computing systems and distributed compute models have greatly streamlined simulated training software, allowing easier incorporation into existing training and testing programs.

Recent developments in simulated training systems have benefited the following areas:

  • Storage
  • Compute processing
  • Display
  • Network architecture
  • Image rendering
  • Virtualization

New training systems incorporate centralized distributed storage systems, enabling simulations to meet key requirements for virtual training, including information integration, interoperability,and composability. Distributed storage enhances computing speed and scalability in training by gathering all essential information in one place, enabling awide range of scenarios to operate within the same framework.

Simulated training environments have improved processes surrounding compute and image rendering as well. These improved approaches appoint different subsystems to render images and deliver content. This distributed approach allows better display management and improved selection of types of images to be rendered, ensuring faster training speeds.

When coupled with embedded computers, distributed systems enable a point-of-need approach that incorporate real-world devices such as tools and weapons to provide more realistic simulated scenarios. These high-fidelity synthetic environments work with a fully networked architecture, enabling higher processing speeds, greater precision, and a higher form of realism for the user.

Distributed and embedded simulation systems will improve flexibility and introduce centralized databases to your training network, reducing operational costs without compromising the quality of instruction.

Superior Simulation and Training

Before the introduction of simulation systems, engineers resorted to live field training with expensive weapons or aircrafts, risking the loss of valuable personnel and equipment to real-world accidents. Embedded computing in simulation greatly reduces the risk of injury and loss of  resources by providing high-quality theoretical models to iron out the kinks in new projects before testing them in the real world.

Increasingly, military,transportation, and aerospace engineers use custom dedicated computing software,hardware, and graphic processing units (GPUs) to produce high-fidelity and realistic simulation scenarios for flight training and the military.

Currently, a wide range of state-of-the-art simulators based on embedded computing offer crucial preliminary training and testing for a broad range of military and flight applications. These systems are allowing more individuals and equipment to meet rigorous quality standards while maintaining facility safety.

Understanding the key features

Simulated training based on embedded computing systems provide the following features:

  • Compelling representation of temporal, spatial, seasonal, geographic, and specular features in high-resolution simulated environments
  • Preloaded training data for numerous synthetic environments allows users to add geo-specific content to create realistic simulations across a variety of fully fleshed out templates
  • Real-time combination and alteration of geo-specific information such as land data andelevation with geo-typical data dynamically assembles simulations for globaltraining experiences
  • 3Dcontent libraries and databases offering thousands of themes and scenarios to help users train and learn better

Learn more about the unparalleled simulation technology

The world’s most innovative training and simulation products are powered by highly engineered embedded computing systems.. These systems enable users to create realistic simulations based on synthetic environments without having to change underlying infrastructure or worry about hardware limitations. The flexibility, adaptability, and mobility of embedded computing–based simulations render thema viable alternative for equipment testing and personnel training in the military and aviation industries.

To learn more about embedded computing systems, contact Dedicated Computing.

Deep Learning: Creating Impact in Training and Simulation

Is the Modeling, Simulation, and Training (MS&T) market ready for machine learning? Our latest white paper covers five key considerations for MS&T OEMs as they explore emerging technologies such as deep learning and artificial intelligence.

  1. Understanding the Technologies
  2. Comparing GPU vs CPU Performance
  3. Embracing the Deep Learning Advantage
  4. Breaking Barriers in Training and Simulation
  5. Tapping into Competitive Value

Currently, training and simulation OEMs focus on getting the most from modern GPU architectures, tapping into steady advances to open up new possibilities for both quality and performance. This cycle has been routinely proven by the remarkable application accomplishments of the last few decades. Now an entirely new set of cognitive technologies is poised to further reshape the industry, including tools such as machine learning and artificial intelligence (AI).

Click HERE to download the full white paper.

If you’re interested in other Dedicated Computing related content, be sure to check out our other blog posts (HERE) or other white papers in our library (HERE).

The Dedicated Difference in 4:40 — Watch the Video

Dedicated Computing recently released a new video taking virtual visitors behind the scenes of their 130,000 sq. ft. Milwaukee-based facility. The 4-minute video provides a view into the company’s design and engineering facility, their performance analysis lab, and manufacturing facility.

For more videos from Dedicated, please visit our youtube page.

Medical Device Vulnerabilities and Tomorrow’s Security Threats

In an era where unprecedented data breaches are affecting corporate and government entities, the devices used in hospitals and other medical settings represent an often overlooked, yet vital source of vulnerability. For years, security researchers have cautioned the healthcare industry about their exposed medical devices.

Too often these devices are internet-capable or networked internally without encryption technology, cloud computing safeguards, or even password protection. This makes them an easy target for hackers who have the ability to steal data, disable medical devices responsible for providing life-saving care, or launch a widespread cyber attack that can affect every device on a particular network.

The Food and Drug Administration issued new guidelines in 2014 covering medical devices in the market. These guidelines stated that all such devices should be secure, be able to easily update to correct any flaws, and have safeguards in place to protect care in the event the device is hacked or otherwise compromised. The guidelines also mandated that, ideally, medical devices should include the ability to be updated and be accompanied by a list of software components that would allow hospitals to check the device for any vulnerabilities.

A Constant Threat

Infusion pumps make up almost half of all medical devices, according to the Zingbox 2018 Threat Report, making them the largest potential source of attack for cyber-related threats. Currently the industry standard is to segment these types of devices, which limits any potential cyber intrusions to an individual device. Yet, this practice also makes it more difficult to provide widespread automatic security updates to such devices.

The individual operators and medical personnel themselves leave another unyielding source of vulnerability. The above study discovered that the most common security risks originated from user practice issues, which included using web browsers on medical workstations for personal online browsing, chatting, and downloading content.

The Way Forward

The FDA offers a series of recommendations to prevent and otherwise fortify medical devices against the life threatening and/or privacy violating compromises that can result from a targeted attack. These include preemptive mitigation of cybersecurity risks early before they can be taken advantage of by hackers, as well as adopting a coordinated vulnerability disclosure policy and practice. They also encourage healthcare providers to put policies and procedures in place that will enable them to understand and evaluate risks, and discover any vulnerabilities in equipment or software.

According to the guidelines, healthcare providers must also have a plan in place to not only mitigate threats, but to respond and recover quickly and efficiently to limit patient risk. IT personnel in healthcare must be empowered to locate and neutralize cybersecurity threats, which means they must have established procedures in place for discovery and elimination of vulnerabilities.

Finally, it is always incumbent upon those managing healthcare IT systems to apply the five core principles put forth in the 2014 NIST voluntary Framework for Improving Critical Infrastructure Cybersecurity:

  1. Identify
  2. Protect
  3. Detect
  4. Respond
  5. Recover

Cybersecurity for IoT and Beyond

The burden on the industry to protect medical devices is great. Those who produce and utilize medical devices need IoT development partners who will work with them through the life of their devices, rather than supplying a basic framework before abandoning them to configure and manage the updates and security threats or breaches that occur on their own.

Contact Dedicated Computing today to learn more about the cloud computing solutions that will keep your systems current and free of vulnerabilities to threats.