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We are excited to release VR-Exchange 2.4, a major feature release that enforces our commitment to supporting the latest protocols and the largest exercises with MÄK products. Here are a few of the changes we made with this release:

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Your squad has been tasked with a convoy mission through a town with suspected insurgent activity. As a surveillance operator, you need to spot the threats and alert your team before it’s too late.

You peer down from a UAV through an infrared camera analyzing and scrutinizing the happenings of a seemingly ordinary town. You see farmers in fields, children coming from and going to school, families en route to and from the marketplace, and religious services – everything seems normal but your training tells you that you need to look ahead. That’s when you notice signs of suspicious behavior: people moving to rooftops looking to the sky for incoming aircraft, armed civilians lurking behind corners, and most dangerous of all, a child wearing a heavily laden vest. You use your comms channels and report the potential threat to your squad leader. 

 

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At MÄK, we help our customers simulate unmanned vehicles in a lot of ways, depending on what part of the system architecture the customer is addressing. Some use VR-Forces to simulate the UAV’s mission plans and flight dynamics. Some use VR-Vantage to simulate the EO/IR sensor video. Of those, some use VR-Vantage as the basis of their payload simulation and others stream video into their ground control station (GCS) from a VR-Vantage streaming video server. 

All of our customers now have the opportunity to add a Synthetic Aperture Radar (SAR) to their UAV simulations — and here’s how to do it. SensorFx SAR Server comes as two parts: a client and a server. The server runs on a machine on your network and connects to one or more clients. Whenever a client requests a SAR image, it sends a message to the server, providing the flight information of the UAV and the target location where to take a SAR image. The server, built with VR-Vantage, then uses the JRM Technologies radar simulation technology to generate a synthetic radar image and return it to the client.  

The SAR Server renders SAR images taking into account the specified radar properties, the terrain database, and knowledge of all the simulated entities. The radar parameters are configured on the server in advance of the simulation. The terrain database uses the same material classification data that is used by SensorFX for rendering infrared camera video so your sensor package will have the best possible correlation. The server connects to the simulation exercise network using DIS or HLA so that it has knowledge of all the entities. It uses this knowledge to include targets in the SAR scenes and so that you can use a simulated entity to host the SAR sensor. 

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A week ago, I wrote a blog entitled “Do I need a new graphics card?” to answer the common question: Will I get better performance if I just upgrade my graphics card? In the blog, I discussed the difference between CPU and GPU bound scenes, and made the point that if you are CPU bound, getting a new graphics card will not help much. Typically scene performance will improve more with better terrain organization. 

While that is all true, there is one additional problem you may encounter that will spoil performance and can be addressed by upgrading hardware: running out of video memory. VR-Vantage 2.0.1 now tracks your total video memory, how much you are using, and if any of your textures have been pushed out of memory (evictions). Once you have consumed all of your video memory, the card will start swapping textures off the card and into the system memory. This is incredibly slow and will seriously affect frame rate. Scenes that were fast may all of a sudden have a 100ms draw time. 

To see how your scene is performing, turn on your Performance Statistics Overlay (found in Display Settings -> Render Settings).  You would want to see something below 80% usage. As you move around in your scene, if the memory consumption gets up to 100%, or you start seeing Evictions, then your performance is being seriously affected by a lack of memory. 

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Frequently we get questions about hardware requirements for customers who are trying to use VR-Vantage as an IG for a specific program. Typically, the customer is looking to achieve 60 frames per second (FPS) in VR-Vantage and their scene is rendering slower than they would like/expect. They have read the MÄK Blog about minimum hardware yet didn’t find the answer they were looking for.

Over the years, many of us have been conditioned to assume that buying newer/better hardware will yield better performance; if your performance isn’t up to snuff, just buy something newer. This often works – new GPUs are released yearly, often with phenomenal performance improvements. The cost for this new hardware is low compared to the total program cost, so upgrading can make sense. That said, most terrains used in the Modeling & Simulation community aren’t particularly complicated and so should run really fast even on old hardware. So how can you figure out if it’s your terrain that is slowing you down or if it’s your graphics card that is the culprit? This blog will try to answer that question for you.

To understand where your bottleneck is, you need to understand if your application is CPU or GPU bound. For this blog I will use the term “CPU” to mean not just the physical processor, but also the process of organizing and passing information to the GPU. Simply put, VR-Vantage can be bottlenecked in many places: collecting information from the network, updating the scene graph, sending information to the GPU, or the GPU itself may be bottlenecked trying to render the actual scene. Of these possible bottlenecks, upgrading your video card will only help the final case. That means if your scene is slow for any reason besides the final render step, you need to optimize your scene’s content and configuration, not by buying a better graphics card.

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At MÄK, we are constantly seeking ways to improve our products by diligently researching the latest technologies that will elevate our fidelity and performance. In this blog, we’ll tell you how we’re doing exactly that by integrating the photogrammetry process into our human content pipeline.

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Photogrammetry is the science of making measurements from photographs "” we’re using it to make a high-resolution 3D mesh. We expertly capture photos of a subject, use specialized processing software and post-processing by our team of 3D artists to make hyper-realistic, high-performing humans for DI-Guy, our Human Simulation software. DI-Guy’s ability to support multi-texturing via albedo, bump, specular, gloss, and ambient occlusion allows us to retain the minute detail of these captures while delivering them in low-polygonal, high-performing models. The DI-Guy artists use industry-leading tools such as ZBrush, 3D Studio Max, Maya, and Photoshop to translate these models from reality to virtual reality. As you can see from the photos and videos, the results are impressive. 

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Last week, we conducted a multi-day seminar series in Beijing hosted by our in-country representatives "“ Seastars Co. Ltd.  The seminar presentations consisted of Solution Architect and UAV Topics, as well as a suite of product presentations. We unveiled for the first time in China the latest capabilities of VR-Forces 4.3 aggregate-level simulation, as well as a suite of "new" functionality and capabilities offered within VR-Vantage and DI-Guy. 

Our VR-Vantage 3D visual solution has many new features, including the new integrated Oculus plugin showing a high flight fly-through over the Hawaiian Islands. We also presented our Light Armored Vehicle demonstration, which consists of physics and wheel dynamics supported by CM-Labs Vortex. Attached are a few photos taken during the seminar which includes a picture of our 50+ audience. Thank you to those who help coordinate and those who participated/attended this successful event -  looking forward to returning to China soon!

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VR-Link 5.1.3, a maintenance release with several minor changes, is out! Here are some of the most notable changes:

Platform support changes: We have added support for Red Hat Enterprise Linux 7 (64 bit only). We have also ended support for Red Hat Enterprise Linux 4, SUSE 11, and Windows MS VC 7.1 and 9.0. MÄK is committed to supporting the platforms our customers care most about; if you require discontinued platforms, contact MÄK support.

VR-Link Code Generator: We continue to improve the VR-Link code generator by making the output more intuitive and easier to read. The code generator now generates VR-Link internal classes as much as possible, helping to produce a highly consistent API. The code generator will also generate an HLA Evolved project without providing the standard MIM.

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The most recent release of MÄK RTI 4.4.1 is a minor maintenance release that makes several minor changes.

New Platform Support: Microsoft Visual C++ 12.0 and Red Hat Enterprise Linux 7 have been added. For both of these platforms, only 64 bit libraries are supported. MÄK products will only support 64 bit libraries for all new platforms. The MÄK RTI has dropped support for VC7, VC9, Red Hat Enterprise 4, and SUSE 11.

If you are a customer under support and require these platforms, please contact support@mak.com for more information.

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In version 4.3, VR-Forces introduces the notion of aggregate-level simulation. Okay. What exactly is the difference between aggregate-level simulation (ALS) and entity-level simulation (ELS)?

At the core, aggregate-level simulation is a more abstract level of modeling and therefore is more suitable for representing higher echelons of a force structure "” units like companies, battalions, and brigades. Entity-level modeling has the fidelity appropriate for individual entities, like vehicles and human characters. 

Lets look at maneuver modeling as an example. In ALS, units have to slow down to move through a forested area, whereas entities in ELS have to maneuver around individual trees. This higher level of abstraction happens for all the types of models. Combat in ELS happens when an entity has line of sight with another entity. When one entity fires, a hit/miss calculation is performed between the detonated ordinance and the nearby entities. Damage is assessed only for the entities that are actually hit. In ALS, units, which cover an area, must have line of sight to the "˜area’ of the other unit. Combat then proceeds as rates of change in the resources and status of the units. For example, a large, well-equipped unit will more quickly deplete the resources and status of a smaller less equipped unit.  

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Simulation has become an accepted, routine, and critical method of training militaries worldwide. Many nations have invested heavily in large simulations for wargaming, however there is no "one size fits all" training simulation. Software that may be appropriate for one nation may be too cumbersome, resource intensive, and unmanageable for others. A low-overhead simulation system will address a nation’s wargaming and constructive simulation requirements, while also being much more economical in terms of procurement, training, and sustainment. 

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MÄK CST fills the Command & Staff training capability gap. It combines the user-friendly features of a game with capabilities of the larger, more complex simulations to help trainees learn how to make stronger battlefield decisions. Because of its flexibility and ease-of-use, MÄK CST can be used in the classroom, in the simulation center, on deployment, and at home stations.

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If you’re just joining us in this 5 part blog series, welcome! Check out the previous few blogs describing the goal of this series, Latency benchmark info, Throughput benchmark info, and HLA Services benchmark info. 

In addition to turning services on and off as noted in my last blog, the MÄK RTI provides a few ways to reduce the traffic in the network. The two most commonly used methods to do this are bundling and compression. The ideal value to set both of these features varies by the type of simulation being done. Thus it is best to understand their effects on traffic to use effectively. The following graph shows the effects of bundling on network throughput:

MAK_RTI_Performance_Paperbundling2

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In VR-Forces 4.3, we’ve made a number of enhancements that are not immediately obvious, but are still very useful if you know how to take advantage of them. In this post I’ll share some tips on how to make use of the improved Simulation Model Set (SMS) management that is part of VR-Forces 4.3.

For those who don’t already know, a Simulation Model Set (SMS) in VR-Forces is the set of configuration files that defines the entities and objects available for creation in a scenario. This includes everything from their names and type enumerations to their behavior logic and physical movement dynamics. An SMS is typically modified using the VR-Forces Entity Editor tool.

VR-Forces ships with some preconfigured SMSs with hundreds of objects to use in scenarios, however, it is quite common for customers to add specific models, or to modify the shipped VR-Forces models to suit the needs of various projects.  In the past, this was most often done by editing the default SMS in VR-Forces directly, or by copying it wholesale and making edits to the copy. Both of these options lead to significant upgrade work when moving to a new version of VR-Forces where parts of the default SMS were edited, since the changes have to be merged.

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LAAD 2015 is one of this year’s largest aerospace, defense, and security events in Brazil, if not in Latin America as a whole. VT MÄK had the opportunity to showcase its technologies as part of the ST Electronics stand showcasing a variety of simulation solutions, as well as having our own stand where we demonstrated our latest released products.

MÄK is well established in Brazil with many customers implementing our modeling and simulation tools in a variety applications, ranging from the Embraer Super Tucano simulator, ITA’s C4i research, to AEL interoperability implementation.  

At LAAD 2015 visitors experienced the best-in-class simulation tools of VR-Forces 4.3 and our visual solution VR-Vantage 2.0, plus other technological solutions such as WebLVC.

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We’ve talked about Latency and we’ve talked about Throughput in the MAK RTI, but now we’ll get into HLA Services.

One major advantage of the MÄK RTI is its ability to turn HLA services on and off. If you are not using DDM, for example, you can have the RTI turn that feature off to get a performance increase. 

Two things need to be noted when using this feature. First, even with all services turned on, the MÄK RTI is very fast. The test federate could still send over 120 thousand updates per second. That is much more than every simulator that we know of, so users really should not fear leaving all services on. Second, every service has its own overhead cost, as is shown in the following chart:

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Last fall, MÄK introduced our FOM Editor, a web-based application for creating and extending HLA FOMs. The original goal of the tool was to make it easier for people to quickly develop their own HLA Evolved FOM modules to extend widely used existing FOMs, such as the RPR FOM. Once we had a tool that supported HLA Evolved FOMs, however, it was simple to add support for HLA 1516-2000 as well. Both 1516-2000 and 1516-2010 (as HLA Evolved is more officially known) use XML formats and contain a lot of the same information. The formats are a bit different and 1516-2010 added some new things, but there is a lot of overlap.

Until recently we have not had any support for HLA 1.3, but we just upgraded the FOM Editor to import 1.3 OMT and FED files for conversion to HLA 1516 formats. To try it you will need a valid 1.3 OMT file at a minimum, but a FED file is also recommended for a full import. Just drag your OMT file onto the Project page, and once that’s complete, follow it up with your FED file.

Things are a bit different in 1.3 than in 1516. The most obvious difference is that rather than using a single type of file, a 1.3 FOM is defined by a combination of an OMT file and a FED file (neither of which is in XML). That’s a fairly minor difference from the point of view of the FOM Editor, but there are more important differences that don’t become apparent until you delve into the content of the files. Datatypes just aren’t the same in 1.3 as in 1516, and the FOM Editor has to make some assumptions and choices when converting a 1.3 file to a 1516 file. Below is a list of some of the most notable differences between 1.3 and 1516 FOMs, as well as a brief description of how the FOM Editor handles each case.

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VR-Vantage IG delivers game-like visual quality in a high-performance image generator "” designed with the flexibility, scalability, and deliverability required for simulation and training.

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With VR-Vantage IG, immerse your trainees in stunning virtual environments. Experience 60 Hz frame rates for smooth motion, engaging action to stimulate trainees, and beautiful effects for immersive realism; all this, inside world-wide geo-specific databases.

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Many IGs are targeted to one environment. IGs designed specifically to provide the correct cues to high-flying-fast-jets don’t do so well in first-person-shootouts. Truck driving simulators don’t generally render the water well enough for maritime operations. Part of this is due to the choices in the content and part is the tuning of the IG and the graphics processing unit (GPU).

We’ve designed VR-Vantage IG to render beautiful scenes in any domain "“ air, land, and sea "“ and to fit into your simulation architectures. Version 2.0 has concentrated on both beauty and performance so you can get the most out of the graphics card.

Graphics cards these days are awesome. They take a steady stream of data and turn it into beautiful pictures rendered at upwards of 60 times each second (60Hz). To pull it off, the GPU computes color values for each pixel on your display. A 1920x1200 desktop monitor has over 2 million pixels and at 60Hz, thats 120 million color values. A lot of processing goes into each pixel so that collectively they form a beautiful picture. AAA game development houses do the work to configure the graphics card for all their target platforms; you, as a system integrator, have to do the same thing for your training customer. 

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Let’s talk about MÄK RTI Throughput. (If you’re interested in the other MÄK RTI Benchmark posts, check out our previous blog on Latency benchmarking.)

Throughput is a measure of how fast an RTI can write to and read from the network. Because throughput tells you how well an RTI can handle federations with large numbers of objects that are frequently sending updates, it is often an even more important metric of RTI performance than latency. In many real-time platform-level simulations, updates or interactions that contain 100-150 bytes of data are fairly typical. For packets this size, we have demonstrated a throughput of over 170 thousand packets per second on our test system.

For larger packets, we do even better. In fact, for packets with 5000 bytes of payload data, we have achieved a throughput of over 22 thousand packets per second, around 90% of the theoretical maximum for a 1 gigabit network. In our original test system, we consistently topped out at 90% payload usage (not counting our minimal HLA overhead); we re-ran all our tests in a 10 gigabit network to get a better idea of what our limit is and we measured over 60 thousand messages over 5,000 bytes per second.

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Welcome to the first topic of our multi-post series highlighting specifics about the performance of the MÄK RTI! We’ll start with the topic of Latency, or the amount of time it takes for data to reach its destination. 

Much of the literature on distributed simulations indicates that latencies of up to 30-100 milliseconds are tolerable without losing the feeling of real-time interactivity. Even a 3D graphics-based application running at 60Hz has 16 milliseconds in which to compute and draw each frame, meaning that latencies of 5-10 milliseconds may not even effect the time at which a particular event is drawn. Meanwhile, typical latencies for the MÄK RTI are closer to 100 microseconds on our gigabit network "“ fast enough to meet the needs of even the most sensitive real-time simulations. 

Latency Benchmark Info

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