Download File Firmware and Flashtool plus Video Tutorial compressed:
do not forget there are some additional tips from me:
How To Flashing umi cross
welcome to today's webinar from toradex about our new apalis tk1 with thenvidia tegra k 1. my name is daniel lang and i work for toradex here outof the office in seattle. later in the webinar, i will be joined by dominik.he is a senior software development engineer in ourheadquarters in switzerland and he will talk a little bit about technicalthing and how to get the tk 1 running. before we dive into the presentation,a couple of organizational stuff. so, at the end we'll have a q&aso you will be able to ask us question
and we will answer that. so, you should see in your webinar panel,a chat or question box. you can just type your question in there whilewe do the presentation, we may already answer a few while we do thepresentation and then the big q&a will be at the end of the presentation. so, thepresentation at first is a very short overview about toradex and then we will do anintroduction about the apalis tk1 and the tk1 soc. then you will hear about apossible application and demo, so, we will have some videos and some stuffpeople do with the tk1. then it will get more technical: how to getstarted; and then dominik really will show
you how to install the latest images; howto work with the jetpacks, and so on; and then at the end we will do aquestion and answer session live. so, a very short introduction about toradex.so, toradex was founded in 2003 in switzerland. in the meantime, we sprang overthe whole world as you can see. so, you should find somebody in your time zone or very closeto your time zone, you can call office and they can talk on your issue. toradex is specialized in arm embedded computermodule or a system on modules. our customers are in a wide rangeof
vertical talking industrial automation, medical, automotive, avionics, test and measurement,digital signage, and so on... ... basically everything except like thetypical consumer super high volume, things we don't do. our socs are from nxp,from nvidia which we will cover today and from marvell. we havein-house support for linux. so, we do linux by ourselves, we do windows embeddedcompact still, actually not on the tk1, but on some of our othermodules and for some selected module, we started now supporting windows 10 iot core, so that we also have a webinar overthat if you're interested. also, as i said
software and hardware is in-house, so ifyou have any trouble and many times if it's not clear if it software or hardware, you can just get in touch with us and wewill help you. so, about the product, that was already abouttoradex. we will get started about the product. we have two main productfamilies of computer modules. one is called colibri. it is a small sodimm form-factormodule. we released the first one in 2005, so they are around for more than10 years. there is a wide range of modules. we alsohave very a low cost module starting at $24 including ram, flash, soc, power management, everything on on the module and
we also have some very low-power module andthey have the typical let's say traditional embedded interface, like spi, iâ²c, and so on. and, all themodules in that family, they're pin- compatible, so, if you design a carrier board 10 years ago, you still can plugin the latest module. then on theother hand, we have the higher performance apalis moduleand actually the tk1, it's apalis module, so that fits in thatgroup and you can actually see that it's the module on the top. this is an mxm3-basedmodule from the form-factor and it's really talk a little bit more onhow high performance has also higher
bandwidth interface like pcie gigabitethernet usb 3.0 and other high bandwidth interface for display andcamera. for the module, you also need a carrier board. here on the left side,you can see on the top, our evaluation boards, it's really big but you have easy access to all the pinsand its really good for proper typing and and especially if you have hardware, youhave to connect that and that's a good board. then, also the iris in the middle,it's also from toradex. i hope with the connector, you get a feeling forthe size, so it's much smaller; can be used as a single board computer; has hdmi,and so on. but we also have third-parties
carrier board for our colibri family, we alreadyhave a big range from third-party companies providing carrier board forour modules. for the apalis, we just begin now to add the few one and hereyou can see one from a company called diamond systems, it is currently in averification mode and i hope that it will appear soon on our website. but mostcustomer actually they design their own carrier board. so, for all our carrier boards, it's openhardware, so all the reference in altium, a file format, or pdf is all available. youcan go on our website there and you'll find a lot of tools and help ifyou want to design your own carrier
board. then if you talk of our website,very short something, toradex is famous, it is really our developer resources and howwe help you developing on our products with the developer website, a developer center with more than 800articles. we update that daily. we have a quite new community forum. it'svery cool. if you know stack overflow, it's little bit inspired by that, so a very good overview. you can alsoemail us directly of course and as you seen in the slide before, we have supportoffices around the world they all have phones, so if you're in trouble,
don't hesitate to pick up the phone andgive them a call and then of course you've video tutorials and webinars like theone you are enjoying at the moment. so now, we will look at thehardware. so, first we look at the module level, sothe apalis nvidia tk1, it comes with 2gb of ram, 8 gb of emmc flash memory, soit means that you don't need an sd card or an sd or anything externally to run your operating system,your program from, you can do that directly from that onboard flash. it alsohas a wide temperature range. so, our early prototypes,
they have a little bit smaller temperaturerange but the volume product has -24â°c to 85â°c and short overviewabout the interface: so, it basically supports the interface of the apalismodule, i don't go through all of them but here are some highlights. you only need the single 3.3v power supplyto get it running, you have a usb 3.0 (two lines). you have hdmi and lvdsfor displays, it can connect 4k displays. actually, you have also have also displayport and the embedded display port and then you have the camera csi interface, so with the
csi you can connect up to threecameras with pcie gen 2.0. you have a two high-performance can interfaces whichare actually realize that k20 microprocessors. this is actually acortex m4 and it's freely programmable. it is connectedto your the spi, so if you don't wanna use it for can and you have other low latencystuff you want to do, you maybe could even use that. then also maybe mentioncompared to our other apalis modules, we did not connect the parallelcamera interface and the parallel lcd, so if you have a parallel lcd on yourcurrent carrier board, please get in
touch with us so that we can look for asolution. so, now i will talk a little bit more soc. so, itcomes with 4-plus-1 arm cortex a15. so, we say 4-plus-1becausenormally we have four cores in there running up to 2.2 ghz; however, ifyou don't fully load the system there is an additional core, it's also called a15 but it's designedfor low power, so the system will automatically migrate yourprocesses to the single a15 core to preserve power so youcan really see the design from that system they were really considering powerconsumption and up to 2.0 ghz
and i think one of the nicest featuresof the tk1 and really one which is a big difference to more or less all theother soc is the very strong gpu with 192 cuda cores. we will look at thata little bit later closely. you can connect 4k displays and it also has a quitestrong video decoder. you can do 4k in h.264, it can do up to 4 things simultaneously,full hd screen, and you can also do h.265 which will load the gpu, sothere's not everything done in the hardware but it can have a full hdstreaming h.265, so this in your codec if you like. you can also encode 4k videos upto 24 frames or 60 frames at full hd. then, here a little bitmore
about the gpu, so it's 192 cuda cores meansit can really use it for general purpose computing. so, you can use it to render very nicegraphics but you can also do for signal processing, for deep learning, and soon and so just general calculation. nice thing also is that you have unified memory, so the memory is accessible from the cpu and the gpu directly. on a traditionalpc, you have a graphic card, which is connected to your pcie and all their
connection. so, if you want to share dataall over the city, you need to process a little bit and then the gpu and go back andand forth, you always have to copy over pcie to one side and then back. so, withtegra, you don't have that, you can access both together. so, depending onyour algorithm, that can give you a big boost; even maybe the cpu's a little bitslower than your i7 and gpu maybe too. and, what we have supportfor framework and feature. you have the full opengl 4.4, so it's not just a mobile gpu, so you havethe full opengl 4.4 like you know from a pc. you also have the opengl es 3.1, you have cuda support, you have
opencv, a very popular framework for acomputer vision and there we have optimized libraries for tegra. so, it you can just replace your opencv functionswith this optimized one for tegra, we also support nvidia visionwork. then,let's talk a little bit about the application. we think the tk1 isinteresting. i hope you have also a lot of ideas but here a few thingsthat people doing and what we expect, so one thing which we already gotquite some requests for is tk1 clusters, you're not just use one tk 1, you use severaltogether.
it was not very obvious for me why you wantto do that but we talked with people and its really a unified memoryand that you have so many cpu cores together coupled with the gpus that givefor some algorithm that's very ideal. so, people really want to basicallysurface full of this apalis modules. we already have a third-party doing acarrier board which you can plug up to four apalis modules in it and then youcan couple them together even more. so, if you're interested in the cluster and youwant to have a carrier board with several apalis module, maybe don't want to doeverything by yourself,
get in touch with us and we canintroduce you to the third-party. then, another application we expect issignal processing that it replaces fpgas and dsps. so, the gpus, they have very good if you can parallelizeyour work and many times you can do that in a signal processing. if you are very good at floating pointperformance, it is a little bit less deterministic than fpgas but we reallyhave it in hardware but it's easier to program. i think it's easier to findpeople which can be taught on cuda or i mean it is very close to c
so then they can vhal or allthese tools for fpgas. it is easy to migrate to other gpus and so on andthere is already applications like in radar application. also, theunified memory here again a big advantage but i mean that's a hotly discussed topic, what's better in which use case, also it'snot always the gpus but it's many times it can be, so, we think, we willsee quite some applications there. then the nextthing - a demo. so, let me show that that's about a user interface done with qt,so something a little bit more traditional and also i didn't say thathere, so, in the chat window, so we will
show you videos. we had problems in thepast that not everybody could see the video. if you can't see the video, justclick on the link in the chat window and you will see theyoutube video of these clips. they're all pretty short, so you can watch it onyoutube site. i start it here. i hope that works and so you see thatthe iris carrier board with apalis under the heatsink and that's a qtui doing a 3d qt 5.6 for that demo and you see it'squite advanced, lot of lightning, lot of parts. but that works all very smooth onthe tk 1, so i think even the most advanced
user interfaces, that will begood. it's also what's run on a full hd. the demo was providedby kdab, a partner company of toradex. so, they can help you with qt, c++,opengl stuff. so, if you want to have an application with qt or you wanna have areally fancy user interface, they can help you with it. here on this slide, you see a littlebit what they do. so they quite experience, they also do qt training. if you look for training, you alsowork with qt directly, so because it's a very popular framework to do uis. they alsomaintenance the
qt for windows embedded compact, so if you have anyquestions in that direction. so next, let's talk a little bit about deeplearning. just very short what it is. i mean the talk would go much too long but i try to make it avery short. the idea , you may already know about the traditionally, if you want to acheive something like detecting a cancer cell in a human tissue. thepicture of a tissue needs to find the cancer cells. so, you need a lot of know-howon what you have to see when it's cancer and then you need a specialist ina computer vision to do edge
detection to check on color and so on. so,it's very complicated! you have to write a really detailed algorithm. withmachine learning you do it different. it just had a lot of data may be fromthe couple of years where people manually detect thecancer and then they mark that's a cancer and that's not and so on. so, we have a lotof pictures, a lot of information; you just feed that in a generic algorithm i sayhere. there are also different ones but
more or less, it's the same concept andthen the computer will figure out by itself how to detect cancer. that's kind of thewhole idea machine learning and deep learningit's one part of that. so, with the deep learning there were someof my recent remarkable result like google's deepmind, so also nvidia's car called bb-8 running davenet, so thatwas a car it learned driving from end-to-end so therewas not guys programming detecting the street, then how do i need to brake, how doi need to steer, so they just teach the
car basically driving and it learned everything from end-to-end. if you go on the internet or some pretty funnyvideo and you see when it learns at the beginning it's not so good and does somemistake. it's also the imagenet competition. that's a competition where you try to describe picture or know what's on picture and the latest algorithm - that's a deep neural network running on gpus, they're outperforming humans. all that stuff reallyshow that gpus are ideal to run this deep neural network. then, a veryshort talk on how a typical looks if you do that, so you have all the lots of data,let's say all the pictures which are
marked what it is. then you feed that in abig computer, typical that's cloud computing. somicrosoft, amazon, google, they all have services for that where you canreally train that. it needs a lot of performance. microsoft as a microsoft nvidia also provides high-performance computer you can put on your desk likethe the digits but they are heavy computers needa lot of power, it's not something you would have mobile they're alsoexpensive. so, after you trained it, you get a trained model that doesn't need thatmuch performance anymore but it's still typically in the cloud, for example onyour cell phone or if to do was recognition or
something like that, normally ittransfers some data to the cloud i can see that trained model detects thepicture or the voice and then send it back. but now with tk 1, you can actually take thattrained model and put it on the tk 1 so you don't need that connection to thecloud anymore. you don't need the cloud computing, ifyou're a uav, if you're on the water, if you're robotic, if you are may be amedical device like ultrasound and somewhere you may don't have thatreliable connection, that's all you can do that everything onthe model and that's pretty cool.
i will show you here a small applicationwhich was realized with deep learning. it's a traffic sign detection demofrom our partner antmicro. so you can watch it on youtube ori can show it to you here. so, you see their stereo cameras, csi camera connected to this carrierboard. our module is actually on the bottom, so you couldn't see that, but it'son the roller. it's a demo we also had at the embedded world and youcan now see the camera detect actually three times and it reacts : so 05 - it drives slow; 10 - drives faster; if there are arrows - it will steer. thatwas all done with just showing them all
the signs and the neural network weretrained and then it was transferred add to the tk 1. that demo was providedby antmicro. this is a longtime partner that did many hardware and softwareproject for our customers. they can do custom carrier boards if you don't wantto do it by yourself, they provide software services so if youwant to have some good optimization opengl, machine vision, deep learningon, and many more. so, if you don't have the knowledge but you think for your application that will be cool, so i have to share my screen again.
then contact them and then they canhelp you. they also do the android support forour module, so they have actioned android for the tk1. also with higher-end camera, so i can also show you that short video. so, here you can see our evaluation board with tk1 module and yousee the camera connected there or hdmi first and then a csi adapter andyou can see android running on that module and the camera running and yousee it's pretty nice quality. then other partners sighthound, also inthis deep learning and they focus on
face detection and they have softwarewhich can run in the clouds, so they have that cloud model at the beginning, they have that. but you can also bring it to the device and they're quite good inthat, so i will show you a demo fromthem. so, you see at the beginning, you will seethe training. so that it learns the face from all sides with sunglassesand so on and and then later it really can detect people and know who iswho and it also detects if somebody does not fit in. they also have a tool where users candirect to that on the tk1 demo.
you can login via web browser and thenlearn your faces and so on. so, if you are interested in more aboutthat for all the partners, just get in touch with us. then the last one is also a partnercalled aerial guard. so, we just started working with them. they also have a solution for tk1 and mostly for drones and mobile robot for object avoidance, so you don't fly into seeing it. it can find the best paththrough trees and i mean that also takes advantage of this learning. it has astereo vision camera connected via usb 3.0 and i also have a smallvideo about that.
so, here you see that the setup and thenyou see here the view from a drone and then here you see the drone flying between trees and it's really autonomous not flying into the tree andbasically find out its way between these trees and that's just with camera not with radar or any other expensive sensors. so, that was my part. nowit will get a more technical. i will give the presentation to dominikand he will talk and how you can install the latest toradex bsp and wehave a different variations at the moment, a little bit for what they areand then how you get really started if you got one of our modules.
so, i will then tranfer it to dominik hello everyone! my name's dominik. i'm going to show how toprepare and flash two different images on the apalis tk1. ok! we will start with our own toradex bsp. there are basically two ways of getting it: you can build it yourself, we provide all the sources and instructions onour developer website; but you can also download bsp packages directly fromour servers. our bsp is based on angstrom distribution build with yocto. thethe bsp archive that you can get from
combining the bsp, our demo given on ourwebsite contains everything you need to get the board started. so, starting from u-boot, the linux kernel, device tree, root file system and all of the flash scripts. and, when you get themodule, the module is already flashed the bsp, so we can start work right away. you don't need to do this. you can doit when you want to update to the latest bsp that we have released oryou want to recover the board for some reason or it does needs a flash drive. currently our bsp apalis tk1 supports hardware video decoding and encoding solutions and graphics acceleration.
okay, so i'm going to start by downloadingthe bsp and unpacking it. the bsp right now is as you can seearound 150 mb and that will just an entire image and kernel and stuff like that. after it's unpacked, you can basicallystart and create and update file, you can create update files. possible update device for the apalis tk1 is the tftpnetwork update or you can copy the update files to the sd cards. this is consistent with all the other devices and you can actually create a single sd card that is able to updateall of our devices and different version
of the software for different devices. okay, so now we've created the image. we have used either the tftp or the sd cards for our estimation and we can move to themodule. we will screen for a moment. we focus on the serial console. this is a serial console of our board during the boot. if youwant to update the board, you will need to break the autoboot and it will drop you tothe u-boot shell and then will you basically just need to issue a run setupdate command. this command will automatically detect which way you're tryingto update the device, whether through mmc, or tftp,
or usb device. ok, because you can see it detected thati have the tftp server and it started downloading/flashing scripts from it. after theflashing scripts are downloaded, you can choose whatever you want toupdate in that board by running run update or you can basically run update onthe u-boot, kernel, device tree, or file system by running run update with file system, u-boot, and so on. you can find more information on ourdeveloper website. so, i'm updating the entire module with run update. this automatically starts downloading and
flashing the image and it will restartitself after it's done and you should boot right into the newupdated framework. okay! now, we will move to installing nvidia jetpack. this is ubuntu based root file system that nvidia provides with all of the cuda, visionworks, deep learning stuff including multipledemos and samples. we're looking for a way to integrateall of the nvidia binaries into our bsp but
we're not yet there. you'll also noticethat nvidia jetpack is much bigger than our bsp. so, in case you want to... youare using a lot of space that this is something to consider. so, to install nvidia jetpack, you doing it in ubuntu but in o core. you can do it in the virtual machineand that's actually what i am using for this demo. i already downloaded the jetpack for free from nvidia. you need to let it start running it. it will uncompress itself and present the dialogue, yup
you will go next. at the next screen, you willneed to verify that it's the directory that you want to use. it will download a lot of data. i think about a little less than 20gigabytes and so we need to have enough space on your device in this regard. well, now it will prepare and give youoptions of what do you want to install. so, here you can see all the options. i dorecommend starting with the standard install. and this will include most of thevisionworks, cuda, and sample stuff, as well as our ubuntu image. so, basically i just click next andaccept the terms and conditions and it
will start downloading and installingstuff. so, i am going to fast forward it. yeah, that's a lot of files to download. so, it will take some time for you. okay, once the instance is completed then proceed to the next. this is actually getting the files to the device and unfortunately since jetpack installer is designed for the jetson board from nvidia and our boards are a bit different. we need to generate ourown images for flash and flash them as a toradex update scripts. so, i'm goingto do it right now. you need to open a new console. i have created
a new... i am going to pack the root file system created by the jetson installer, so i can use this laterwith our bsp. after that, you will need our bsp. you candownload this first. that's what i am going to do. and, we install pockets of course. after it is done unpacking, you need to basically we need to replace theexisting root file system that is provided with the bsp with the one that jetson installer hascreated. so, i am going to change name of the existing root file system and thenunpack our jetpack root file system in place. okay, since our update scripts
are relying on a veryspecific... okay, size of the image is increased free size of it and it has increased from 150megabytes for our images to over 2 gigabytes for the nvidia image it will giveus a little more free space while rendering first boot and we will also needto include a etc/issue part because we are using this just one to determine which module the image is made for. so, i'm just usingapalis to get one as a module and right now we can generate the update files. and from now on,
the procedure is the same. as for the bsp,you have the files, for you can use tftp or sd card and so yeah, once you select that we would be one to use it to the module run setupdate and then the module once again will recognize that i'musing tftp and start downloading updated scripts. once again i'm during run update for the update of thewhole board. this time it will take a lot more timeand then with all our bsp image but it will finish and you will once again reboot the soc and start putting ourimage.
yeah, it is reset and it is starting. after the first boot, iwould recommend running resize filesystem to occupy the entire emmc and this will happen automatically on our bsps and once you do it, you can reboot the board and we can start on the next part of the tk1 jetson installation. we need to go back to the jetson jetpackinstaller and click next it will start creating an environment for the install like setting up network on the host for the dhcp and creatingimages for update.
after the jetson style is ready to installimages, it will ask you. yeah, it will ask you to put the device inusb carrier board. you must not do that. this is some instructions only for the jetson tk1 board. we havealready flashed our devices using our bsp scripts. so, basically we need to press enter here and leave our device boots at ubuntu. thejetpack installer will recognize that it's unable to connect. after trying to do it few times... andactually we will continue without any problems.
yeah so, as you can see that it says that it failed to flash the device and you can press enter to try again and it will fail again and then try to willtry to find our jetpack device and still since it's not just it's not going to be able to do it automatically. so here you need to choose manual enter the ip address. after you have selected that, you have a prompt when you caninput device address. i'm checking it on the board right now. that's our new ip and we know that different password and user name for ubuntu is ubuntu and password ubuntu. so, i am entering it here.
yeah, after a while it will connect to the board overssh and it will start copying dev files and running updates. to get allof the necessary files on the board after installing all the packages as youcan see on the list, it'll start cross-compiling gameworks samples and cuda sample. itdoes take a lot of time and so be prepared for that. yeah after the install is complete, you basically have that's the ubuntu user home directory. you can see we have gameworks, opengl samples and nvidia cuda samples, visionworks samples and right now i am going to show the visionwork samples.
you can also see it on youtube. ok, this is the screen running on our eval boards with the tk1 on it. that's the visionworks demoshowing car recognition using single camera. we can switch betweendifferent views, for example at point close for recognizing objects. you can turn on fences. so, it will try to recognize where are theboundaries that you are not allowed to enter because you'll bump into othercars. you can see this here. this demo is running on just twocores and not fully utilizing them, it's also using a video encoder and few cuda cores and so it's actually not
very taxing. we have a lot of free resources on a cpu formuch more elaborate demo applications. and the otherdemo that i would like to show is the apalis gpu demo. sorry about that. yeah, the gpu demo. you can also find it on youtube. it runs natively on tk1, as you can see ofall translucency and reflections and different surfaces. it is very fluid. it runs on 240 frames per second and asyou can see that the ui is veryresponsive. okay and the other demo that what i have is a camera demo from, we have a
basler camera from one of our partners. it's a full-hd camera capable of 112frames/second. it's usb 3.0 camera. so, you can see here, this is a camera that is natively tk1 and it's a full hd image with112 frames which is effectively over 250 mb/s of bandwidth through usb3.0 up to a screen with video recorder. and that still leaves us over two unused cores on the arm and a lot of cuda to do video recognition and other computer visionstuff. the final setup for today isour full open source demo.
we will go the setup. so, if you want to, youcan run the latest mainline kernel and the nouveau open source driver on thetk1. it will give you hardware-accelerated graphics as well ashardware-accelerated desktop and whatever weston or glamour. the demo is based on arch linuxdistribution. so, i'm starting installing you can findall of the information on nvidia on their help page and there is an article coming on ourdeveloper website on how to achieve the mainline linux kernel + nouveau on a apalis tk1. okay, so that's all of the are installed. i'm actuallydownloading nvidia repo bundle for
the tegra nouveau root file system. and since the check at the current apalis tk1 module is the device tree for it isalready main-lined, you can actually run this figure out an application. and, all the general modification help is going to their minor verification link and all the things that i will show you later. now, we need to export our cans directly to cup variable, with scripts to work and basically we are stuck withdownloading actually root file system. now next we're running download-gcc. download the appropriate cross-compilersthat they required.
so, the after the toolchain is downloaded in an instant successfully. you can prepare filesystem. it will be updated install all the... run and install the required packages. after that we need to modifythose kernel scripts does our bsps using your images that are zimages. that is why you need to change the image type and also include loadaddr whichfor our module is 0x80008000, we can now split the kernel. as i said, the apalis tk1 support isalready in my main kernel.
there is our device reader andso the umi that is generated here and interested look in the image is all that in it. after the linux the kernel is built successfully. you can move to the nouveau driver building. and then we need some extra packages like pthread drm and i'm also going to build kmscubeto verify that everything, 3d graphics is working correctly andinstall weston. there is also a set of scripts for running a building xserver ifyou really want to.
basically, this will create a root file system and the kernel and device to images that you can use again with bspfor flashing. so, once we put the the weston, we go to the outdirectory and we will once again create a tar archive with our root filesystem download the bsp, unpack it, change the root file system name and unpack and basically replace our root filesystsem with thier
arch file system that we havegenerated from the nouveau installer. and, now they are going to extra steps compared to jetson stuff. we need to update the kernel image and the device tree because we are not going to use the frequent and that we supply with our bsp but going to use main line generated by the installer. so here i am creating some files thatare required and links that are required by our update script to generate a properimage of flashing. and after this is ready you can go ahead. issue file - etc/issue file so the others can recognize our work and
the rootfile is created for it and after that is ready we can generate update images. so the images are generated using sd card or network tftp methods just go to the box, run updates and after the boot you will have full one resource arch base and linux runningon our board with the gpu acceleration, smooth ui, and under the cpu levels for the ui. so yeah, that's it for the this part. i showed you how to install and prepare and install three different images on our board that's ubuntu with jetpack, full open
source arch-based with mailnline kernel and our own bsp and we can now move to question and answer section. i see here one question about the availabilityand a price of the module. so, from starting today, you can actuallyorder the tk1 in our workshop. we expect shipping in about two weekshere in the us and the price for single quantities is 219 us dollar and in theprice of 1k/year it is 175 usd. and, you can actually see all theprices for volume and all the steps and all our website so we are quitetransparent. then i think we also have the question about dsi displayinterface.
maybe dominik, you can answer that. yeah, and so weactually have hdmi edp under these records. dsi up to quad channel tunnel and singlelane lvds available on on the tegra module andthey may not be available simultaneously as they need to check with the bustlemarks options. then other questions about heat. so, if you need a fan. and we expect that most applicationthat go in volume will be fanless however the module generates quitesome heat if you fully push it and ew definitely really recommend if you buy a module to get our heat sink. if you
really plan to push it in andespecially in evaluation if you don't really want to have to worry about the temperature, you also can add a fan, so all our carrier board they have athree-pin motherboard connector for a fan but also i mean the module is new so we expect some optimization in power consumption and also when youdo your final design. i mean there's way for example toconnect the module, the heat's fitted directly with the case of a device toget rid of the heat and we also will update our developer website withmuch more information about the thermal and the use cases you already test andtips for that.
ok, i see another question. thequestion is "can the gpu be split between multiple applications?" so we have bsps you can run multiple opengl or cuda applications. you know there will be some overheads but it will be quite minimal. okay! there is other question if youplan to release windows embedded compact for tk1. no, we reallydon't at the moment. so that will be actually the first toradex module that will not support windows embedded compact. i mean it's not impossible to get it running of course. the problem isreally that the very nice thing about tk1
is the gpu and then the windows ce isreally not ideal if you want to do gpu computing and things like that. youdon't really have cuda and things like that. what you're actuallydiscussing is if you want to bring windows 10 iot core on that module. so, if you have any feedback or you feel you have a use case where you would like touse windows 10 iot core on a tk1, please get back to us. the image ishowed with the arch. so, the mainline kernel that passes through nouveau driver, can be used with ubuntu as well, but that's an unofficial open source driver. right now, the nvidia is not supporting ubuntu 16.04 and we are based on the jetpack over nvidia.
so, just to make clear here he had a questions about, "will you have support for ubuntu 16.04 with opengl 4.0 support?" i would like to do the cpu/gpu memory transfer. so is there specific setup required to make use of the unified gpu/cpu memory to transfer data between the two? so, i would recommend using the jetpack because it gives you all of the toolchain, probably cuda and computing and but if you want to just write it pretty much per in linux, you can use nouveau driver on our bsp. but to get the cuda and all of theopencv for tegra, you do need nvidia
system and all of their binaries. ok! thanks a lot for joining and we will follow up with an email where you can find the recording of the webinar and soyou can rewatch the part of especially of dominik if you couldn't follow and of course to find also this information on how to install thesedifferent bsps on our developer website.
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