Looks like I am a lucky dog as well. My x15 also has the industrial temp rated AM5729. This one was from the first public production run back in late 2017. I did some searching around and found the following:
1) The AM5729 is a non-catalog part, which is why there is no real public datasheet. 2) This chip has four EVEs but only one is enabled for the purpose of hacking/experimenting. Is the above correct? On Wednesday, 16 January 2019 05:30:11 UTC-8, Mark A. Yoder wrote: > > My x15 has an AM5729 on it and it has 2 DSPs and 4 EVEs[1] (Embedded > Vision Engines). I don't know much about the EVEs, but I read somewhere > that each EVE can do 16 multiply accumulates per clock cycle. The tidl > gives you some control over which processors (DSP or EVE) works on what > part of the problem. > > I'm often seeing 15 to 30 frames per second wile recognizing objects. > > --Mark > > [1] http://processors.wiki.ti.com/index.php/EVE > > On Thursday, January 10, 2019 at 4:40:06 PM UTC-5, Calvin Slater wrote: >> >> That's fantastic! >> >> I was just wondering about this a couple weeks ago. >> >> I heard the AM5728 had TIDL support this whole time and uses the DSPs >> right? >> >> >> >> On Wednesday, 9 January 2019 18:08:28 UTC-8, Mark A. Yoder wrote: >>> >>> It was recently pointed out to me that the BeagleBoard-X15 has hardware >>> that supports Deep Learning >>> <http://downloads.ti.com/mctools/esd/docs/tidl-api/> and TI has already >>> created several examples >>> <http://downloads.ti.com/mctools/esd/docs/tidl-api/example.html> of how >>> to use it. >>> >>> I've created a wiki page >>> <https://elinux.org/EBC_Exercise_39_Setting_Up_tidl_on_X15> that gives >>> a quick guide for installing and running the examples. >>> >>> https://elinux.org/EBC_Exercise_39_Setting_Up_tidl_on_X15 >>> >>> All the examples are pretrained and the X15 is just running the >>> inference engine. It's been trained to recognize 1000 objects from a live >>> video stream. >>> Using a simple webcam, I've shown it several objects (tennis ball, >>> baseball, coffee mug, beer bottle, etc.) and it has recognized them all. >>> >>> I'm impressed. >>> >>> Has anyone else played with this? What do you think? >>> >>> --Mark >>> >>> [image: Items.png][image: Water_bottle.png] >>> >>> -- For more options, visit http://beagleboard.org/discuss --- You received this message because you are subscribed to the Google Groups "BeagleBoard" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/beagleboard/b1fdf594-4be4-460f-881d-7b489bf1aaba%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
