> On Jan 25, 2019, at 11:11 PM, Calvin Slater <[email protected]> > wrote: > > 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:
All Rev C boards used AM5729. The industrial part is a surprise to me. > > 1) The AM5729 is a non-catalog part, which is why there is no real public > datasheet. Correct. Having 4 EVEs is the only difference from AM5728. I have hopes the AM5729 will be public some time this year. > > 2) This chip has four EVEs but only one is enabled for the purpose of > hacking/experimenting. All 4 are enabled. > > 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 and TI has already created several examples of >>>> how to use it. >>>> >>>> I've created a wiki page 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 >>>> >>>> >>>> > > -- > 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. -- 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/D06174DA-783B-43F4-8607-E533D8529C61%40gmail.com. For more options, visit https://groups.google.com/d/optout.
