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Right ... that's weird, why isn't Nvidia's own Jetson-page more clear on this? Confusing.
~~You only get 4 usable at any given time. Either the big core runs (A57) or the LITTLE core (A53) runs.~~ Sounds like I'm mistaken.
I am looking for something that can replace RPi2/Edison in my humanoid robot for real-time computer vision. Is Jetson TX1 a good candidate? Is it a drop-in replacement with a similar power envelope as RPi2/Edison, i.e. can be powered by a small LiPo battery?
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That really frustrates me. I'm running a Dreamplug [1] as one of the main boxes on my network. The second USB port has died and it's really starting to show its age. The Gigabyte board would give me enough SATA ports and grunt to run a decent NAS - I think it'd give the C2750 from Intel a run for its money, power wise. Your linked article has a comment suggesting the Gigabyte board retails for 987 Euros. Jeebus. [1]:…
The dreamplug is probably closer to the pogoplug in feature set (and definitely cost!). http://www.amazon.com/gp/product/B005GM1Q1O/?&tag=bcgpfeed-2... It's dirt cheap ($10-20), easy to load linux on [1], and it can be a simple file server, it can run minidlna, google cloud print [2], all kinds of stuff. 800MHz is not a screamer, but most simple I/O tasks like A/V streaming and printing are a walk in the park. [1] ht…
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No, it's more that Denver sucked. A57 is just faster.
Got any references?
If Denver's JIT happens to do well the device flies, but if you're not a benchmark or the benchmark is too large to be easily JIT'ed, then the performance falls off a cliff.
The price is quite a disappointment particularly when comparing to the Shield pricing (and how long NVidia has taken to present the kit - the X1 was introduced now almost a year ago / Shield on the market since early this year). Let's see in the next days how performance of the board stacks up once the embargo on publishing test results is over. Remember that the 1TFlops published is FP16 not FP32.
Spec-wise, Odroid xu4 [1] from Hardkernel is very close to meet this requirement, though still lacking in cpu and memory(only 32bit and 2GB memory for xu4).
The price is quite a disappointment particularly when comparing to the Shield pricing (and how long NVidia has taken to present the kit - the X1 was introduced now almost a year ago / Shield on the market since early this year). Let's see in the next days how performance of the board stacks up once the embargo on publishing test results is over. Remember that the 1TFlops published is FP16 not FP32.
The module itself doesn't seem that expensive, given that you're getting a top-notch ARM SoC. Personally I'd be interested in a group buy when it gets released (early next year, for $299 in 1k quantities).
The only Cortex-A72 chip that I know of is the MediaTek MT8173, and the GPU on that is nowhere close to a Tegra X1. So it's not like this is a previous-generation chip, despite being close to a year old.
Another 64-bit ARM board out there: the Gigabyte MP30-AR0 http://b2b.gigabyte.com/products/product-page.aspx?pid=5422#... http://www.cnx-software.com/2015/03/27/gigabyte-mp30-ar0-is-... . Unfortunately this one has limited distribution and $ask pricing.
This is exactly what I need for my deep learning research. Iv been abusing my raspberry pi 2 with heavy neuro nets. Shame about the prise though. I will wait for the price to drop(hopefully).
Heavy neural nets on a rasp-pi? How does that work out?
Wish there is an affordable ARM SOC board for building DIY Spark clusters, which has a 64bit CPU, 8 cores, gigabit ethernet, SATA, USB3, and 4GB memory (8GB memory would be even better), and under $100. Spec-wise, Odroid xu4 [1] from Hardkernel is very close to meet this requirement, though still lacking in cpu and memory(only 32bit and 2GB memory for xu4). [1] http://www.hardkernel.com/main/products/prdt_info.php