IBM's library is 46x faster than TensorFlow

[Cardoso]

https://www.theregister.co.uk/2018/03/2 ... ined_fast/

[abulmo2]

IBM machines are too expensive for me, humble amateur chess programmer, to even dare dreaming at. On the other hand, I wonder what is the performance of some affordable development boards with a NPU (Neural Processing Unit) like NVidia jetson tx2(1) ot Huawei HiKey 970 (2).

(1)https://developer.nvidia.com/embedded/buy/jetson-tx2

(2)https://www.xda-developers.com/huawei-l ... n-970-soc/

[Dann Corbit]

IBM machines are too expensive for me, humble amateur chess programmer, to even dare dreaming at. On the other hand, I wonder what is the performance of some affordable development boards with a NPU (Neural Processing Unit) like NVidia jetson tx2(1) ot Huawei HiKey 970 (2).

(1)https://developer.nvidia.com/embedded/buy/jetson-tx2

(2)https://www.xda-developers.com/huawei-l ... n-970-soc/

If you want the most power per watt, those might be nice.
But if you want compute power per dollar, they are not good buys.

Pop a nice GPU in you home computer and you will smoke those units. The Jetson is (for instance) 1.5 TFlop. My 3 year old graphics card at home is 2 TFlop and you can buy an 8 Tflop card for the price of one of those mini-boards.

I just bought some GTX 960 cards at $86 each. Those are 2.3 TFlops
so:
86/2.3 = $37.39 per TFlop.

Dev Board:
$599/1.5 Tflops = $399 per tflop. Less than 10% as cost effective.
Students can get the boards for less.

[Milos]

https://www.theregister.co.uk/2018/03/2 ... ined_fast/

Hehe, proud on my officemate .

P.S. It can also be executed on Intel and Intel+GPU not only on POWER+GPU