Image Processing Benchmarks on NVIDIA Jetson TK1

Pradeep ArrayFire, Benchmarks, CUDA 6 Comments

In this post we will be looking at benchmarks of the following ArrayFire image processing functions on an ARM device. Erosion/Dilation Median filter Resize Histogram Bilateral filter Convolution We pitted the brand new compute 3.2 GPU on NVIDIA Jetson TK1 against a mobile NVIDIA GPU. The closest match to the GPU (from here on referred as TK1) on the Jetson board we have in our mobile card deck is a NVIDIA GT 650M. The GPU device properties that have critical effect on the function performance are listed below. Property Name / Device Name Jetson TK1 GK20A GT 650M Compute 3.2 3.0 Number of multiprocessors 1 2 Cores 192 384 Base clock rate 852 MHz 950 MHz Total global memory 1746 ...

APU 2013 – Day 3 Recap

John Computing Trends, Events, OpenCL Leave a Comment

Big announcement here at #APU13! AMD CTO, Mark Papermaster, just announced 2 additions to the 2014 Mobile APU roadmap http://t.co/sWHMhb9AAe — AMD (@AMD) November 13, 2013 Today was the final day of AMD's APU 2013 conference. The theme of today was mostly focused on gaming topics, so it was not as relevant to technical computing as yesterday. However, the mobile product announcement from AMD in the tweet above was interesting. OpenCL is just as important in mobile computing as it is in HPC computing. Both ends of the spectrum have a need for speed and can achieve it through great data parallelism. AMD is looking to make better inroads into mobile computing with these APU announcements. Overall, APU 2013 was a fantastic ...