We love seeing all of the social media posts from developers using NVIDIA GPUs – here are a few highlights from the week:
a good improvement on training CNN on #DeepLearning install cuDNN, for me in GTX-970 give me 3 times better performance per layer
— angelo337 (@angelo337) January 11, 2016
Titan X ready to go. Now time to try #cuda 7.5 sdk pic.twitter.com/UN7fL5jWTm
— Sergey Ten (@sergecell) January 14, 2016
What makes me happy? ~40000 #cuda cores in a server! #christmasinlabs @Cirrascale @NVIDIATesla @nvidia 8 #k80 #gpu! pic.twitter.com/ce5NwDqQQg
— Josh Patterson (@datametrician) January 12, 2016
Number of orgs engaged w/ NVIDIA on deep learning:
2013: 100
2014: 1,549
2015: 3,409 #futureofai pic.twitter.com/luW6DvAjSs— Jason Black (@jasonblackxyz) January 11, 2016
https://t.co/MsnfQiJ5wk
I Did not know we geeks would see the Day of the 24 Gigabyte Video Card!
Can you say 4992 NVIDIA CUDA cores!— Citizen Truth (@RobertTheGeeK) January 13, 2016
On Twitter? Follow @GPUComputing and @mention us and/or use hashtags so we’re able to keep track of what you’re up to: #CUDA, #cuDNN, #OpenACC.
