gpism

Welcome to Apache StreamPipes - wait for installation to be finished...

[INFO] Version: 0.68.0
[INFO] Environment: 'pipeline-element'
[INFO] Mode: Development mode, all ports mapped
[INFO] Docker network 'spnet' already exists. Continuing
[INFO] Creating docker volumes and starting docker containers
Creating volume "streampipes_backend" with default driver
Creating volume "streampipes_files" with default driver
Creating volume "streampipes_consul" with default driver

gpism

ubuntu:~/odc/dev$ ls
apachecon-demo-processor  incubator-streampipes  incubator-streampipes-installer
(base) ubuntu:~/odc/dev$ cd incubator-streampipes-installer/
(base) ubuntu:~/odc/dev/incubator-streampipes-installer$ cd cli/
(base) ubuntu:~/odc/dev/incubator-streampipes-installer/cli$ ./streampipes env --set pipeline-element
[INFO] Set environment to 'pipeline-element'
(base) ubuntu:~/odc/dev/incubator-streampipes-installer/cli$ ./streampipes up -d
  _______ __                              ______ __
 |     __|  |_.----.-----.---.-.--------.|   __ \__|.-----.-----.-----.
 |__     |   _|   _|  -__|  _  |        ||    __/  ||  _  |  -__|__ --|

gpism

{
	"name": "toi",
	"type": "news_intel",
	"guid": "de74a25f-e1a6-40da-ad4c-9a67af6414fc",
	"title": "Cheer for India: Novavax Jab\nShows 90% Efficacy, J&J 66%\n\f",
	"content": "Big boost to inoculation\ndrive as Novavax has\ntieup with Serum,\n\nJ&J with Biological E\n\nOur Bureau\n\nMumbai: US drug makers Nova-\nvax and Johnson & Johnson said\ntheir Covid vaccine candidates\nshowed encouraging phase 8 trial\nresults, which should boost Indi-\na\u2019s inoculation programme. Both\nnave tied up with local partners\u2014\nNovavax with Serum Institute of\nIndia (SII) and J&J with Hydera-\noad-based Biological E.\n\nNovavax said its NVX-CoV2373\nJemonstrated a 90% efficacy in\n\nphase 3 trials in the UK, taking it\ncloser to approval by the UK he-\nalth authorities. J&J\u2019s single-do-\nse Covid vaccine demonstrated\nan overall efficacy of 66%, while\nit showed 85 % efficacy in preven-\nting death (severe disease)\nacross allage and ethnic groups.\n\n\u201cThe potential to significantly\nreduce the burden of s

gpism

Best GPU overall (by a small margin): Titan Xp
Cost efficient but expensive: GTX 1080 Ti, GTX 1070, GTX 1080
Cost efficient and cheap:  GTX 1060 (6GB)
 work with data sets > 250GB: GTX Titan X (Maxwell), NVIDIA Titan X Pascal, or NVIDIA Titan Xp
 little money: GTX 1060 (6GB)
 almost no money: GTX 1050 Ti (4GB)
Deep learning  researh/model/AI: GTX 1080 Ti.
 computer vision researcher: NVIDIA Titan Xp; do not upgrade from existing Titan X (Pascal or Maxwell)