CFP Submissions

[Gary <ga...@apache.org>]

Hi Devs.

I have submitted a draft to the following conference as BoFs for the purpose of attracting more audience e.g. developers, industrial customers to be aware of the values of our community and project


	Abstract Title <http://events.linuxfoundation.org/cfp/proposals?order=title&sort=asc> 	Event Name 	Submitted <http://events.linuxfoundation.org/cfp/proposals?order=created&sort=asc> 	Status <http://events.linuxfoundation.org/cfp/proposals?order=field_presentation_status&sort=asc> 	Slide 	Edit
	General Durable Object and Native Computing Model for Apache Bigdata Platforms 	Linux Storage Filesystem and MM Summit 	01/18/2017 - 11:50 	New 	Please upload your slides <http://events.linuxfoundation.org/cfp/proposals/14100/13043/edit> 	edit <http://events.linuxfoundation.org/cfp/proposals/14100/13043/edit>
	General Durable Object and Native Computing Model for Apache Bigdata Platforms 	Open Source Summit Japan 	01/18/2017 - 11:50 	New 	Please upload your slides <http://events.linuxfoundation.org/cfp/proposals/14100/13044/edit> 	edit <http://events.linuxfoundation.org/cfp/proposals/14100/13044/edit>
	General Durable Object and Native Computing Model for Apache Bigdata Platforms 	Apache: Big Data North America 	01/18/2017 - 11:50 	New 	Please upload your slides <http://events.linuxfoundation.org/cfp/proposals/14100/13045/edit> 	edit <http://events.linuxfoundation.org/cfp/proposals/14100/13045/edit>

http://events.linuxfoundation.org/events/apache-big-data-north-america/program/cfp

Abstract:
The real challenges of the JVM based high performance real time streaming/massive data processing are how to remove those major bottlenecks as whole, the local or small optimization doesn't work in most cases due to intrinsic problems about the fitting of hardware platform with software abstract layers/patterns. The Mnemonic project proposed higher abstract models to address those problems as a whole, its creative concepts target to come up with a new standards of Big-data platforms that could leverage full advantages of latest server platforms to resolve those bottlenecks e.g. SerDe/marshalling, Garbage Collection(GC) performance issues, viewpoint difference between memory space and storage space, massive object caching, object sharing across clustering and kernel caching issues. They are also looking forward to optimizing large scale neural networking architecture on top of that.

Please contact me if you are interested as additional presenters and your guidance and advice are warmly welcome, Thanks.

Very truly yours,
+Gary.