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.

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