Can someone explain what is the difference between parameter server and
spark ?
There's already an issue on this topic
https://issues.apache.org/jira/browse/SPARK-4590
Another example of DL in Spark essentially based on downpour SDG
http://deepdist.com
On Sat, Jan 10, 2015 at 2:27 AM, Peng
Not if broadcast can only be used between stages. To enable this you have
to at least make broadcast asynchronous non-blocking.
On 9 January 2015 at 18:02, Krishna Sankar ksanka...@gmail.com wrote:
I am also looking at this domain. We could potentially use the broadcast
capability in Spark to
Hi all,
DeepLearning algorithms are popular and achieve many state of the art
performance in several real world machine learning problems. Currently
there are no DL implementation in spark and I wonder if there is an ongoing
work on this topics.
We can do DL in spark Sparkling water and H2O but
Pretty vague on details:
http://www.datasciencecentral.com/m/blogpost?id=6448529%3ABlogPost%3A227199
On Jan 9, 2015, at 11:39 AM, Jaonary Rabarisoa jaon...@gmail.com wrote:
Hi all,
DeepLearning algorithms are popular and achieve many state of the art
performance in several real world
You are not the first :) probably not the fifth to have the question.
parameter server is not included in spark framework and I've seen all kinds
of hacking to improvise it: REST api, HDFS, tachyon, etc.
Not sure if an 'official' benchmark implementation will be released soon
On 9 January 2015
Does it makes sense to use Spark's actor system (e.g. via
SparkContext.env.actorSystem) to create parameter server?
On Fri, Jan 9, 2015 at 10:09 PM, Peng Cheng rhw...@gmail.com wrote:
You are not the first :) probably not the fifth to have the question.
parameter server is not included in
I am also looking at this domain. We could potentially use the broadcast
capability in Spark to distribute the parameters. Haven't thought thru yet.
Cheers
k/
On Fri, Jan 9, 2015 at 2:56 PM, Andrei faithlessfri...@gmail.com wrote:
Does it makes sense to use Spark's actor system (e.g. via
