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 > 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 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 at 10:59, Marco Shaw <marco.s...@gmail.com> wrote: >> >>> 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 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 this adds an >>> additional software stack. >>> >>> Deeplearning4j seems to implements a distributed version of many popural >>> DL algorithm. Porting DL4j in Spark can be interesting. >>> >>> Google describes an implementation of a large scale DL in this paper >>> http://research.google.com/archive/large_deep_networks_nips2012.html. >>> Based on model parallelism and data parallelism. >>> >>> So, I'm trying to imaging what should be a good design for DL algorithm >>> in Spark ? Spark already have RDD (for data parallelism). Can GraphX be >>> used for the model parallelism (as DNN are generally designed as DAG) ? And >>> what about using GPUs to do local parallelism (mecanism to push partition >>> into GPU memory ) ? >>> >>> >>> What do you think about this ? >>> >>> >>> Cheers, >>> >>> Jao >>> >>> >> >
