Re: No speedup in MultiLayerPerceptronClassifier with increase in number of cores

u're thinking by changing the partitioning. > > On 10/11/15, Disha Shrivastava wrote: > > Dear Spark developers, > > > > I am trying to study the effect of increasing number of cores ( CPU's) on > > speedup and accuracy ( scalability with spark ANN ) performan

Re: No speedup in MultiLayerPerceptronClassifier with increase in number of cores

to force Spark to distribute the > data across all nodes, however it does not seem to be worthwhile for this > rather small dataset. > > > > Best regards, Alexander > > > > *From:* Disha Shrivastava [mailto:dishu@gmail.com] > *Sent:* Sunday, October 11, 201

Implementation of RNN/LSTM in Spark

Hi, I wanted to know if someone is working on implementing RNN/LSTM in Spark or has already done. I am also willing to contribute to it and get some guidance on how to go about it. Thanks and Regards Disha Masters Student, IIT Delhi

Re: Implementation of RNN/LSTM in Spark

https://issues.apache.org/jira/browse/SPARK-9273 > > Roadmap of MLlib deep learning > https://issues.apache.org/jira/browse/SPARK-5575 > > I think it may be good to join the discussion on SPARK-5575. > Best > > Kai Sasaki > > > On Nov 2, 2015, at 1:59 PM, Disha Shrivas

Re: Implementation of RNN/LSTM in Spark

ccess to shared memory) in RNN. I also look forward > to contributing in this respect. > > El 03/11/2015, a las 16:00, Disha Shrivastava > escribió: > > I would love to work on this and ask for ideas on how it can be done or > can suggest some papers as starting point. Also, I w

Data and Model Parallelism in MLPC

Hi, I would like to know if the implementation of MLPC in the latest released version of Spark ( 1.5.2 ) implements model parallelism and data parallelism as done in the DistBelief model implemented by Google http://static.googleusercontent.com/media/research.google.com/hi//archive/large_deep_netw

Re: Data and Model Parallelism in MLPC

> Multilayer perceptron classifier in Spark implements data parallelism. > > > > Best regards, Alexander > > > > *From:* Disha Shrivastava [mailto:dishu@gmail.com] > *Sent:* Tuesday, December 08, 2015 12:43 AM > *To:* dev@spark.apache.org; Ulanov, Alexander &g

Akka with Spark

Hi, I wanted to know how to use Akka framework with Spark starting from basics. I saw online that Spark uses Akka framework but I am not really sure if I can define Actors and use it in Spark. Also, how to integrate Akka with Spark as in how will I know how many Akka actors are running on each of

Re: Akka with Spark

op.oreilly.com/product/0636920033073.do> (O'Reilly) >> Typesafe <http://typesafe.com> >> @deanwampler <http://twitter.com/deanwampler> >> http://polyglotprogramming.com >> >> On Sat, Dec 26, 2015 at 12:54 PM, Ted Yu wrote: >> >>> Do

Partitioning of RDD across worker machines

Hi, Suppose I have a file locally on my master machine and the same file is also present in the same path on all the worker machines , say /home/user_name/Desktop. I wanted to know that when we partition the data using sc.parallelize , Spark actually broadcasts parts of the RDD to all the worker m

Re: Data and Model Parallelism in MLPC

option does not seem very practical to me. > > > > Best regards, Alexander > > > > *From:* Disha Shrivastava [mailto:dishu@gmail.com] > *Sent:* Tuesday, December 08, 2015 11:19 AM > *To:* Ulanov, Alexander > *Cc:* dev@spark.apache.org > *Subject:* Re: Data and Model Pa

Re: Data and Model Parallelism in MLPC

coming from the way input data is read and stored. Please correct me if I am wrong and clarify my doubt. Thanks and Regards, Disha On Tue, Dec 29, 2015 at 5:40 PM, Disha Shrivastava wrote: > Hi Alexander, > > Thanks a lot for your response.Yes, I am considering the use case when the &g

No speedup in MultiLayerPerceptronClassifier with increase in number of cores

ot;label") val evaluator = new MulticlassClassificationEvaluator().setMetricName("precision") println("Precision:" + evaluator.evaluate(predictionAndLabels)) Can you please suggest me how can I ensure that the data/task is divided equally to all the worker machines? Thanks and Regards, Disha Shrivastava Masters student, IIT Delhi