Monthly Archives: October 2012

Research paper in R: Here is why GotoBLAS2 may be the fastest C multi threading library over ATLAS, MKL, GPU, FPGA, and others

Research paper in R: Here is why GotoBLAS2 may be the fastest C multi threading library over ATLAS, MKL, GPU, FPGA, and others.

 

I was just referred to this which shows GotoBLAS2 could be the fastest C multi threading library out there.

http://www.tacc.utexas.edu/tacc-projects/gotoblas2

 

These claims come from a vignette where there is an R package around these:

 

http://cran.r-project.org/web/packages/gcbd/index.html

 

I just extracted out of this from this research paper:

http://cran.r-project.org/web/packages/gcbd/vignettes/gcbd.pdf

 

.

Between the multithreaded

BLAS implementations, Goto is seen to have a slight advantage over MKL

and Atlas. GPU computing is showing promise but requires relatively large matrices to

outperform multi-threaded BLAS.

A second key aspect is the di_erence between static and shared linking. In static linking,

object code is taken from the underlying library and copied into the resulting executable.

This has several key implications. First, the executable becomes larger due to the copy of

the binary code. Second, it makes it marginally faster as the library code is present and no

additional look-up and subsequent redirection has to be performed…. Shared library builds, on the other

hand, result in smaller binaries that may run marginally slower|but which can make use of

di_erent libraries without a rebuild.

Shared library builds, on the other

hand, result in smaller binaries that may run marginally slower|but which can make use of

di_erent libraries without a rebuild.

How to install R with RCpp RInside for C++ HFT with multithreading capabilities for parallelizing with Open MPI in Ubuntu Linux

How to install R with RCpp RInside for  C++ HFT with multithreading capabilities for parallelizing with Open MPI in Ubuntu Linux

To get RCpp and RInside running in your Ubuntu Linux environment

Install RStudio to manage the installation of your R packages which is the lazy person’s way of doing it.  Also, ensure you have the latest R version by doing:

http://quantlabs.net/r-blog/2012/10/how-to-upgrade-to-the-latest-r-package-in-your-ubuntu-linux-environment/

In RStudio, install RCpp and RInside. Download the latest version of RInside for C++ from (under Download section)

http://dirk.eddelbuettel.com/code/rinside.html

Once the tarball is expanded in your Linux environment, navigate to the examples standard to make all the examples. Again, you will need the RCpp and RInside R packages available for the build process. Other R packages may be needed as your run the many examples.

To run the RInside examples with the OPen MPI for parallelizing examples, install Open MPI following apt-get instructions at:

http://cs.ucsb.edu/~hnielsen/cs140/openmpi-install.html

The navigate to the RInside example mpi and do a make. Run the samples and watch your jaw drop on the potential of R and C++ for HFT in a multithreaded environment.

 

 

 

How to upgrade to the latest R package in your Ubuntu Linux environment.

How to upgrade to the latest R package in your Ubuntu environment.

Get your latest Ubuntu Linux version by visiting:

https://help.ubuntu.com/community/CheckingYourUbuntuVersion

lsb_release -a and press Enter.

Follow instructions by changing the sources.list files with the correct Ubuntu version. Ensure your mirror is correct in the format of http://cran.stat.sfu.ca/bin/linux/ubuntu

http://askubuntu.com/questions/98749/installing-r-on-ubuntu-getting-updates-to-work

Apply the key as instructed and also upgrade your Ubuntu packages as well.

 

How to parallelize with R and Hadoop tonite! Complete ARIMA source code strategy walkthrough online Meetup Oct 23!

Hi there

Join Ram Venkat tonite at 7PM Eastern Standard Time to learn about how he uses Hadoop and R for his parallel processing with Python. This is on tonite via my GotoMeeting online virtual meeting. Login details:

1.  Please join my meeting, Monday, October 15, 2012 at 7:00 PM Eastern Daylight Time.
https://global.gotomeeting.com/join/275963877

2.  Use your microphone and speakers (VoIP) – a headset is recommended.  Or, call in using your telephone.

Dial +1 (647) 497-9373
Access Code: 275-963-877
Audio PIN: Shown after joining the meeting

Meeting ID: 275-963-877

Also, another Meetup is slated for North York Ont Monday 10/22 at 7pm EST.

http://www.meetup.com/R-Matlab-Users/events/85160532/#event-comments-section
http://www.meetup.com/quant-finance/events/84012842/

Lastly, another Premium Membership Meetup is slated for Tues 10/23 on a complete walkthrough of my ARIMA modelling R script. It includes fast data capture as well as a function for automatic best fit.


–> Join now go get access to this Oct/23 event! <–

Got a question,? Let me know.
Thanks Bryan

 

Q&A Order book R package for ultimate historical backtesting simulation?

Q&A Order book R package for ultimate historical backtesting simulation?

This was from an R blog visitor  

Hi! Im trying to get access to the R package “orderbook” (which is not on CRAN), any idea how to get hold on this?

 

This is an old but look really good. I would refer to these helpful URLs:

http://limitob.r-forge.r-project.org/

https://stat.ethz.ch/pipermail/r-sig-finance/2010q2/006222.html

Older download links where you need to manually install the zip through your RStudio:

http://cran.r-project.org/src/contrib/Archive/orderbook/

 

I also found this which may help:

http://journal.r-project.org/archive/2011-1/RJournal_2011-1_Kane~et~al.pdf

Online Meetup for Hadoop and R for Parallel Processing

Online Meetup for Hadoop and R for Parallel Processing

Hadoop has been so popular as a parallel processing infrastructure, it is synonymous with ‘big data’ today. This presentation introduces Hadoop as well as executing R routines with Hadoop.”

Ram Venkat is an anlytics consultant in Toronto Area with focus on R, Python, Hadoop and MongoDB technologies. His interest in statistical areas include Customer Analytics with emphasis on Opinions, Trends, Associations and Clustering.

http://www.meetup.com/R-Matlab-Users/events/85160532/

http://www.meetup.com/quant-finance/events/85160792/

Best high frequency trading HFT performance: Linux open source with C++ v Java with R, RJava,RCaller, RCPP,RInside

Best high frequency trading HFT performance: Linux open source  with C++ v Java with R, RJava,RCaller, RCPP,RInside

This has been a struggle for me for a while. It seems that I always struggle between Java and C++ regarding HFT. As I want to implement R into it vs my usual struggle between R and Matlab, this is easily the best development stack to go with. Watch this video at

http://quantlabs.net/r-blog/2012/09/fantastic-youtube-video-from-google-tech-with-demo-of-r-c-rcpp-rinside-and-rprotofbuf/

I also did some metric research of calling R from both Java and C++. It seems without a doubt, calling R from C++ is definitely the way as it is half the time vs Java.I need to thank any person developing these highly important R packages. They know who they are.

http://workshop.mkobos.com/2011/comparison-of-application-of-rcpp-and-rjava-in-r/

http://stackoverflow.com/questions/10937374/benchmarking-of-rcpp-or-rcaller-of-c-or-java-calling-r-script

Please do not engage me on this debate but I don’t have the time for it. I also will be moving on with a very primitive C++ open source trading platform for Linux. It is a rather complicated library stack but when you research the above links, it should be no reason not to. I don’t want to face a rewrite down the line. Also, I can confirm that is the best way forward on development on some kind of trading platform using R with RCPP. You can only do this in Linux as RCPP only support GCC. There is no option in using Visual C++ with Visual Studio so sorry there.

I will present my next set of steps on how I proceed with this. I do think this will be the most time consuming step I have been involved especially the amount of debugging time on this platform. Let me be as straight as possible, I will not be releasing the code to no one on my hacked version of this platform. You will need to note that this stage is becoming a very proprietary stage of QuantLabs.net development. As a result, only my Premium member will get this access through my unrecorded live webinar and  live demos. There be no track record of these steps as I am not redistributing this code to no one other than demoing it to certain people. This platform will be worth a lot of money to people so  this will really only include those who can afford it, Institutional or high  net worth. Problem with it? Move on to Google for a new search.

My time is getting highly crunched and I do not have the time to hand hold people any more. This will only be given to those who pay for my time. That is all.

I will continue to provide pointers for you but don’t expect this operation to give you an out of box overnight kit to being a millionaire by following green arrows. It does not work like that. Use the scammers known as Vector Vest for that.

QuantLabs.net now is following the footsteps of the most secretive institutional trading operations in the world. This is an expensive endeavour and I would expect only those that can afford to enter it, otherwise go to a casino to spend your money. You have better chances that way or continue losing money with your favourite corrupt trading broker. Have fun.

Get access to this membership now before these rate skyrocket.