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Tag Archives: Intel
NASDAQ 100 ETF #Rally in after hours trading on #Amazon #Intel earning
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Intel TBB Flow Graph dfor rapid multithreading development of High Speed Trading
Intel TBB Flow Graph dfor rapid multithreading development of High Speed Trading
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Intel TBB C++ with MIC available for massive multicore HFT
Intel TBB C++ with MIC available for massive multicore HFT
C++ library built for massively-parallel multicore processors
https://en.wikipedia.org/wiki/Xeon_Phi
http://www.intel.com/content/www/us/en/architecture-and-technology/many-integrated-core/intel-many-integrated-core-architecture.html
https://www.threadingbuildingblocks.org
NOTE that most offloading libraries use OpenMP but it is commercial. I will stick with TBB for now.
http://stackoverflow.com/questions/615264/c-parallelization-libraries-openmp-vs-thread-building-blocks
http://www.drdobbs.com/parallel/cuda-vs-phi-phi-programming-for-cuda-dev/240144545
CUDA programmers need to remember that the Phi is designed as a coprocessor that runs Linux. Unlike GPUs that act only as accelerators, the Phi coprocessor has the ability to be used as a very capable support processor merely by compiling existing applications to run natively on it. Although this means that Phi coprocessors will probably not be a performance star for non-vector applications, they can still be used to speed applications via their many-core parallelism and high memory bandwidth.
http://arstechnica.com/gadgets/2016/08/nvidia-intel-xeon-phi-deep-learning-gpu/?comments=1
Xeon Phi might have the edge on Nvidia GPUs when it comes to double-precision FP. IIRC the performance of Pascal (and other GPUs) on DP is pretty awful, and that’s a big problem for many real-world HPC applications…
The poor double-precision performance is only an issue on consumer-grade Nvidia cards (e.g. anything that is not in their Tesla line of compute cards aimed toward HPC). In recent years, Nvidia has intentionally crippled DP performance on non-professional cards in order to ensure that those who need that aren’t tempted to purchase the much-cheaper Geforce devices instead…
Intel needs to stop playing this game of Xeon Phi vs GPGPUs like this. They are very different, and their strengths are different. After having benchmarked both of these many times, I realized that they should just be clear which problem domains are better on the Xeon Phi. GPGPU cores are “much dumber” and you get a lot more of them, which is perfectly fine for linear algebra. So any task which is asking the GPGPU to do straight repeated linear algebra (machine learning), obviously the GPGPU will be faster because that’s pretty much all it can do.
But the Xeon Phi has much faster data transfers, much faster memory allocation, can be used with standard MPI/OpenMP/OpenACC, and Knights Landing will be byte-compatible with x86. Do you have a code you already setup with MPI or OpenMP? As long as the memory requirements aren’t too high, you probably already set it up to minimize communications, and so you get a free 240 threads for every node you put a Xeon Phi in (without changing your program!). Does your program run for an indeterminate amount of time and have to allocate memory? Then the Xeon Phi will be faster. Do you have to use it simply as an accelerator, i.e. the problem size is too large for the memory of the card so you will have to keep pushing things back to the CPU? Then the Xeon Phi will be faster (and Knights Landing will have more memory, alleviating this problem even more).
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See 18;10 for vanilla pricing engine options example speed up
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#intel #shares increase after rising third-quarter revenue outlet
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Tutorial for C++ with Redis Intel TBB on Ubuntu Linux
Tutorial for C++ with Redis Intel TBB on Ubuntu Linux
Insrtuctions and checklist
Download and install TBB
http://stackoverflow.com/questions/25616064/how-to-get-threaded-building-blocks-working-in-ubuntu-14-04
Download and build Hiredis C driver
http://codingsteps.com/installing-using-hiredis-c-client-library-for-redis/
C++ driver for Redis: https://github.com/luca3m/redis3m
Use Install instructions
sudo apt-get install libmsgpack-dev libboost-thread-dev libboost-date-time-dev libboost-test-dev libboost-filesystem-dev libboost-system-dev libhiredis-dev cmake build-essential
git clone https://github.com/luca3m/redis3m
cd redis3m
cmake
make
sudo make install
In Codeblocks,for each project ensure you tell where the include path (for **h header files). Also, ensure you configure library path for redis3m.so (and any other dependable libraries are included)
Build options->Linker settings (tab) and Search Directories (for compiler)
More links:
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More links:
http://www.codeblocks.org/downloads/26
http://askubuntu.com/questions/499238/cmake-cant-find-pthread
http://stackoverflow.com/questions/12578499/how-to-install-boost-on-ubuntu
http://stackoverflow.com/questions/24813827/cmake-failing-to-detect-pthreads-due-to-warnings/25130590#25130590
http://www.howtogeek.com/howto/ubuntu/install-an-rpm-package-on-ubuntu-linux/
<div class=”feature-section–center”>
https://www.digitalocean.com/community/tutorials/how-to-install-and-use-redis
https://www.linode.com/docs/databases/redis/redis-on-ubuntu-12-04-precise-pangolin
https://github.com/redis/hiredis
http://codingsteps.com/installing-using-hiredis-c-client-library-for-redis/
http://stackoverflow.com/questions/24813827/cmake-failing-to-detect-pthreads-due-to-warnings/25130590#25130590
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Update on source code for Redis Intel TBB on Ubuntu Linux and Windows
Update on source code for Redis Intel TBB on Ubuntu Linux
For those that watched my video, I am trying to port my Mac Xcode source project into Ubuntu Linux. This is turning into a massive failure as you can combine dynamic share linked libraries with static ones no sweat in Xcode which uses CLang C++ compiler. When you move the CMake project into Linux, the mix of library types conflict during the build process. This now putting me in a rethink mode to go with the original Fastflow (instead of Intel TBB as that build is another issue). So what I am trying to do use a Windows Virtual Box Ubuntu virtual machine with a new project for Fastflow and Redis client project. In the meantime, I have posted last night’s presentation below.
Note for Windows and Visual Studio users. These frameworks will not work on Windows especially Redis for Visual Studio or Windows. I will not have time or focus to maintain different versions of this so I am encouraging everyine interested in this project should move onto a virtual machine with Ubuntu Linux with Virtual Box. These are all free.
I will post my usual updates in video or postings for reference.
Also, this flash sale will be put on hold until I get this completed.
Compiled Updates:
I am dumping Codelite as the preferred C++ due to complicated building from source code with multiple dependencies of GTK libssh etc. I am may switch to CLion which is paid.
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#intel annual growth slows
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Demo of C++ Redis NOSQL Intel TBB concurrency together
Demo of C++ Redis NOSQL Intel TBB concurrency together
This could be the blueprint for my upcoming C++ trading systems
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Please watch these videos before the last one which is the overview of this code:
Most recent milestone code with Redis and Intel TBB working together
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Overview of Intel TBB Redis NOSQL C++ for potential HFT
Overview of Intel TBB Redis NOSQL C++ for potential HFT
Combined with the links below and videos, I want to showcase the direction I am going with for rapidly implementing independent trading systems. This is similar to Matlab’s Simulink but everything is done is native C++ with 2 open source projects including Redis NOSQL and Intel TBB for the concurrency!
Check out this Windows only tool to visually design your parallel components with code generation to native C++
Quick demo of Intel TBB C++ Flow Graph Designer code generation on Windows
Simple example of flow graph with two algos executed in parallel
https://software.intel.com/en-us/node/506217
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NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!