- Language Problems
- OpenCL: internal implementation tests in MQL5
- beginning with OpenCL
Then you did not search very well ... https://www.mql5.com/en/search#!keyword=OpenCL&module=mql5_module_forum
Besides the many posts by MetaQuotes, there several posts by normal users too and their experiences.
For example by the user @Lorentzos Roussos ... https://www.mql5.com/en/search#!keyword=OpenCL&module=mql5_module_forum&author=LoRio
But there are more. So take some time to do your research.
OpenCL
The forum
- Taking Neural Networks to the next level
- OpenCL in trading - key forum thread
- SQLite in MQL5: New Features and Performance Testing - the announcement
- OpenCL and GPUs in to Agent tester
- How to modify the code with Opencl?
CodeBase
- OpenCL Test - script for MetaTrader 5
The articles
- OpenCL: The Bridge to Parallel Worlds
- Understand and efficiently use OpenCL API by recreating built-in support as DLL on Linux (Part 1): Motivation and validation
- Understand and Efficiently use OpenCL API by Recreating built-in support as DLL on Linux (Part 2): OpenCL Simple DLL implementation
- Using OpenCL to test candlestick patterns
- How to Install and Use OpenCL for Calculations
- OpenCL: From Naive Towards More Insightful Programming
- Library for easy and quick development of MetaTrader programs (part XIX): Class of library messages
- MetaTrader 5 - More Than You Can Imagine!
- Deep Neural Networks (Part VII). Ensemble of neural networks: stacking
The blogs
The documentation
- DatabaseOpen
- Databaseclose
- DatabaseTableExists
- DatabaseExecute
- DatabasePrepare
- DatabaseRead
- DatabaseFinalize
- DatabaseTransactionBegin
- DatabaseTransactionCommit
- DatabaseTransactionRollback
- DatabaseColumnsCount
- DatabaseColumnName
- DatabaseColumnType
- DatabaseColumnSize
- DatabaseColumnText
- DatabaseColumnInteger
- DatabaseColumnLong
- DatabaseColumnDouble
- DatabaseColumnBlob
- CLGetInfoString
- CLProgramCreate
- Working with OpenCL
- CLGetInfoInteger
- CLGetDeviceInfo
- many in search here
The market
- many in search here
If you want to use it for neural networks , and you have an nVidia gpu skip it go straight to pyTorch .
The main "feeling" i got is that only openCL cares about the "idea" of openCL and gpu vendors are reluctant to assign resources and money in their departments to support it.
Recent developments in nVidia reveal why that was (sort of like someone is asking you to optimize your facilities for horses while you are developing a supersonic jet)
If however you want to learn more and get the experience under your belt you can try it . It won't be fun at all though and just like with neural nets you will have the tendency to assume you learned something while you have actually not just because it happened to work . You need to be aware of that . (difference is neural nets are fun and frustrating this is just frustrating)
The docs here won't help either and you will get the sense that the person who wrote the docs is not the person who deployed the library (i feel them, i would need a vacation after that too).
There is a newer attempt by the Khronos group itself ,its called Vulkan Compute if i recall correctly and there is a high level wrapper available for c++ , i'll try and find it.
OpenCL is for programming functionality in OpenCL, not for speeding up back-tests.
Thanks for your feedback. It's not for developing an EA with a neural network, too complicated for me and I've heard bad feedback on that. OpenCL only interests me to simply increase the speed of my backtests.
I see .
The first step would be to squeeze the melon as much as possible before openCL .
So if i have an ea that has to do passes for different rsi parameters and different macd parameters i could test and see if there is a gain in loading each rsi and each macd vs calculating it at each pass (so -if the tester is not doing that already- for example if you had to test a macd setting with rsi7 rsi9 ... rsi60 etc you would remove the constant calculation of the macd which would be the same value in all these tests)
edit : the macd and rsi are for example , there's probably caching going on for default indicators . you should substitute rsi and macd with whatever calcs you run that are repetitive across tests in each new bar or in each tick.If you want to use it for neural networks , and you have an nVidia gpu skip it go straight to pyTorch .
The main "feeling" i got is that only openCL cares about the "idea" of openCL and gpu vendors are reluctant to assign resources and money in their departments to support it.
Recent developments in nVidia reveal why that was (sort of like someone is asking you to optimize your facilities for horses while you are developing a supersonic jet)
If however you want to learn more and get the experience under your belt you can try it . It won't be fun at all though and just like with neural nets you will have the tendency to assume you learned something while you have actually not just because it happened to work . You need to be aware of that . (difference is neural nets are fun and frustrating this is just frustrating)
The docs here won't help either and you will get the sense that the person who wrote the docs is not the person who deployed the library (i feel them, i would need a vacation after that too).
There is a newer attempt by the Khronos group itself ,its called Vulkan Compute if i recall correctly and there is a high level wrapper available for c++ , i'll try and find it.
Why is that ? This is very personal and subjective. You would better have said "I had not fun at all".
Why is that ? This is very personal and subjective. You would better have said "I had not fun at all".
touche` but i was describing my experience anyway , i was not describing the experience of a tall handsome dude from New Zealand with a porche who does not like hot dogs .
It was implied . 😋
The reader assumes that too . I'm describing it from my own point of view and you obviously liked working with it so , props . ps : if you liked openCL neural nets might be a breeze for you , try it.
touche` but i was describing my experience anyway , i was not describing the experience of a tall handsome dude from New Zealand with a porche who does not like hot dogs .
It was implied . 😋
The reader assumes that too . I'm describing it from my own point of view and you obviously liked working with it so , props . ps : if you liked openCL neural nets might be a breeze for you , try it.
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