Compiler Optimisation : CPU/GPU/Vector/Float : Transparent Open CL Direct compute.
OpenCL, Web CL, Web Compute, Direct compute & Integration of CL code into gaming & web content..We are able to utilise processing unite types by running the majority of code within a single class,
Such is the case, But we need to optimise the interruption cycle with Open CL Compute,
After all is it not the objective to receive code that compiles well on all?
Proposing to streamline the coding stacks into the Open CL pipeline allows simplification of the complicated task of writing in Open CL & also optimises code is such a way that it is :
Faster, Smaller & safer.
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To implement the usable and fully functioning implementation of Open CL direct compute,
For the improvement of CPU MMX,scalar,Vector pipelines into the system architecture of future & present systems.
The open CL, Direct compute pipeline is predominantly vector & therefore,
Open CL Direct compute pipelines are by nature compatible with Scalar Vector architecture..
This means CPU,Float,Vector & GPU, This also means that Open CL structures can be directly encoded into scalar vector,GPU & CPU pipelines easily using vectorised compilers,
The advantage of vector pipelines is the CACHE; By this i mean all processor caches,
In type vectorised pipelines are also faster in integer.
While directly vectoring pipelines may be problematic, Mathematically clean balanced vectors are by nature error proof & fast.
Therefore OpenCL Direct compute is implementable by encoding that is to say compiling directly..
to the CPU feature sets & GPU, Vectorised floats are manageable in AVX,Scalar Vector functions and usable by floating point units, non floating point variables are capable of CPU integer encode.
Compiling code directly from languages in GCC & other compilers into Vectorisable variable adaptable code is also manageable in transparent compilation that makes invisible the necessity to compile code that is only usable one single way,
With pages in php with database backing rendered Though:
OpenCL Direct Compute maths scripting the output into Vulkan,ESGL & DirectX..
The usability of Open CL compilers; Enabled to write instructions for Vector processing units & float & Yes even Integer instruction sets such as X64, Is most important.
Function of the Floating unit : FPU : Scalar Vector Unit & Integer ..
Are fully compilable with instruction conversion & microcoded objects.
Allowing the system HPC to convert all available computation unity into realestate for high performance computing and gaming, rendering, Dynamic compiled code objects .. All at the same time.
Since compilers such as GCC shall have object compilers for Open CL Direct Compute code..
Direct from C++ & Fortrans & the objective code will be optimized for compute unite by class,
Float, Integer..
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Data Example Chart: OpenCL Backed data object hive: data science, web pages and gaming
With pages in php with database backing rendered Though:
OpenCL Direct Compute maths scripting the output into Vulkan,ESGL & DirectX..
Into: object orientated data & charts, Into 2D/3D web pages & charts or diagrams.
Alternatively the rendering of High performance computing can compile and output:
Machine intelligence data, Medical data sets, Bioinformatics & gaming data informatics such as consoles & 3D Renderings.
Into: Web pages; Including JS,PHP & Database that back the dataset hive we need to improve the scientific readability & look.
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However since float and integer exist together; Coding has become a slippery squiril so to speak..
Quite often floats in Vector code end up being translated from and to integer over and over,
The transfer of code from and to float is quite in-efficient,
However for example floating point definitions of page layout in PHP can lead to errors in web page layout & cost additional ram & page .php file size (however we do use compressed UTF-8 (GZIP),
Only the final form needs to definitely fit into the finite data set of integer or float ..
For rendering in high definition & VR realities we really need the 64bit precision or even float,
Data saved in integers saves money & resources such as storage..
Conversion of float data into integer & Integer into float takes advantage of resource allocations & we do need to ensure that output pipeline is float on higher than HD displays!
We can allocate OpenCL compatible code to integer units quite easily, But as stated we need clear lines between sets of integer code and float for optimisation reasons.
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https://science.n-helix.com/2018/01/integer-floats-with-remainder-theory.html
https://science.n-helix.com/2020/01/float-hlsl-spir-v-compiler-role.html
https://science.n-helix.com/2016/04/3d-desktop-virtualization.html
https://science.n-helix.com/2017/02/open-gaming.html
Compiler books & reading : https://science.n-helix.com/2017/04/boinc.html
https://www.khronos.org/sycl/
https://llvm.org/
https://gcc.gnu.org/
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