Daniel
c62aff806a
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37 lines
1.2 KiB
TeX
37 lines
1.2 KiB
TeX
\chapter{Implementation}
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\label{cha:implementation}
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somewhere in here explain why one kernel per expression and not one kernel for all expressions
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Go into the details why this implementation is tuned towards performance and should be the optimum at that
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\section{Technologies}
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Short section; CUDA, PTX, Julia, CUDA.jl
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Probably reference the performance evaluation papers for Julia and CUDA.jl
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\section{Expression Processing}
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Talk about why this needs to be done and how it is done (the why is basically: simplifies evaluation/transpilation process; the how is in ExpressionProcessing.jl)
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\section{Interpreter}
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Talk about how the interpreter has been developed.
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UML-Ablaufdiagram
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main loop; kernel transpiled by CUDA.jl into PTX and then executed
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Memory access (currently global memory only)
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no dynamic memory allocation like on CPU (stack needs to have fixed size)
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\section{Transpiler}
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Talk about how the transpiler has been developed (probably largest section, because it just has more interesting parts)
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UML-Ablaufdiagram
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Front-End and Back-End
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Caching of back-end results
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PTX code generated and compiled using CUDA.jl (so basically the driver) and then executed
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Memory access (global memory and register management especially register management)
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