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mwd code and figs

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Nam Tran
2019-11-18 10:29:19 -06:00
parent 238119d740
commit 3badc8392e
3 changed files with 169 additions and 33 deletions
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mwd_gpu/mwdGpu.tex
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@@ -5,48 +5,27 @@
\usepackage{textcomp}
\usepackage{epsfig}
\usepackage{hyperref}
\usepackage{hyphenat}
\usepackage[noabbrev, capitalize]{cleveref} % hyperref must be loaded first
\usepackage[
detect-weight=true,
per=slash,
detect-family=true,
separate-uncertainty=true]{siunitx}
% \usepackage{listings}
detect-weight=true,
per=slash,
detect-family=true,
separate-uncertainty=true]{siunitx}
\usepackage[dvipsnames]{xcolor}
\usepackage{upquote}
\usepackage[framemethod=tikz]{mdframed}
\usepackage{adjustbox}
% \definecolor{greybg}{rgb}{0.25,0.25,0.25}
% \definecolor{yellowbg}{rgb}{0.91, 0.84, 0.42}
% \definecolor{bananamania}{rgb}{0.98, 0.91, 0.71}
\mdfdefinestyle{warning}{%
linecolor=red!70,
frametitle={Warning},
frametitlerule=true,
frametitlebackgroundcolor=orange!40,
backgroundcolor=orange!30,
innertopmargin=\topskip,
roundcorner=8pt,
linewidth=1pt,
\usepackage{listings}
\usepackage{xparse}
\NewDocumentCommand{\codeword}{v}{%
\texttt{\textcolor{blue}{#1}}%
}
% \mdtheorem[style=theoremstyle]{warning}{Warning}
\lstset{language=C++,keywordstyle={\bfseries \color{blue}}}
\mdfdefinestyle{listing}{%
linecolor=Aquamarine!50,
linewidth=1pt,
backgroundcolor=yellow!40,
roundcorner=8pt,
% frametitlerule=true,
% frametitlebackgroundcolor=yellow!50,
innertopmargin=\topskip,
}
% \mdtheorem[style=listing]{listing}{Listing}
% \DeclareSIUnit\eVperc{\eV\per\clight}
% \DeclareSIUnit\clight{\text{\ensuremath{c}}}
\usepackage{forest}
\begin{document}
\title{Moving window decomposition implementation using GPU}
@@ -54,4 +33,161 @@
\date{\today}
\maketitle
\section{Introduction}%
\label{sec:introduction}
The purpose of this work is assessing the feasibility and performance of using
GPU to process raw waveforms from a HPGe detector. Expected result of the MWD
algorithm is shown in \cref{fig:mwdInputOutput}. The input is a
\num{250000}-sample long waveform taken at the preamplifier output of the HPGe
detector. The MWD algorithm transforms each jump in the input waveform into a
flat-top peak, of which height is proportional to charge deposited in the
detector.
\begin{figure}[tbp]
\centering
\includegraphics[width=0.90\linewidth]{figs/mwdInputOutput}
\caption{MWD algorithm: input waveform on the left, and expected output on
the right.}%
\label{fig:mwdInputOutput}
\end{figure}
\section{Set up}%
\label{sec:set_up}
\subsection{Hardware}%
\label{sub:hardware}
There are two consumer computers used in this study:
\begin{itemize}
\item PC 1\@:
\begin{itemize}
\item CPU\@: AMD Ryzen 5 2400G, running at \SI{3.60}{\giga\hertz},
maximum frequency \SI{3.90}{\giga\hertz}
\item GPU\@: GeForce GTX 1060, DDR5 memory \SI{6}{GB},
maximum frequency \SI{1.70}{\giga\hertz}
\end{itemize}
\item PC 2\@:
\begin{itemize}
\item CPU\@: Intel Core i5\hyp{}4590 CPU, running at \SI{3.30}{\giga\hertz},
maximum frequency \SI{3.70}{\giga\hertz}
\item GPU\@: GeForce GTX 1650, DDR5 memory \SI{4}{GB},
maximum frequency \SI{1.70}{\giga\hertz}
\end{itemize}
\end{itemize}
\subsection{Software}%
\label{sub:software}
The computers run two different versions of Linux:
\begin{itemize}
\item PC 1\@: CentOS 7.2
\begin{itemize}
\item gcc
\item CUDA
\end{itemize}
\item PC 2\@: Debian 10.2
\begin{itemize}
\item gcc (Debian 8.3.0\hyp{}6) 8.3.0
\item nvcc V9.2.148, CUDA 10.1, driver version 418.74
\end{itemize}
\end{itemize}
\section{Implementations}%
\label{sec:implementations}
There are two implementations of the MWD algorithm:
\begin{itemize}
\item C++ implementation which does all calculations on the CPU. This will be
used to verify the accuracy of the other code, as well as a benchmark
\item CUDA implementation: offloads the digital pule processing part on to
the GPU, CPU only handles input/output related tasks
\end{itemize}
\subsection{C++ code}%
\label{sub:c_code}
This implementation uses raw array wrapped in a \codeword{struct} to represent
waveforms, pointers are managed manually. There are 3 methods
\codeword{Deconvolute}, \codeword{OffsetDifferentiate}, and
\codeword{MovingAverage} corresponds to 3 stages of the MWD algorithm.
The related files are:
\begin{forest}
for tree={
font=\ttfamily,
grow'=0,
child anchor=west,
parent anchor=south,
anchor=west,
calign=first,
edge path={
\noexpand\path [draw, \forestoption{edge}]
(!u.south west) +(7.5pt,0) |- node[fill,inner sep=1.25pt] {} (.child anchor)\forestoption{edge label};
},
before typesetting nodes={
if n=1
{insert before={[,phantom]}}
{}
},
fit=band,
before computing xy={l=15pt},
}
[mwd
[mwd.c]
[srcs
[vector.h]
[vector.c]
[algo.h]
[algo.c]
]
]
\end{forest}
\subsection{CUDA code}%
\label{sub:cuda_code}
The CUDA code implements 3 GPU functions \codeword{gpuDeconvolute},
\codeword{gpuOffsetDifferentiate}, and \codeword{gpuMovingAverage} which
replace 3 C++ methods in the other implementation. There are also helpers for
moving data between main memory and GPU memory, error checking and time
keeping. The I/O part is the same as in the C++ version.
Related files are:
\begin{forest}
for tree={
font=\ttfamily,
grow'=0,
child anchor=west,
parent anchor=south,
anchor=west,
calign=first,
edge path={
\noexpand\path [draw, \forestoption{edge}]
(!u.south west) +(7.5pt,0) |- node[fill,inner sep=1.25pt] {} (.child anchor)\forestoption{edge label};
},
before typesetting nodes={
if n=1
{insert before={[,phantom]}}
{}
},
fit=band,
before computing xy={l=15pt},
}
[mwd
[gmwd.cu]
[srcs
[gpuAlgo.cu]
[gpuAlgo.h]
[gpuTimer.h]
[gpuUtils.h]
[prefixScan.cu]
[prefixScan.h]
]
]
\end{forest}
\section{Results}%
\label{sec:results}
\section{Code}%
\label{sec:code}
A tarball of the code is attached as \codeword{mwd.tar.gz}
\end{document}