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Tue Jul 13 02:46:31 2010 UTC (10 years, 6 months ago) by jhr
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Tue Jul 13 02:46:31 2010 UTC (10 years, 6 months ago) by jhr
File size: 6173 byte(s)
revising probe document
\documentclass[11pt]{article} \input{defs} \usepackage{graphicx} \usepackage{listings} \lstset{ basicstyle=\ttfamily, keywordstyle=\bfseries, showstringspaces=false, } \lstset{ language=C, } \setlength{\textwidth}{6in} \setlength{\oddsidemargin}{0.25in} \setlength{\evensidemargin}{0.25in} \setlength{\parskip}{5pt} \newcommand{\matM}{\mathbf{M}} \newcommand{\vecx}{\mathbf{x}} \newcommand{\vecp}{\mathbf{p}} \newcommand{\vecn}{\mathbf{n}} \newcommand{\vecf}{\mathbf{f}} \newcommand{\VEC}[1]{\left\langle{#1}\right\rangle} \newcommand{\FLOOR}[1]{\left\lfloor{#1}\right\rfloor} \title{Compiling probe operations for Diderot} \author{ John Reppy \\ University of Chicago \\ {\small\tt{}jhr@cs.uchicago.edu} \\ } \date{\today} \begin{document} \maketitle \thispagestyle{empty} \bibliographystyle{../common/alpha} \bibliography{../common/strings-short,../common/manticore} \section{Introduction} This note describes the code needed to implement a probe of a field operation. In the discussion below, we use $\matM^{-1}$ for the homogeneous matrix that maps from world coordinates to image coordinates and use $\vecx$ for the position vector. \section{Probing a 1D scalar field} The simplest case is probing a 1D scalar field $F = V\circledast{}h$, where $s$ is the support of $h$. The probe $F\mkw{@}x$ is computed as follows: \begin{eqnarray*} \left[\begin{array}{c} x' \\ 1 \end{array}\right] & = & \matM^{-1} \left[\begin{array}{c} x \\ 1 \end{array}\right] \qquad \text{\textit{transform to image space}} \\ n & = & \FLOOR{x'} \qquad \text{\textit{integer part of position}} \\ f & = & x' - f \qquad \text{\textit{fractional part of position}} \\ F\mkw{@}x & = & \sum_{i=1-s}^s {V(n+i) h(f - i)} \end{eqnarray*}% The convolution $h$ is represented as a symmetric piecewise polynomial formed from $s$ polynomials $h_1,\,\ldots,\,h_s$. \begin{displaymath} h(x) = \left\{\begin{array}{ll} 0 & \text{$x < -s$} \\ h_i(-x) & \text{$-s \leq -i \leq x < 1-i \leq 0$} \\ h_i(x) & \text{$0 < i-1 \leq x < i \leq s$} \\ 0 & \text{$x > s$} \\ \end{array}\right. \end{displaymath}% Thus, we can rewrite the probe computation as \begin{displaymath} F\mkw{@}x = \sum_{i=1-s}^{0} {V(n+i) h_{1-i}(i - f)} + \sum_{i=1}^s {V(n+i) h_i(f - i)} \end{displaymath}% \figref{fig:1d-probe} illustrates the situation for a kernel $h$ with support $s = 2$, and \figref{fig:1d-probe-code} gives the C code for the probe operation, assuming that $h$ is represented by third-degree polynomials. \begin{figure}[t] \begin{center} \includegraphics[scale=0.8]{pictures/convo} \end{center}% \caption{1D scalar probe} \label{fig:1d-probe} \end{figure}% \begin{figure}[t] \begin{quote} \begin{lstlisting} double img[]; // image data double h1[4], h2[4]; // kernel double probe (double x) { double imgX = transform(x); // image-space position double n, f; f = modf (imgPos, &n); double value = 0.0, x; w = -1.0 - f; value += img[n-1] * (h2[0] + w*(h2[1] + w*(h2[2] + w*h2[3]))); w = -f; value += img[n] * (h1[0] + w*(h1[1] + w*(h1[2] + w*h1[3]))); w = f - 1.0; value += img[n+1] * (h1[0] + w*(h1[1] + w*(h1[2] + w*h1[3]))); w = f - 2.0; value += img[n+2] * (h2[0] + w*(h2[1] + w*(h2[2] + w*h2[3]))); return value; } \end{lstlisting}% \end{quote}% \caption{Computing $F\mkw{@}x$ for a 1D scalar field in C} \label{fig:1d-probe-code} \end{figure} \begin{figure}[t] \begin{quote} \begin{lstlisting} double4 d = (double4)(h2[0], h1[0], h1[0], h2[0]); // x^0 coeffs double4 c = (double4)(h2[1], h1[1], h1[1], h2[1]); // x^1 coeffs double4 b = (double4)(h2[2], h1[2], h1[2], h2[2]); // x^2 coeffs double4 a = (double4)(h2[3], h1[3], h1[3], h2[3]); // x^3 coeffs double probe (double x) { double imgX = transform(x); // image-space position double n, f; f = modf (imgPos, &n); double4 v = (double4)(img[n-1], img[n], img[n+1], img[n+2]); double4 w = (double4)(-1.0 - f, -f, f - 1.0, f - 2.0); return dot(v, d + w*(c + w*(b + w*a))); } \end{lstlisting}% \end{quote}% \caption{Computing $F\mkw{@}x$ for a 1D scalar field in OpenCL} \label{fig:1d-probe-code-opencl} \end{figure} \section{Probing a 3D scalar field} The more common case is when the field is a convolution of a scalar 3-dimensional field ($F = V\circledast{}h$). Let $s$ be the support of $h$. Then the probe $F\mkw{@}\vecp$ is computed as follows: \begin{eqnarray*} \vecx & = & \matM^{-1} \vecp \qquad \text{\textit{transform to image space}} \\ \vecn & = & \FLOOR{\vecx} \qquad \text{\textit{integer part of position}} \\ \vecf & = & \vecx - \vecn \qquad \text{\textit{fractional part of position}} \\ F\mkw{@}\vecp & = & \sum_{i=1-s}^s {\sum_{j=1-s}^s {\sum_{k=1-s}^s {V(\vecn+\VEC{i,j,k}) h(\vecf_x - i) h(\vecf_y - j) h(\vecf_z - k)}}} \end{eqnarray*}% \begin{figure}[t] \begin{quote} \begin{lstlisting} typedef double vec3[3]; typedef struct { int degree; double coeff[]; } polynomial; typedef struct { int support; polynomial *segments[]; } kernel; double probe (vec3 ***img, kernel *h, vec3 pos) { } \end{lstlisting}% \end{quote}% \caption{Computing $F\mkw{@}\vecx$ for a 3D scalar field in C} \end{figure} \section{Probing a 3D derivative field} We next consider the case of probing the derivative of a scalar field $F = V\circledast{}h$, where $s$ is the support of $h$. The probe $(\mkw{D}\;F)\mkw{@}\vecp$ produces a vector result as follows: \begin{eqnarray*} \vecx & = & \matM^{-1} \vecp \qquad \text{\textit{transform to image space}} \\ \vecn & = & \FLOOR{\vecx} \qquad \text{\textit{integer part of position}} \\ \vecf & = & \vecx - \vecn \qquad \text{\textit{fractional part of position}} \\ (\mkw{D}\;F)\mkw{@}\vecp & = & \left[\begin{array}{c} \sum_{i=1-s}^s {\sum_{j=1-s}^s {\sum_{k=1-s}^s {V(\vecn+\VEC{i,j,k}) h'(\vecf_x - i) h(\vecf_y - j) h(\vecf_z - k)}}} \\ \sum_{i=1-s}^s {\sum_{j=1-s}^s {\sum_{k=1-s}^s {V(\vecn+\VEC{i,j,k}) h(\vecf_x - i) h'(\vecf_y - j) h(\vecf_z - k)}}} \\ \sum_{i=1-s}^s {\sum_{j=1-s}^s {\sum_{k=1-s}^s {V(\vecn+\VEC{i,j,k}) h(\vecf_x - i) h(\vecf_y - j) h'(\vecf_z - k)}}} \\ \end{array}\right] \end{eqnarray*}% \end{document}
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