-on spline interpolation (see below). It also computes the coefficient
-used for unwrapping the phase. The second one is the acquisition loop,
-while which images are taken at regular time steps. For each image,
-the phase $\theta$ of all profiles is computed to obtain, after
-unwrapping, the deflection of cantilevers.
-
-This phase computation is obviously the bottle-neck of the whole
-process. For example, if we consider the camera actually in use, an
-exposition time of 2.5ms for $1024\times 1204$ pixels seems the
-minimum that can be reached. For a $10\times 10$ cantilever array, if
-we neglect the time to extract pixels, it implies that computing the
-deflection of a single cantilever should take less than 25$µ$s, which is
-quite small.
+on spline interpolation (see section \ref{algo-spline}). It also
+computes the coefficient used for unwrapping the phase. The second one
+is the acquisition loop, while which images are taken at regular time
+steps. For each image, the phase $\theta$ of all profiles is computed
+to obtain, after unwrapping, the deflection of cantilevers.
+
+\subsection{Design goals}
+\label{sec:goals}
+
+If we put aside some hardware issues like the speed of the link
+between the camera and the computation unit, the time to deserialize
+pixels and to store them in memory, ... the phase computation is
+obviously the bottle-neck of the whole process. For example, if we
+consider the camera actually in use, an exposition time of 2.5ms for
+$1024\times 1204$ pixels seems the minimum that can be reached. For a
+$10\times 10$ cantilever array, if we neglect the time to extract
+pixels, it implies that computing the deflection of a single
+cantilever should take less than 25$\mu$s, thus 12.5$\mu$s by phase.\\
+
+In fact, this timing is a very hard constraint. Let consider a very
+small programm that initializes twenty million of doubles in memory
+and then does 1000000 cumulated sums on 20 contiguous values
+(experimental profiles have about this size). On an intel Core 2 Duo
+E6650 at 2.33GHz, this program reaches an average of 155Mflops. It
+implies that the phase computation algorithm should not take more than
+$240\times 12.5 = 1937$ floating operations. For integers, it gives
+$3000$ operations.
+
+%% to be continued ...
+
+%% � faire : timing de l'algo spline en C avec atan et tout le bordel.
+
+
+
+
+\section{Proposed solution}
+\label{sec:solus}
+
+
+\subsection{FPGA constraints}
+
+A field-programmable gate array (FPGA) is an integrated circuit designed to be
+configured by the customer. A hardware description language (HDL) is used to
+configure a FPGA. FGPAs are composed of programmable logic components, called
+logic blocks. These blocks can be configured to perform simple (AND, XOR, ...)
+or complex combinational functions. Logic blocks are interconnected by
+reconfigurable links. Modern FPGAs contains memory elements and multipliers
+which enables to simplify the design and increase the speed. As the most complex
+operation operation on FGPAs is the multiplier, design of FGPAs should not used
+complex operations. For example, a divider is not an available operation and it
+should be programmed using simple components.
+
+FGPAs programming is very different from classic processors programming. When
+logic block are programmed and linked to performed an operation, they cannot be
+reused anymore. FPGA are cadenced slowly than classic processors but they can
+performed pipelined as well as pipelined operations. A pipeline provides a way
+manipulate data quickly since at each clock top to handle a new data. However,
+using a pipeline consomes more logics and components since they are not
+reusable, nevertheless it is probably the most efficient technique on FPGA.
+Parallel operations can be used in order to manipulate several data
+simultaneously. When it is possible, using a pipeline is a good solution to
+manipulate new data at each clock top and using parallelism to handle
+simultaneously several data streams.
+
+%% contraintes imposées par le FPGA : algo pipeline/parallele, pas d'op math complexe, ...
+
