AUTOMATED SYNTHESIS OF INTEGRATED CIRCUITS FOR VISION
Georges
QUÉNOT, Ivan KRALJIC*, Bertrand ZAVIDOVIQUE**
Object: The purpose of this research is to develop tools
allowing fast and automatic generation of integrated circuits (or chip
sets) dedicated to implement, on demand and in a compact and economic
way, real time vision systems. This work is carried out in cooperation
with the Perception System
Laboratory from the DGA/ETCA (PhD thesis Ivan Kraljic) as part of their
Data-Flow
Functional Computer project.
Content: The chosen approach is called emulation / derivation.
It is articulated around the Data-Flow Functional Computer which is a
massively parallel data-flow machine (1024 processors within an 8 x 8 x 16
cubic mesh network) that processes on the fly and in real time digital
video streams and which is programmed using a functional language (FP-like).
The data-flow execution mode has been chosen because it fits very well
the emulation / derivation approach.
During the emulation phase, the user may develop and debug its applications
on the Data-Flow Functional Computer in an interactive way and in real
conditions. He writes a program in a functional language tailored to the
architecture: every primitive function of this language corresponds to an
operator implementable on a processor and every functional form
(composition, construction) corresponds to a combination of operators
(serial, parallel) as a data-flow graph. Figure 1 shows a very simple edge
point detector example. The D(n,p) operator is parameterizable and provides
as output a pixel flow shifted by n lines and p columns relatively to its
input flow. The THR(v) operator performs a thresholding relatively to
a parameter. The SUB, ABS and MAX operators perform simple arithmetic
operations on data-flows. Figure 2 shows the corresponding operator
data-flow graph and Figure 3 shows how such a graph may be placed and
routed over a network of data-flow processors. Figure 4 shows the Data-Flow
Functional Computer physical implementation. Figure 5 shows the emulation
result as it can be seen in real-time on the monitors of the Data-Flow
Functional Computer for a more complex application (defect detector within
a regular texture).
The derivation consists in extracting a VLSI circuit description from an
application emulated on the Data-Flow Functional Computer. The data-flow
/ functional approach guarantees that is is possible and efficiently
feasible. The circuit description is a netlist of electronic components.
A description is obtained for every used operator by simplifying the
data-flow processor's one while taking into account the actually used
resources. These descriptions are then merged according to the operator
graph. Figure 6 shows a two-chip set that implements the emulated defect
detector.
Situation: Current studies aim at improving the performance
and generality of the tools in order to be able to handle more important
and more various applications. New vision applications are also being
developped.
Figures (postscript, 1574105 bytes).
References
(1) De la programmation fonctionnelle au traitement d'images temps
réel, Jocelyn S. Sérot, Georges M. Quénot et
Bertrand Zavidovique,. Technique et Science Informatiques 14(7),
pp 839-865, Sept. 1995.
Résumé,
Abstract.
(2)
Retargeting Field-Programmable Operator Arrays, [2431109 bytes]
Ivan C. Kraljic, Georges M. Quénot and Bertrand Zavidovique,
Third Canadian Workshop on Field-Programmable Devices, Montreal, Quebec,
May 1995. Abstract.
(3)
From Real-Time Emulation to ASIC Integration for Image Processing
Applications, [424814 bytes]
Ivan C. Kraljic, Georges M. Quénot and Bertrand Zavidovique,
8th Annual IEEE Intl. ASIC Conference, Austin, Texas, 18-22 September 1995.
Abstract.
(4) High level synthesis by systematic derivation of vision automata from
emulation results, Ivan C. Kraljic, Georges M. Quénot and Bertrand
Zavidovique, In G. Saucier and A. Mignotte, editors, Logic and
Architecture Synthesis: State of the Art and Novell Approaches, pages 300-306.
Chapman & Halll, 1995. Abstract.
(5)
Expérimentation en Architecture de Machines pour la Perception,
[13108816 octets],
version compressée gzip [4515409 octets],
Georges M. Quénot,
Habilitation à Diriger des Recherches, LIMSI, Orsay,
18 novembre 1998.
* Laboratoire Système de Perception, DGA/ETCA
** Institut d'Électronique Fondamentale, Université d'Orsay Paris XI