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http://www.lab.analogic.sztaki.hu/index. ABSTRACT: A portable programmable opto-electronic analogic. CNN computer (Laptop-POAC) has been built. Its kernel ...
Laptop POAC: a Compact Optical Implementation of CNN-UM Szabolcs Tőkés, László Orzó, Ahmed Ayoub, Tamás Roska Analogical and Neural Computing Laboratory, Computer and Automation Research Institute, Hungarian Academy of Sciences, H-1111 Kende u. 13-17, Budapest, Hungary, {Tokes, Orzo, Ahmad, Roska}@sztaki.hu http://www.lab.analogic.sztaki.hu/index. ABSTRACT: A portable programmable opto-electronic analogic CNN computer (Laptop-POAC) has been built. Its kernel processor is a novel type of high performance optical correlator based on the use of bacteriorhodopsin (BR) as a dynamic holographic material. This optical CNN implementation combines the optical computer's high speed, high parallelism and large applicable template size with the flexible programmability of the CNN devices. Unique feature of this optical array computer that the programming templates can be applied either by a 2D acousto-optical deflector (up to 32x32 pixel size templates) incoherently or by an LCD-SLM (up to 128x128 size templates) coherently. Input images are fed-in by a second LCD-SLM of 600x800 pixel resolution.

1

Introduction

The CNN and later the CNN-UM architecture provides a simple and extremely efficient design and programming frame among the existing parallel VLSI architectures [1,2,3]. A lot of efforts had been done to implement CNN with optical hardware [4,5,6], because optical computing and primarily optical correlator architectures offer extremely high parallelism, and this way an outstanding speed [7]. On the other hand, in the case of existing optical correlator architectures flexible programmability is hard to be solved, due to the fact that they are mainly based on the application of pre-calculated matched filters (VanderLugt) [7]. The CNN paradigm grants a programming frame for the optical correlators, while the optical architecture extend the VLSI based CNN-UM implementations' resolution and template size limits. An optical correlator itself can be regarded as a feed forward only CNN. To combine the advantages of the VLSI CNN architectures – stored programmability, local memories, feedback, nonlinear output functions and high-speed on chip adaptive sensors (etc.) – with that of the optical implementation – big templates, high resolution input images - we introduced the so-called Programmable Opto-electronic Analogic CNN computer architecture (POAC) [8]. This architecture applies a novel type of optical correlator architecture (t2-JTC) [9], which provide flexible programmability, while preserving the high speed and optimize the available laser power and other resources (see later) [10].

2

Motivations

In the frame of the present project our goal is to construct a compact portable version of our earlier optical correlators developed for optical CNN implementation [8]. We intend to apply it in diverse image processing and target tracking tasks. Building such prototype system help

us to gain further optical and system design experiences. Furthermore, this new model helps us to enhance the system performance and test its inherent capabilities (including nonlinear feedback possibilities). The assembled prototype system makes it possible to test the so far developed POAC and optical CNN templates and algorithms [11] and to work out further practical and commercial applications. We are focusing our efforts to three main application fields: optical document security; adaptive target tracking (single and multi object detection and tracking) and collision avoidance.

3

The Laptop-POAC Architecture

3.1 System architecture of POAC The POAC system includes an optical correlator as a kernel processor. Although, the system speed is based primarily on this optical CNN implementation, it needs a conventional computer to control the different parts and devices. This control ensures the required input, measures outputs and displays the results. The next figure summarizes what kinds of tasks have to be solved. Displaying results (output) Microdisplay (input) Microdisplay (template) Control and Timing Camera (input) Camera (output) AOD control (template) Lasers controls

Figure 1.Schematic view of the POAC control. 3.2

The optical architecture of t2-JTC

Bacteriorhodopsin films as a recyclable dynamic holographic medium plays essential roles in all of our correlator solutions [12]. Both Bragg and Lippmann-Denisyuk type architectures have been built and successfully tested. However, as here we utilize two different wavelengths for recording and reading the holograms [13], Bragg-holograms are proven to be more appropriate, having less wavelength selectivity. Even in the case of Bragg-type, thick holograms it is important to choose a proper thickness of holographic medium. Two main aspects have to govern this choice. On the one hand, diffraction efficiency grows with the increasing thickness. On the other hand, thicker holograms have narrower angular (and color) selectivity that limits the angular size both of the input image and that of the templates, as well. The optimum thickness lies in the Raman-Nath region. In our case it is found to be about 40 µm. One of the main advantages of the two-wavelength correlator [13] is based on the recyclable light sensitivity of BR. For any computing application the optical correlator has to work in cycles: hologram writing, reading (usually multiply reading is required to correlate

different templates on the same input image), - and erasing. In the case of BR there are two different way to erase the recorded hologram. In the first method we illuminate the BR film with deep blue light to drive back the material from M-states to BR-states (see the photocycle of Bacteriorhodopsin [14]). According to our experiment this method appears to be to be not satisfactory enough. So, another method has been chosen where the thermal decay time is set to match the frame-rate of the hologram recording what depends on the changing rate of the input image. The thermal decay time can be modified either by genetic manipulation of the archea bacteria (Halobacterium Halobium) to produce modified bacteriorhodopsin protein or by appropriate physical and/or chemical treatment. This way the frame-rate can be adjusted to the application's special requirements. 3.3 Object-arm architecture For reliable hologram recording a stable rigid opto-mechanical structure is required. In a laptop size device it can be satisfied much more easily than in the case of our earlier breadboard model systems. The reference and object beam path lengths have to be equalized to be within the coherence length of the frequency doubled YAG laser. This way a less costly laser source can be used and the quality of the recorded hologram improves considerably. Appropriate polarization of the different beams has to be set according to the applied liquid crystal micro-displays' characteristics. Finally, the in this optical arrangement the objective lens serves both as a Fourier lens and as an imaging lens. So, it has to satisfy a series of rather contradicting requirements. Filter

CCD or CNN Camera

BR

Fourier optic Lens

Dichroic Mirror

Mirror Beam Expander

Green Laser

Microdisplay

Mirror

Polarizer

Template Beam

Polarization Beam Splitter

Polarization Rotator

Mirror 5 Beam splitter

Polarization rotator

Beam Expander

Figure 2. Object (hologram recording) arm architecture of the laptop POAC system. Appropriate beam attenuation, expansion and path lengths are set in both image and reference paths to assure the high quality dynamic hologram recording into the Bacteriorhodopsin film. Read out (template path) beams are denoted by dashed lines. Before the sensor (CNN VLSI chip or CCD camera) an appropriate filter cut the green laser of the object path. 3.4 Template-arm architectures Earlier we have developed two different architectures to realize template operations. In this model a combined structure has been built. In the first mode the templates are displayed with a two-dimensional acousto-optic deflector device (AOD), where the template pixels are displayed sequentially, resulting in shifted and weighted holographic reconstructions of the input object's image. The correlation is formed in an incoherent way by adding-up photoelectrons (that are proportional to the image intensities) in the pixels of the camera.

Therefore, this mode of operation requires a time-integrating photo-electronic device (such as CCD). Although, the hologram is reconstructed according to the template pixels in a sequential way, the two dimensional acousto-optical deflector provides high speed even for relatively large template sizes (1000 correlations per second for 30x30 templates, because the physical limit is about 1µsec/template pixel with our TeO2 deflector). In the coherent mode of operation an LCD SLM is used to display the templates. In this case all of the shifted, weighted image pixel amplitudes are reconstructed simultaneously. The complex amplitudes (what include the phase information as well) add-up coherently. This coherent correlation produces higher and sharper peaks, but are considerably sensitive to phase errors. Therefore this mode is very sensitive to the quality and precise alignment of the optical components. To get correlation we have to ensure the same viewing angle both for template and object pixels at the hologram plane (Bacteriorhodopsin film) [10,8]. Due to the simultaneous displaying of template pixels in this mode, only the applied micro display refresh rate limits the achievable frame rate (300Hz in our case). The overall performance of this system is limited by the camera sensitivity and speed of data acquisition. Later we intend to use a high-end camera – current one is a simple web camera – with built-in CNN sensor and processor array (Bi-I system). The modest resolution CNN device will control and process the high-resolution sensor data acquisition. This way we can achieve high speed and avoid the data uploads bottleneck. dichroic mirror

mirror

bacteriorhodopsin

polarization rotator template SLM

polarization rotator mirror

2nd lens of tele and lens of SLM 2D AOD polarizing beamsplitter

red laser red laser 1st lens of telescope

Figure 3 Optical setup of the template arms of LT-POAC 3.5 Opto-mechanical architecture Our earlier breadboard models, due to the size of the used general-purpose optical components, were rather large. By the use of several mirrors we folded the optical system to decrease its size. A newly designed small-size vary-focal lens has replaced the earlier used bulky commercial zoom lens. Thanks to the apt engineering work the system size has been considerably decreased. By the application of different dichroic mirrors and filters the reference and template beams could be collected and a much shorter path-length has been reached. The photograph of the final architecture is shown in the next figure.

Correlation (output) Template (program)

Object (Input)

Figure 4 Photo of the laptop POAC architecture. Red and green lines denote the paths of the laser beams. Input (LCD), programming (AOD or LCD) and output (CCD) devices are also indicated.

4

Conclusions

We have designed and built a portable, laptop size optical CNN implementation, which is based on a new type of optical correlator architecture and outperform all the so far published and implemented optical antecedents. This device incorporates both coherent and incoherent correlator solutions, to utilize the actual advantages of the used mode of operation. The sturdy, fix structure makes it easier to develop new applications and improve the system performance. This device is able to perform one Tera operation per second. Depending on the application further simplification of the correlator structure is achievable, that can decrease the size and cost of the current prototype system. Incorporating a special CNN as a sensor and post and pre- processing unit, will enhance the current CNN implementation performance considerably. Measurement results will be shown. Two applications (document security and target tracking) are being developed.

Acknowledgements This research was supported by the Computer and Automation Research Institute of the Hungarian Academy of Sciences (SZTAKI) and Hungarian Scientific Research Found Grant (OTKA) No.: T 043136. In engineering works the help of Gabor Sass is highly appreciated. George Váró in the Biophysical Research Institute, at Szeged prepared the BR samples.

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