The worldâ„¢s most advanced super computer doesnâ„¢t require a single semiconductor chip.
The human brain consists of organic molecules that combines to form a highly sophisticated network able to calculate, perceive, manipulate, self-repair, think and feel. Digital computers can certainly perform calculations much faster and more precisely than humans, but even simple organisms are superior to computers in the other five domains. Computer designers may never be able to make machines having all the facilities of natural brain,but we can exploit some special properties of biological molecular-particularly proteins-to build computer components that are faster ,smaller and more powerful than any electronic devices .
Devices fabricated from biological molecules promise compact size and faster data storage. They lead themselves to use in parallel processing computers,3Dmemories and neural networks.
As the trend towards miniaturization continues, the cost of manufacturing a chip increases considerably. On the other hand ,the use of biological molecules as the active components in a computer circuitry may offer an alternative approach that is more economical.
Molecular electronics is an emerging field that lies at the interface of chemical physics, electrical engineering and solid state science. It involves encoding, manipulation and retrieval of information at the macromolecular level in contrast to current techniques which are fast approaching their practical limits.
Molecular electronics provides new methodologies for high speed signal processing, holographic associate memories and 3D optical memories. Molecular devices are reliable and competitive with semiconductor devices when monomolecular state assignment averaging can be implemented. Biomolecular electronics offers significant promise in addressing some of the inherent limitations of semiconductor architecture.
Is a computer based on the dynamics of bio molecular activities rather than on electronic switching. By exploiting some special properties of biological molecules, particularly proteins, components that are smaller, faster and more powerful than any electronic device can be made to function.
Since 1960â„¢s the computer industry has been compelled to make the individual components on semiconductor chips smaller and smaller inorder to manufacture large memories and more powerful processors economically. These chips consists of array of switches, usually of the kind known as logical gates that flip between two states-0 or 1 in response to electric current passing through them. If the trends toward miniaturization continues, the size of single logic gate will approach the size of molecules in the year 2030.
A serious roadblock to miniaturization is the increase in cost of manufacturing a chip. At some point the search for even smaller electronic devices may be limited by economics rather than physics. So the use of biological molecules as the active components in computer circuitry may offer an alternative approach that is more economical.
Molecules can potentially serve as computers switches because their atoms are mobile and change position in a predictable way. If we can direct the atomic motion and thereby constantly generate two discrete states in a molecule, we can use each state to represent either 0 or 1.This results in reduction of size, that is, a biomolecular computer in principle is one-fifth of the size of the present day semiconductor computer. This theoretically makes it thousand times modern computers.
Researchers have introduced parallel processing architecture which allows multiple rows of data to be manipulated simultaneously. In order to expand memory capacities, they are devising hardware that stores data in 3D instead of usual ways. So scientists have built nueral networks that mimic the leasing by association capabilities of the brain. The ability of creating proteins to change their properties in response to light should simplify the hardware required for its implementations.
Although no computer components made from proteins are in the market yet, ongoing international research efforts are making enticing headway. Several molecules are under consideration for the use in computers. Bacteriorhodopsin has generated the most interest.
ORIGIN IN SALT MARSH
Bacteriorhodopsin is a light harvesting protein in the purple membrane of a micro organism called Halobacterium halobium .Bacterior-hodopsin , the bacterial protein , is the basic unit of protein memory and is the key protein in Halobacterial photosynthesis .It functions like a light â€œdriven photo pump. Under exposure to light it transports photons from the halobacterial cell to another medium, changes its mode of operation from photosynthesis to respiration, and converts light energy to chemical energy. The response of this molecule to light energy can be utilised to frame prutein memories.
Bacteriorhodopsin grows in salt marshes ,where temperature can exceed 150 degree F for the extended time period and the salt concentration is approximately six times that of sea water. Survival in such an environment implies that this protein can resist thermal and photochemical damages. Upon absorption of light it generates a chemical and osmotic potential that serves as energy source. It has the ability to form thin films that exhibit excellent optical characteristics and offer long term stability .
Soviet scientists were the first to recognize and develop the potential of the Bacteriorhodopsin sea for computing. Many aspect of this ambitious project are still considered military secrets.
At first interests were on the protein called rhodopsin ,but later were focused on Bacteriorhodopsin because of the greater stability and better optical properties It can be prepared in large quantities also. The application under study for computer processors and the memories on which they operate exploit the photocycle of Bacteriorhopdopsin.
PHOTOCYCLE OF BACTERIORHODOPSIN
Bacteriorhodopsin comprises a light absorbing component known as CHROMOPHORE , that absorbs light energy and triggers a series of complex internal structural changes to alter the proteinâ„¢s optical and electrical characteristics. This phenomenon is known as photocycle.
The sequence of structural changes induced by light as in figure allows for the storage of data in memory. Green light Changes the initial resting state known as Br to the intermediate K.Next K relaxes, forming M and then O. If the O intermediate is exposed to red light, a so called branching section occurs.
O converts to the P state and quickly relaxes to the Q state-a form that remains stable indefinitely. Blue light will however convert Q back to bR .Any two long lasting states can be assigned the binary value 0 or 1,making it possible to store information as a series of bacteriorhodopsin molecules in one state or another.
The intermediates absorb light in different regions of the spectrum. As a consequence, we can read the data by shining laser beams on molecules and noting the wavelengths that donâ„¢t pass through the detector. Since we can alter the structure of bacteriorhodops in with one laser and another laser, we have the needed basis for writing and then reading from memory.
Most devices under study make use of resting state and one intermediate. One state is designated as 0 and other as 1.Switching between the states are controlled by means of laser beams. Most of the early memory devices based on bacteriorhodopsin could operate only at extremely cold temperatures of liquid nitrogen, at which the light induced switching between the initial bR structure and intermediate known as the K could be controlled. These devices were very fast compared with semiconductor switches. But the need for low temperatures precluded general application.
Today most bacteriorhodopsin devices functions at or near room temperature, a condition under which another intermediate M is stable. Although most bR based memory devices incorporate bR â€œ M switch, other structures may actually prove more useful in protein - based computer systems.
INTERCONNECTION FACE BIOMOLECULAR COMPUTING
Over the past two decades VLSI circuit technology has developed rapidly. Unfortunately in complex VLSI systems these increases cause serious interconnection problems in chip area, power consumption and noise. One promising candidate for breaking through these difficulties is the biomolecular computer. The model is based on the specificity of enzymes in their choice of reactants and substrates. They carry information by their presence or absence in solution. At the specified destination, enzyme based biosensors selectively detect the released substrates which automatically triggers a specific biomolecular switch in solution.
The foundation of any computing system is its logic. To support the systematic design of biomolecule computing systems, an algebraic system called set valued logic (SLV),special class of multivalued logic is used. In the SLV concept we use a large number of enzymes and their substrates in our system and the varieties of substrate molecules represent SLV logic states.
Electronic VLSI systems have very effective execution and fast interactive capabilities. Though a biomolecular computer has low data rates, their advantage in natural and massive parallelism. They offer a new parallel processing architecture and bioprocessor executes operations in a data driven manner that makes it possible to exploit the maximum parallelism of a given algorithm.
Logic value 0 logic value 1------------------logic value r-1
Substrate 0 substrate 1---------------------substrate r-1
MODEL OF BIOMOLECULAR SWITCHING DEVICE
Let L be the set of all the substrate that can be transmitted simultaneously in solution. This simultaneous transmission is interpreted algebraically as logic value multiplexing. An enzyme based biosensors can exactly discriminate the molecular information.
In this the concept of MLV to design biodevice networks for interconnection free computation is discussed.The use of more than two levels of logic can reduce the complexity of intergrated circuit interconnection. Practical MLV use continous electrical variables such as voltage,current and change to convey information.
AN ENZYME SUBRATE REACTION
Certain intermediates produced after bacteriorhodopsin initially exposed to light will change to unusual structures when they absorb energy from second laser beam, in a process known as sequential 1-photon architecture. In the photocycle above, a branching section occurs from 0 intermediate to form P and Q. These are generated by two consecutive pulses of laser light-first green and then red. Although P is fairly shortlived, it relaxes to form Q which is stable for extended periods. Because of its extended stability, the Q state has greater significance in search for long term, high density memory.
The intermediate PandQ formedin the sequential 1- photon, are particularly useful for parallel processing. For writing data in parallel our approach incorporates another information-these dimensional data storage. A cube of bacteriorhodops in is surrounded by two arrays of laser beams placed 90 degree from each other. One array of laser, all set to green and called pagging beams, activates the photocycle of proteins in any selected square plane or page within the cube. After a few milliseconds, when the number of 0 intermediates reaches near maximum, the other laser array of red beams is fired.
This second array is programmed to illuminate only the region of activated square where data bits are to be written, switching the molecules to the P structure. T he P intermediate then relaxes. Since the laser array can activate molecules in various places throughout the chosen illuminated page, multiple data locations, known as addressed can be written in parallel.
The system for reading stored memory during processing or during the contraction of result relies on the selective absorption of red light by the 0 intermediate. To read multiple bits of data in parallel ,we start just as we do in the writing process First the green paging beam fire at the square of the protein to be read , starting the normal photocycIe of molecules in bR state. After two milli seconds, the entire laser assay is turned on at a very low intensity of red light .Molecules that are in the binary 1 state do not absorbe these, red molecules that started out in the binary 0 state (bR) do absorbe the beams .The detector reads 0â„¢s and lâ„¢sin terms of the binary code .The process is complete in approximately 10 ms, a rate of 10 megabytes per second for each page of memory
THREE DIMENSIONAL MEMORY
In addition to facilitating parallel processing, 3D cubes of bactrioshodcpsin provides much more space that two dimensional optical memories. Three dimensional optical memories can theoratically approach storage densities of one trillion bits per cubic centimeters .A 300 folds improvement in storage capacity over 2-D devices should be possible .So a major impact of bioelectronics on computer hardware will be in the area of volumatric memory.
Speed is also an important benefit. of volumatric memories. The complication of 3-D storage within the use of parallel architectures enhances the speed of such memories , just a parallel processing in the human brain overcomes relatively slow nueral processor and allows the brain, to be a thinking machine with fast reflexces and rapid decision making capability .If we illuminate a square measuring 1,024 bits by 1,024 bits within a larger tube of protein, we can write 105 KB into memory in a 10 mS cycle. .So it means an overall write speed of 10 million characters per second comparable to slow semiconductor memory.
Associative memories operate rather differently from the memories that dominate current computer architectures .This type of architecture takes a set of data often in the form of an image and scans the entire memory bank until it finds a data set that matches it .Since human brain operates in a nueral associative mode , many computer scientists believe large - capacity associative memories will be required if we are to achieve artificial intelligence.
As associative memory device that relies in the holographic properties of thin films of bacterioshodopsin, holograms allows multiple image to be stored in the same segment of memory, permitting large data sets to be analysed simultaneously. Associative memories have significant potential for applications in optical computer architectures optically coupled nueral network computers etc.
The hyhrid computer we envision would be highly flexible by taking advantage of particular combinations of the memory card described above, large pools of data carry out complex scientific simulations or serve as a unique plate form for investigation of artfical intelligence With above a tetra byte of memory in cubes of bacteriorhodopsin , this machine would handle large data bases with alacrity. Associative memory processing coupled with volumetric memory would make databases searches. Many orders of magnitude faster than is currently possible. Since this hybrid computer can be designed to function as a nueral associative computer capable of learning and analysing data like a human brain, the importance of hybrid computers to studies in artificial intelligence cannot be under estimated.
1. SCIENTIFIC AMERICAN by ROBERT.R.BIRGE
2. THE LOCK KEY PARALDIGM by MICHAEL CONSAD
3. INTERCONNECTION FREE BIOMOLECULAR COMPUTING by TAKAFUNI AOKI,MICHIKITA KAYEMA
4. A BIOLOGICAL MATERIAL FOR INFORMATION PROCESSING by DIETER OESTHERHELT
2. http://www.protein memories.com
ORIGINS IN SALT MARSH
INTERCONNECTION FACE BIOMOLECULAR
MODEL OF A BIOMOLECULAR SWITCHING DEVICE
THREE DIMENSIONAL MEMORY