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Comparative Study of Alternative Computing Technologies for Speed and Density

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Comparative Study of Alternative Computing Technologies for Speed and Density Journal of Computing and Information Technology - CIT 11, 2003, 2, 103–110 103 Comparative Study of Alternative Computing Technologies for Speed and Density Tarik Ozkul Computer Engineering Division, American University of Sharjah, Sharjah, UAE As we design faster and denser silicon hardware to in- age, heat dissipation and energy consumption crease computing performance, some limitations started of the chip is likely to limit the number of tran- to appear. It is apparent that these limitations will stifle the growth of performance in the near future. In order sistors to pack in a chip. As more and more to overcome these limitations, alternative computing transistorsdevices get packed on a chip, the technologies started to emerge. Among many attempts, power consumption and heat generated will in- biological computing, DNA computing, quantum com- crease. Even if more efficient technologies can puting and optical computing emerged as promising technologies. In this present paper we give state of the be developed to reduce the power consump- art of alternative computing technologies and compare tion and increase the packing density to 1017 them from the viewpoint of speed and density and classify logic devices in a cubic centimeter, theoretical the type of problems they can help to solve. The driving force behind the search for alternative technologies and power consumption of such a device will be the major trends are also explained. enormously high 2,3 . According to the under- lying physics, an ideal conventional device must Keywords: DNA computing, biological computing, dissipate at least ln2 x kT joules in switching; whole cell computing, quantum computing, reversible computing, optical computing, high performance com- so an ideal device packing 1017 transistors, op- puting. erating at room temperature at a frequency of 10 gigahertz, would dissipate > 3,000,000 watts: ln2 xkTatT 300 Kelvin 1. Introduction 17 21 9 10 X3X10 X10X10 3 000 000 watts In accordance with the Moors law, the den- Performances of the actual conventional devices sity of IC chips keep increasing at a steady seem to be much lower than the ideal theoretical rate. So far the rule has worked very well figures given above 4 . With the current tech- and it seems that, using better photolithographic nology 55x106 transistor count Pentium IV chip tools, we can keep reducing the size of the operating at 2 Ghz consumes about 60 watts of IC chips. As of 2002, some IC manufac- power. With this type of energy consumption turers have started using 193 nm ultraviolet rate – which is far from ideal – any device with light for deep-ultraviolet lithography to manu- 1017 transistor count will be consuming around facture very dense microchips. Some manufac- 160,000,000 watts. Obviously, with this type turers have been developing extreme ultraviolet of energy consumption it makes no sense to in- lithography EUV which will utilize 13 nm crease the transistor count any more. light wavelength. With this technology it is ex- These requirements started pushing researchers pected to have the ability to print 40 atom wide toward alternative computing technologies transistors on silicon chip 1 . which consumes much less power yet in can Even though it will be physically possible to be very dense. In this paper we will be review- pack more and more transistors on a VLSI pack- ing several alternative computing technologies 104 Comparative Study of Alternative Computing Technologies for Speed and Density which may change the shape of computing in we have noticed that biological systems are far the near future. more efficient and compact than anything that is humanly engineered. As an example, a single cell of Escherichia coli bacteria with a diameter 2. Basic Requirements from Alternative of 1 micrometer has a digital storage capacity Computing Technologies of a high density floppy disk. When we look at biological systems at nanoscale, it is possible Traditional digital computing architecture uses to find analogues of all engineering tools that logic gates for decision making. Extending the we use; programmable control systems, wires, same concept to the alternative technologies, we shafts and even motors 5 . can state the following are the requirements for In order for any system to perform computing any technology to be used for computing. function it should have the ability to select a path exercising its decision. In a traditional comput- 1 Should have a mechanism for decision mak- ing. ing device this function is performed by logic gates. Event though a logic gate performs a very 2 Should be able to pack large quantities of simple function, collection of these simple gates decision making devices in a small physical can perform very complex tasks as computing space, machines. Biological sensing and computing using nucleic acids, enzymes and whole cells 3 Should have reasonable power consumption. are successfully tried recently 6,7 . It is known The following technologies satisfy the above that individual cells can perform very complex conditions and seem promising as alternative tasks such as searching for nutrients. computing technologies. There are two major trends for biological com- puting. One of the trends uses DNA, which 3. Alternative Technologies is the information storage element available in every cell, for computing purposes. The other trend uses biological cells as a whole to perform Currently, there are three different technologies computational operations. emerging as promising competitors to become the mainstream technology of the future com- DNA Computing puting, promising to meet the requirements of high density, high performance and low power DNA deoxyribonucleic acid is a genetic stor- consumption. All technologies are at their in- age element available in every living cell. DNA fancy and still much work needs to be done be- computing relies on devising algorithms for fore the technology becomes mainstream pro- solving equations using the encoded informa- duction technology. The technologies and the tion stored in DNA. Computing through DNA class of problems they are suitable for are dis- makes use of the following facts 8 . cussed below. A natural DNA strand is a succession of four different building blocks called bases ordered in a specific way. These bases are known as 3.1. Biocomputing Adenine, Guanine, Thymine and Cytosine or as A,G,T and C in short. DNA is made up Biocomputing is emerging as an alternative for of sequences of these bases and the ordering is high density, high performance computing of unique for every living organism. Currently it is computationally difficult problems. Massive possible to synthesize these bases synthetically developments in this area indicate that biocom- in a test tube. puting is indeed possible and may very well be manufactured like the silicon technology in There exists a set of molecular biology tools to the near future. A visionary talk by Richard manipulate DNA strands. These tools are as Feynman in 1959 described the dream of con- follows: structing micro scale computers. It seems that 1. Synthesizing: Building a desired length the dream of Feynman is turning into reality strand using the four different A,G,T and day by day. By observing the nature carefully, C bases. Comparative Study of Alternative Computing Technologies for Speed and Density 105 2. Mixing: Combining different size DNA left over represents the class of solutions to the strands in a test tube. problem posed. 3. Annealing: Bonding together different DNA It should be noted that DNA computing is not sequences. suitable for all types of computing. The class of problems that can be solved by DNA comput- 4. Melting: Breaking double stranded DNA ing effectively are problems that require massive apart into single strands. parallelism and extensive number of trials. A 5. Copying: Making copies of DNA strands. good source for the type of problems suitable for DNA computing is given in 8 . 6. Separating: Separating the strands. Even though the speed of DNA replication itself 7. Extracting: Extracting a pattern of sequence is not very high, massive parallelism of DNA from the whole string. computing makes the overall data processing 8. Cutting: Cutting DNA strands at specific very efficient. The speed of DNA replication is points. 500 base pairs per second. Considering 2 dis- tinct base possibilities for every base, this rate 9. Ligating: Pasting DNA strands together. amounts to 1000 bitssecond processing speed 10. Substituting: Substituting, inserting or delet- in terms of conventional computing terms. As ing a sequence. soon as the replication of a base ends, the fin- ished base starts being replicated as well. So the 11. Detecting: Reading a DNA sequence from number of base pairs replicated increases expo- the solution. nentially. In conventional terms, this means in- creasing processing speed with every iteration. DNA computing is done by generating a DNA As an example, at the 30 th iteration the process- sequence to represent a question and allow- ing speed is 2>30 X 1000 1000 Gbits sec. ing all possible combinations of solutions to be generated by natural replication mechanism of The bases in a DNA are spaced at every 0.35 DNA. After all possible solutions are generated nanometers. According to this, DNA has a lin- in the form of different DNA strings, the class ear data density of 18 Mbitsinch. Extending of solutions which needed to be eliminated are the calculation to two dimensions, assuming a filtered by using the molecular biology tools space of 1 nm between the pairs, data density mentioned above. After elimination, what is becomes 1 million gigabits per square inch. Fig. 1. In an enzymatic transistor effectors control the rate of conversion of substrate into product. 106 Comparative Study of Alternative Computing Technologies for Speed and Density Whole Cell Computing gate generating output light if either one of the inputs TCE or toluene is present.
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