Wednesday, June 6, 2012

The Future of Computing Technology



    Many experts are saying that silicon is beginning to approach the limits of its usefulness in computing, and that different materials and, eventually, completely different approaches will be needed in order to sustain a steady pace of advancement in computing technology. Here are some of the remarkable alternatives that have been proposed. What do You think the future of computing will be like? Personally, throbbing zombie-worm-like bio-computers capture my imagination.

 

The Future of Computing Technology

-by theGrg
Contents:
Introduction
Optical Computing
Quantum Computing
Biological Computing
Conclusion

 

Introduction

    In 1947, American computer engineer Howard Aiken said that just six electronic digital computers would satisfy the computing needs of the United States. Apparently, Aiken didn't count on the large amounts of data that would be generated by scientific research, the huge spread of personal computers, or the establishment of the Internet, all of which constantly increase our need for more and more computing power.
    According to Moore's Law, the number of transistors that can be placed inexpensively on an integrated circuit doubles approximately every 18 months. Until today, and for more than 40 years, computer chips have been manufactured from silicon, a material that can be easily obtained from sand. But this material will soon reach its useful limits, because its physical limitations are standing in the way. Eventually, in the near future, chip-makers will no longer be able to use silicon to make smaller, faster chips, and if CPUs and memory chips are going to continue to advance, alternatives are needed.
Already, scientists are researching completely different ideas and alternatives that may become the future of computer design, and some of the most remarkable of those alternatives are optical, quantum, and biological computing.


Optical Computing

Description:

    The idea of optical computing is to make a computer that relies completely on light (photons) instead of electricity (electrons) to do the digital computing. One of the main problems of today's processors is that they are producing more and more heat as they become faster, and this heat can be harmful to the hardware.  Light creates much less heat in the same size scale, and travels much faster than electrons, so the development of faster, more powerful processing systems may become possible.

 

Advantages:

  1. Speed: Faster data transfers and computations would be possible because light travels faster than electricity.
  2. Less Heat: Less heat produced by light means that faster data transfer is possible without damaging hardware components.
  3. Size: Optical computers can be smaller than electronic ones because light beams within components can intersect each other without causing interference.

Disadvantages:

  1. Hard to Handle: Trapping, storing and manipulating light is difficult.
  2. Energy Loss: Over very short distances, energy loss by light is actually greater than energy loss by electrons, and large beams of light are necessary to avoid signal loss.
  3. Depend on Material Transistors: An optical computer still depends on material components to achieve computation.

Applications:

    Optics are already used in data communications, and IBM has managed to design an on-chip optical data transmitter that sends 100 times more data between processor cores using 10 times less power than with copper wires (see video). But the application of optics for computing is still experimental. Researchers have already found a way to use a single photon instead of a beam of light to flip a register, which reduces the problem of energy loss, and have been able to make an actual optical transistor with a single molecule, although it requires cooling down to a temperature of -272 degrees C. But scientists predict that many more years of research will still be needed before a practical computer can be made in which photons fully replace electrons.

Quantum Computing

Description:

    Quantum computers are computers that make use of the Quantum Physics of atoms and molecules to perform computations. Within the atom, some aspects like the location of an electron from its nucleus, or the direction of the spin of an electron can be used to represent the 1s and 0s of computers. Also, according to Quantum Physics, a phenomenon called superposition states that at the atomic level, atoms can be in many different states at once, with a probability for being in each state. Using this effect, instead of having electronic bits of information that exist in either 1 or 0 states, quantum computers make use of superposition to create quantum bits that can be in both (1 and 0) states at once. As an example, with a 3-bit system, there are 8 possible combinations. In an ordinary computer, the system can only be in one of those combinations at once. However, a three quantum bit system can be in all 8 states at once because of the superposition principle. So instead of having to process each individual combination at once, a quantum computer can process them all that the same time. This parallelism is what makes quantum computers exponentially faster than a normal computer with every added bit.

 

Advantages:

  1. Can Solve Some Problems With Great Speed: Quantum computers have the potential to perform certain calculations significantly faster than any silicon-based computer –even today's most powerful supercomputers. And with the correct type of algorithm it is possible to use their parallelism to solve some problems in a tiny fraction of the time taken by a classical computer. For example, while a classical computer can take around 10 million billion billion years to factor a 1000-digit number, a quantum computer using a special algorithm can take around 20 minutes.

Disadvantages:

  1. Large Scale Implementation is Difficult: Although scientists have been able to produce small scale prototypes of a few quantum bits, they still do not know how to combine these elements to produce a practical large scale quantum computer. In fact, as the number of quantum bits increases, it becomes even more difficult.
  2. Difficult to Build and Observe: It is tremendously challenging to build and control quantum bits and even more challenging to observe them, meaning that obtaining a solution from a quantum computer can be just as hard as building it.
  3. Specific Applications: A quantum computer will not necessarily outperform a classical computer at all computational tasks, rather only at those tasks for which special algorithms are designed to make use of its quantum parallelism, like cryptography. Multiplication for example would take the same amount of time. So unless a quantum computer with a significant amount of quantum bits can be produced, classical computers will remain superior.

Applications:

    Current cryptography methods rely on the fact that it would take too much time -in some cases longer than the age of the universe, to crack a security key. If a large-scale quantum computer is developed, it would only take a matter of seconds to crack, and no information on the Internet would be secure.
A Canadian company called D-Wave has already produced a 16 quantum bit quantum computer that can solve a Sudoku puzzle and other pattern matching problems, and claims that is now able to produce usable commercial quantum computers.


Biological Computing

Description:

    Millions of natural supercomputers exist inside living organisms, including our bodies. DNA molecules already naturally store and process data and coordinate biological mechanisms that keep organisms alive. In fact, DNA molecules have the potential to perform calculations many times faster than the world's most powerful human-built computers. Thus, biological components like DNA and enzymes may be perfect material for computing. Already, scientists are building basic computer "clocks" and logic gates inside bacteria and using genes to manipulate microorganisms into states that can represent information.

 

Advantages:

  1. Higher Capacity: DNA computers will be capable of storing billions of times more data than a normal computer; only half a kilogram of DNA has the capacity to store more information than all the electronic computers ever built.
  2. More Powerful: The computing power of a teardrop-sized DNA computer, using DNA logic gates, will be more powerful than the world's most powerful supercomputer.
  3. Much Smaller: More than 10 trillion DNA molecules can fit into an area no larger than 1 cubic centimeter. With this small amount of DNA, a computer would be able to hold 10 terabytes of data, and perform 10 trillion parallel calculations at a time.
  4. Raw Material is Abundant: As long as there are cellular organisms, there will always be a large, cheap supply of DNA to produce biological computers.
  5. Clean to Manufacture: Unlike the toxic materials used to make traditional microprocessors, biological processors can be made cleanly.

Disadvantages:

  1. Unreliable Components: One of biological computing's biggest challenges is calculating with elements that are flawed and unreliable, because unlike in a conventional integrated circuit, biological elements like an individual bacteria cell or enzyme can be flawed and are not always 100% guaranteed to provide a correct solution, so scientists will have to figure out a way to build reliable systems out of unreliable components.
  2. Difficult to Handle Because of Small Size: Because of the nano-sized particles in DNA, researchers have struggled for many years with the challenge of making a DNA computer that is as effective as a silicon-based system

Applications:

    There are many areas that can benefit from DNA computing, like solving complex mathematical problems that other types of computers have so far been unable to solve, but one particularly important area is medicine. Currently in development is a DNA computer that actually operates within human cells. The hope is that this technology will eventually allow for the DNA computer to perform tasks inside the human body like administering insulin shots when needed, accurately diagnosing disease, reprogramming cancer-causing genes, and fighting disease by selecting and exclusively treating diseased cells while leaving healthy ones intact. In addition developing a biological computer might bring us closer to understanding the most complex biological computer on earth -the human brain.


Conclusion

    For now, all these applications are distant on the horizon, and it will take years before any of these technologies can be developed on a full, practical scale. But whether it is optical, quantum, biological or other approaches, the future of processing is headed beyond silicon, because if computers are to continue advancing, radical new approaches will be needed.

References

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