Future computers
1 / 15

Future Computers - PowerPoint PPT Presentation

  • Uploaded on

Future Computers. CSCI 107, Spring 2010. When Moore’s law runs out of room. When transistors become only tens of atoms thick Quantum mechanics applies Defects are harder to control Heat is extreme “Dual-core” chips avoid these issues. What’s next?.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Future Computers' - maja

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Future computers

Future Computers

CSCI 107, Spring 2010

When moore s law runs out of room
When Moore’s law runs out of room

  • When transistors become only tens of atoms thick

    • Quantum mechanics applies

    • Defects are harder to control

    • Heat is extreme

  • “Dual-core” chips avoid these issues

What s next
What’s next?

  • Alternative architectures and nanomaterials

  • Perfecting new ways to process information

    • E.g., quantum computing and biological computing

New architectures memristor
New Architectures-Memristor

  • Smallest transistors are 32 nanometers wide—about 96 silicon atoms across

  • crossbar approach has parallel nanowires in one plane crossing over a set of wires at right angles

  • A 1 molecule thick buffer layer is between them

  • The intersections between the two sets of wires act like switches, called memristors

  • They represent 1s and 0s as transistors do, but also store more information.

  • 1 memristor can do the work of 10 or 15 transistors.

Multiple cores
Multiple Cores

  • When clock cycles reached 3 to 4 GHz chips reached the heat ceiling

  • For greater performance, designers placed two processors on 1 chip

  • Personal computers now have quadruple cores

    • Intel i7

    • AMD Phenom X4

  • Need to create languages and tools for software developers of consumer applications

    • Microsoft’s F# programming language

    • More needed

Faster transistors
Faster Transistors

  • researchers hope to make graphene transistors

    • 10 nm across and one atom high

    • Faster than field-effect transistors.

    • Lose very little energy from scattering or colliding with atoms in the lattice, so less heat is generated

Different computing schemes
Different Computing Schemes

  • Current Efforts

    • Optical

    • Biological

    • Quantum

  • Criteria for being a computer

    • Represent information

    • Operate on that data

  • Turing machine

Optical computing
Optical Computing

  • Representing information

    • photons carry information, not electrons, and they do so at the speed of light

  • Computation

    • Controlling light is much more difficult

    • Current work: optical switches and optical interconnect between traditional processors

Dna computing
DNA Computing

  • Representing data and instructions

    • DNA molecules

    • Theses molecules store the “programming” that directs the lives of our cells

Dna computing1
DNA Computing

  • Computing Tools

    • Watson-Crick pairing

      • every strand of DNA has its Watson-Crick complement

    • Polymerases

      • copy information from one molecule into another

    • Ligases

      • binds molecules together

    • Nucleases

      • cut nucleic acids

    • Gel electrophoresis

      • A solution of heterogeneous DNA molecules is placed in one end of a slab of gel, and a current is applied

    • DNA synthesis

      • write a DNA sequence on a piece of paper, send it to a commercial synthesis

  • Massively parallel, energy efficient, clean

Quantum computing
Quantum Computing

  • Representing Data

    • The energy state of a hydrogen atom

      • An atom in its ground state, with its electron in its lowest possible energy level can represent a 0

      • The atom in an excited state, with its electron at a higher energy level can represent a 1

Representing information
Representing Information

  • Quantum computers aren't limited to two states

  • Quantum bits, or qubits, can exist in superposition

    • when checked, the qubit will read 1 half of the time and 0 half of the time

  • Quantum Physics

Quantum computing1
Quantum Computing

  • Qubits can be set and read using lasers to pulse energy

  • Operations:

    • AND, NOT, COPY

  • Big Problem: How to isolate atoms:

    • Ion traps use optical and/or magnetic fields

    • Optical traps use light waves to trap and control particles.

    • Quantum dots are made of semiconductor material and are used to contain and manipulate electrons.

Quantum parallelism
Quantum Parallelism

  • Quantum entanglement

    • if you apply a force to 2 atoms in superposition, they can become entangled

    • In entanglement the original information no longer resides in a single quantum bit but is stored instead in the correlations between qubits

    • Measuring one bit, thereby putting it in a definite state, causes the other bit to also enter a definite state

  • “Quantum Parallelism”---massively parallel, non-deterministic computing

    • Put all the input bits in equal superposition of 0 and 1---an equal superposition of all possible inputs.

    • Run this input through a logic circuit that carries out a particular computation.

    • The result is a superposition of all the possible outputs of that computation.


  • Clean, fast, and can solve a new class of problems