1. Future Computers CSCI 107, Spring 2010

2. 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

3. What’s next? Alternative architectures and nanomaterials nanomaterials Perfecting new ways to process information –E.g., quantum computing and biological computing

4. 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.

5. 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

6. 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

7. Different Computing Schemes Current Efforts –Optical –Biological –Quantum Criteria for being a computer –Represent information –Operate on that data Turing machine

8. 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

9. DNA Computing Representing data and instructions –DNA moleculesDNA molecules –Theses molecules store the “programming” that directs the lives of our cells

10. 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

11. 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

12. 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

13. 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.

14. 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.

15. Benefits Clean, fast, and can solve a new class of problems