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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? • Alternative architectures and nanomaterials • Perfecting new ways to process information – E.g., quantum computing and biological computing 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 • 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 • 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 • Current Efforts – Optical – Biological – Quantum • Criteria for being a computer – Represent information – Operate on that data • Turing machine 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 • Representing data and instructions – DNA molecules – Theses molecules store the “programming” that directs the lives of our cells 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 • 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 • 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 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 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, nondeterministic 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. Benefits • Clean, fast, and can solve a new class of problems