As Moore's Law slows down, engineers have been calmly observing how to continue to drive computing progress when the law fails. Artificial intelligence will certainly work. Quantum computing is also possible. However, there are still some peculiar things in the field of computing, some of which were brought to the attention of the IEEE International Conference on Revitalization of Computing Science and Technology in November 2017.
The conference explored some of the cool variants of the classic form, such as reversible calculations and neuromorphic chips. Some less familiar concepts have surfaced, such as photonic chips that accelerate artificial intelligence, nanomechanical comb logic, and "multidimensional" speech recognition systems. Next, we will introduce some things that are both peculiar and have potential.
Cold quantum neuron
Engineers often envy the brain's amazing energy efficiency. A human neuron consumes only about 10 femtojoules (one billionth of a joule) of energy when each spike voltage occurs. Michael L. Schneider of the National Institute of Standards and Technology (NIST) and his colleagues believe that artificial neurons with two Josephson junctions can be used to approximate this number.
These superconducting devices rely on the tunneling of electron pairs to pass through the barriers, which are the basis for building today's most advanced quantum computers, with less than 0.001 femtojoules of energy to generate spikes.
NIST scientists have come up with a way to connect these devices into a neural network. In the simulation, they trained the network to identify the three letters z, v and n, which is a basic test. Ideally, the network recognizes that each letter consumes only 2 femtojoules if the energy consumed to reduce its temperature to 4 Kelvin is counted. Of course, reality can't match the ideal situation, but if you can solve some problems through engineering design, you can build a neural network with as little energy as human neurons.
Calculated by line
Transistors are connected to form a circuit, and the interconnection between the lines is tighter than ever. This can lead to crosstalk interference, where the signal on one line interferes with the signal on the adjacent line through a parasitic capacitance connection. Naveen Kumar Macha of the University of Missouri-Kansas and his colleagues did not try to eliminate this interference, but to accept it. Mashe said that in today's logic circuits, "interference signals are a small fault that can propagate, and now we want to use it in logic circuits."
They found that some interconnect modes were effective in simulating the effects of basic logic gates and circuits. Assume that three interconnected lines run in parallel. When a voltage is applied to one or both of the lines, a crosstalk voltage appears on the center line. This forms an "or gate" with two inputs.
By reasonably increasing the number of transistors everywhere, Kansas staff constructed the AND gates, OR gates and XOR gates, as well as circuits that perform the carry function. These four circuits use fewer transistors than the corresponding complementary metal oxide semiconductor (CMOS) circuits, and the chip area is much smaller.
Nano cluster attack!
Engineers at Durham University in the United Kingdom have taught nanomaterial films to solve classification problems, such as canceration in mammography. Using evolutionary algorithms and custom boards, they send voltage pulses through an array of electrodes to a dilution mixture of carbon nanotubes dispersed in a liquid crystal. Over time, carbon nanotubes (a mixture of conductors and semiconductors) are arranged into a complex network of electrodes.
The network addresses key parts of the optimization problem. More importantly, nanoclusters can learn to solve secondary problems as long as the problem is not as complicated as the first one.
Is it a good solution to these problems? In some cases, the results are comparable to humans; in other cases, they are worse. Still, its effect is surprising. Eléonore Vissol-Gaudin, who helped Durham develop the system, said: "What you have to remember is that we are training a group of carbon nanotubes."
Silicon circuit board
The data is easy to move inside the chip, and the transmission between the chips is slow and energy-intensive, which makes computer designers complain. Engineers at UCLA say this is a problem with chip packages and printed circuit boards. Both are poor conductors of heat, so they limit the amount of energy that can be consumed. They also increase the energy and time consumed by data transfer between chips. To be sure, the industry has recognized these shortcomings and has begun to package multiple chips in their entirety.
Puneet Gupta and his collaborators at UCLA propose to replace printed circuit boards with a small piece of silicon. On this "silicon interconnect structure", unpackaged bare silicon can be squeezed tightly over a 100 micron length, connecting to the same fine, dense interconnects in an integrated circuit, reducing latency and reducing power consumption. And system size.
This approach also facilitates the decomposition of expensive system-on-a-chip (SoC) into inexpensive "chip particles" that perform the functions of different cores of the SoC. More importantly, because silicon has better thermal conductivity than printed circuit boards, you can run these processor cores at higher speeds.
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