Chip companies from the US and China are developing new materials to reduce reliance on a Japanese monopoly. It won’t be easy.
Category: computing – Page 286
Intel’s Hala Point, the world’s largest neuromorphic computer, has 1.15 billion neurons
Three years after introducing its second-generation “neuromorphic” computer chip, Intel on Wednesday announced the company has assembled 1,152 of the parts into a single, parallel-processing system called Hala Point, in partnership with the US Department of Energy’s Sandia National Laboratories.
The Hala Point system’s 1,152 Loihi 2 chips enable a total of 1.15 billion artificial neurons, Intel said, “and 128 billion synapses distributed over 140,544 neuromorphic processing cores.” That is an increase from the previous Intel multi-chip Loihi system, debuted in 2020, called Pohoiki Springs, which used just 768 Loihi 1 chips.
Sandia Labs intends to use the system for what it calls “brain-scale computing research,” to solve problems in areas of device physics, computer architecture, computer science, and informatics.
Machine at Intel’s Hillsboro campus can produce chips so advanced, they don’t yet exist
Engineers and developers at Intel are always working to push the boundaries of what’s possible, leaning on Moore’s Law — the idea that the number of transistors on a single chip will double every two years with a minimal increase in cost.
But over the last five years, Intel has had its ups and downs, demonstrated by the wavering value of its stock. It went from a high of $68 per share to more recently trading at $36 per share.
By investing $100 billion in American factories and innovation, the company hopes to turn that trend around. In late March, the company learned that it had secured $8.5 billion from the Biden administration, paired with another $11 billion in loans, with the goal of bringing chip manufacturing back to the U.S.
TSMC to charge premium for making chips outside of Taiwan, including its new US fabs, CEO says
Indeed, the costs of building fabs in Germany, Japan, and the U.S. are higher than the costs of building fabs in Taiwan and TSMC has complained about it a number of times in the past. The company even had to delay production start at its Fab 21 near Phoenix, Arizona, due to problems with tools installation and negotiations with trade unions.
Therefore, if a TSMC customer wants to produce its chips at a specific location, then the foundry will charge a premium. How high is that premium will be remains to be seen, but last year a media report indicated that chips made in Arizona on TSMC’s N5 and N4 production nodes could be from 20% to 30% more expensive than the same chips produced in Taiwan.
Due to higher construction and operational expenses of fabs in Japan, Germany, and the U.S., TSMC plans to transfer these additional costs to its customers to sustain its target gross margin of 53%. Although American chip designers may not welcome the increased production costs in the U.S., they will probably manufacture chips intended for government and other markets less sensitive to price increases at the Arizona facility. Consequently, they should manage to pass on these higher costs to at least some of their end customers without jeopardizing their market competitiveness.
Field-Free Future: The Rise of Quantum Precision in Electronics
Researchers at the University of Würzburg have developed a method that can improve the performance of quantum resistance standards. It’s based on a quantum phenomenon called the Quantum Anomalous Hall effect.
The precise measurement of electrical resistance is essential in the industrial production of electronics – for example, in the manufacture of high-tech sensors, microchips, and flight controls. “Very precise measurements are essential here, as even the smallest deviations can significantly affect these complex systems,” explains Professor Charles Gould, a physicist at the Institute for Topological Insulators at the University of Würzburg (JMU).
With our new measurement method, we can significantly improve the accuracy.
Compact quantum light processing: New findings lead to advances in optical quantum computing
An international collaboration of researchers, led by Philip Walther at University of Vienna, have achieved a significant breakthrough in quantum technology, with the successful demonstration of quantum interference among several single photons using a novel resource-efficient platform. The work published in Science Advances represents a notable advancement in optical quantum computing that paves the way for more scalable quantum technologies.
In a global first, scientists create, store, and retrieve quantum data
A collaboration of scientists from various universities in the UK and Europe have stored and retrieved data from quantum computers, marking a “crucial connection for ‘quantum internet,’” in a global first.
This is an essential step in quantum networking as the world gears up for the next generation of computing.
With its ultrafast computational speeds, quantum computing is touted to solve the world’s problems in designing new drugs, understanding the properties of materials, and optimizing financial risk.
Graphene’s Light-Speed Electrons Promise Revolution in Nanoscale Transistors
Researchers have shown that double-layer graphene can function both as a superconductor and an insulator, a property that could revolutionize transistor technology. This dual functionality allows for the development of nanoscale transistors that are highly energy-efficient.
An international research team led by the University of Göttingen has demonstrated experimentally that electrons in naturally occurring double-layer graphene move like particles without any mass, in the same way that light travels. Furthermore, they have shown that the current can be “switched” on and off, which has potential for developing tiny, energy-efficient transistors – like the light switch in your house but at a nanoscale. The Massachusetts Institute of Technology (MIT), USA, and the National Institute for Materials Science (NIMS), Japan, were also involved in the research. The results were published in the scientific journal Nature Communications.