Lifeboat Foundation

A machine-learning algorithm demonstrated the capability to process data that exceeds a computer’s available memory by identifying a massive data set’s key features and dividing them into manageable batches that don’t choke computer hardware. Developed at Los Alamos National Laboratory, the algorithm set a world record for factorizing huge data sets during a test run on Oak Ridge National Laboratory’s Summit, the world’s fifth-fastest supercomputer.

Equally efficient on laptops and supercomputers, the highly scalable algorithm solves hardware bottlenecks that prevent processing information from data-rich applications in cancer research, satellite imagery, social media networks, national security science and earthquake research, to name just a few.

“We developed an ‘out-of-memory’ implementation of the non-negative matrix factorization method that allows you to factorize larger data sets than previously possible on a given hardware,” said Ismael Boureima, a computational physicist at Los Alamos National Laboratory. Boureima is first author of the paper in The Journal of Supercomputing on the record-breaking algorithm.

Tesla’s (TSLA) stock is rising in pre-market trading on an optimistic new report about the automaker’s Dojo supercomputer coming from Morgan Stanley.

The firm massively increased its price target on Tesla’s stock because of it.

Dojo is Tesla’s own custom supercomputer platform built from the ground up for AI machine learning and, more specifically, for video training using the video data coming from its fleet of vehicles.

It is expected to deliver performance up to eight times faster than its predecessor.

The Los Alamos National Laboratory (LANL) is in the final stages of setting up a new supercomputer dubbed Crossroads that will allow it to test the US nuclear stockpile without major tests, a press release said. The system has been supplied by Hewlett Packard and installation began in June of this year.

The Department of Energy (DoE) has been tasked with the responsibility of ensuring that the US nuclear stockpile can be relied upon if and when it needs to be used. For this purpose, the federal agency does not actually test the warheads but carries out simulations to determine the storage, maintenance, and efficacy of the weapons.

In a recently published article featured on the cover of the Biophysical Journal, Dr. Rafael Bernardi, assistant professor of biophysics at the Department of Physics at Auburn University, and Dr. Marcelo Melo, a postdoctoral researcher in Dr. Bernardi’s group, shed light on the transformative capabilities of the next generation of supercomputers in reshaping the landscape of biophysics.

The researchers at Auburn delve into the harmonious fusion of computational modeling and experimental biophysics, providing a perspective for a future in which discoveries are made with unparalleled precision. Rather than being mere observers, today’s biophysicists, with the aid of advanced high-performance computing (HPC), are now trailblazers who can challenge longstanding biological assumptions, illuminate intricate details, and even create new proteins or design novel molecular circuits.

One of the most important aspects discussed in their perspective article is the new ability of computational biophysicists to simulate complex biological processes that range from the subatomic to whole-cell models, in extraordinary detail.

Quantum technologies—and quantum computers in particular—have the potential to shape the development of technology in the future. Scientists believe that quantum computers will help them solve problems that even the fastest supercomputers are unable to handle yet. Large international IT companies and countries like the United States and China have been making significant investments in the development of this technology. But because quantum computers are based on different laws of physics than conventional computers, laptops, and smartphones, they are more susceptible to malfunction.

An interdisciplinary research team led by Professor Jens Eisert, a physicist at Freie Universität Berlin, has now found ways of testing the quality of quantum computers. Their study on the subject was recently published in the scientific journal Nature Communications. These scientific quality control tests incorporate methods from physics, computer science, and mathematics.

Quantum physicist at Freie Universität Berlin and author of the study, Professor Jens Eisert, explains the science behind the research. “Quantum computers work on the basis of quantum mechanical laws of physics, in which individual atoms or ions are used as computational units—or to put it another way—controlled, minuscule physical systems. What is extraordinary about these computers of the future is that at this level, nature functions extremely and radically differently from our everyday experience of the world and how we know and perceive it.”

Since the start of the quantum race, Microsoft has placed its bets on the elusive but potentially game-changing topological qubit. Now the company claims its Hail Mary has paid off, saying it could build a working processor in less than a decade.

Today’s leading quantum computing companies have predominantly focused on qubits—the quantum equivalent of bits—made out of superconducting electronics, trapped ions, or photons. These devices have achieved impressive milestones in recent years, but are hampered by errors that mean a quantum computer able to outperform classical ones still appears some way off.

Microsoft, on the other hand, has long championed topological quantum computing. Rather than encoding information in the states of individual particles, this approach encodes information in the overarching structure of the system. In theory, that should make the devices considerably more tolerant of background noise from the environment and therefore more or less error-proof.

The teams pitted IBM’s 127-qubit Eagle chip against supercomputers at Lawrence Berkeley National Lab and Purdue University for increasingly complex tasks. With easier calculations, Eagle matched the supercomputers’ results every time—suggesting that even with noise, the quantum computer could generate accurate responses. But where it shone was in its ability to tolerate scale, returning results that are—in theory—far more accurate than what’s possible today with state-of-the-art silicon computer chips.

At the heart is a post-processing technique that decreases noise. Similar to looking at a large painting, the method ignores each brush stroke. Rather, it focuses on small portions of the painting and captures the general “gist” of the artwork.

Continue reading “An IBM Quantum Computer Beat a Supercomputer in a Benchmark Test” »

Wave-based analog computing has recently emerged as a promising computing paradigm due to its potential for high computational efficiency and minimal crosstalk. Although low-frequency acoustic analog computing systems exist, their bulky size makes it difficult to integrate them into chips that are compatible with complementary metal-oxide semiconductors (CMOS). This research paper addresses this issue by introducing a compact analog computing system (ACS) that leverages the interactions between ultrasonic waves and metasurfaces to solve ordinary and partial differential equations. The results of our wave propagation simulations, conducted using MATLAB, demonstrate the high accuracy of the ACS in solving such differential equations. Our proposed device has the potential to enhance the prospects of wave-based analog computing systems as the supercomputers of tomorrow.

Quantum computers are the next step in computation. These devices can harness the peculiarities of quantum mechanics to dramatically boost the power of computers. Not even the most powerful supercomputer can compete with this approach. But to deliver on that incredible potential, the road ahead remains long.

Still, in the last few years, big steps have been taken, with simple quantum processors coming online. New breakthroughs have shown solutions to the major challenges in the discipline. The road is still long, but now we can see several opportunities along the way. For The Big Questions, IFLScience’s podcast, we spoke to Professor Winfried Hensinger, Professor of Quantum Technology at the University of Sussex and the Chief Scientific Officer for Universal Quantum, about the impact these devices will have.