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Could energy efficiency be quantum computers’ greatest strength yet?

Quantum computers have attracted considerable interest of late for their potential to crack problems in a few hours where they might take the age of the universe (i.e., tens of billions of years) on the best supercomputers. Their real-life applications range from drug and materials design to solving complex optimization problems. They are, therefore, primarily intended for scientific and industrial research.

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Nuclear fusion researchers have created a machine learning AI algorithm to detect and track the existence of plasma blobs that build up inside the tokamak for prediction of plasma disruption, the diagnosis of plasma using spectroscopy and tomography, and the tracking of turbulence inside of the fusion reactor. New AI supercomputer with over 13.5 million processor cores and over 1 exaflop of compute power made be Cerebras. A new study reveals an innovative neuro-computational model of the human brain which could lead to the creation of conscious AI or artificial general intelligence (AGI).

AI News Timestamps:
0:00 Breakthrough AI Runs A Nuclear Fusion Reactor.
3:07 New AI Supercomputer.
6:19 New Brain Model For Conscious AI

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Lawrence Livermore National Laboratory has long been one of the world’s largest consumers of supercomputing capacity. With computing power of more than 200 petaflops, or 200 billion floating-point operations per second, the U.S. Department of Energy-operated institution runs supercomputers from every major U.S. manufacturer.

For the past two years, that lineup has included two newcomers: Cerebras Systems Inc. and SambaNova Systems Inc. The two startups, which have collectively raised more than $1.8 billion in funding, are attempting to upend a market that has been dominated so far by off-the-shelf x86 central processing units and graphics processing units with hardware that’s purpose-built for use in artificial intelligence model development and inference processing to run those models.

Cerebras says its WSE-2 chip, built on a wafer-scale architecture, can bring 2.6 trillion transistors and 850,000 CPU cores to bear on the task of training neural networks. That’s about 500 times as many transistors and 100 times as many cores as are found on a high-end GPU. With 40 gigabytes of onboard memory and the ability to access up to 2.4 petabytes of external memory, the company claims, the architecture can process AI models that are too massive to be practical on GPU-based machines. The company has raised $720 million on a $4 billion valuation.

Chip startup Cerebras Systems Inc. today debuted Andromeda, a supercomputer optimized to run artificial intelligence applications that features more than 13.5 million processor cores.

Sunnyvale, California-based Cerebras Systems is backed by more than $720 million in venture funding. The startup sells a chip called the WSE-2 that is specifically designed to run AI software. The new Andromeda supercomputer that Cerebras Systems debuted today is based on the WSE-2 chip.

According to Cerebras Systems, Andromeda can provide performance in excess of one exaflop when running AI applications. One exaflop equals 1 million trillion calculations per second. The startup says that Andromeda’s performance makes it suitable for, among other use cases, training large language models, which are complex neural networks that can perform tasks such as translating text and generating software code.

The U.S. Department of Energy’s INCITE program has awarded supercomputing time to 56 projects!

Managed jointly by the Argonne Leadership Computing Facility and Oak Ridge Leadership Computing Facility, INCITE supports large-scale, computationally intensive projects that address “grand challenges” in science and engineering.

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The U.S. Department of Energy’s (DOE) Office of Science announced allocations of supercomputer access to 56 high-impact computational science projects for 2023 through its Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. These awards, which will pursue transformational advances in science and engineering, account for 60% of the available time on the leadership-class supercomputers at DOEs Argonne and Oak Ridge national laboratories.

The projects will support a broad range of large-scale research campaigns to advance knowledge in areas ranging from astrophysics to sustainable energy technologies to materials design and discovery.

Jointly managed by the Argonne Leadership Computing Facility (ALCF) and the Oak Ridge Leadership Computing Facility (OLCF), the INCITE program is the primary means by which the facilities fulfill their mission to advance open science by providing the scientific community with access to their powerful supercomputing resources. The ALCF and OLCF are DOE Office of Science user facilities.

The hundreds of gold-rich stars discovered in our Milky Way galaxy may have come from smaller galaxies that merged 10 billion years ago, according to new simulations by a supercomputer.

Using the ATERUI II supercomputer in the Center for Computational Astrophysics at the National Astronomical Observatory of Japan, scientists at Tohoku University and the University of Notre Dame developed new simulations of galaxy formation with the highest resolution yet.

The paper was published this week in the Monthly Notices of the Royal Astronomical Society.

Could energy efficiency be quantum computers’ greatest strength yet?

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