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A simpler, single-minded computer to solve complex problems

A team of Rochester electrical and computer engineers has developed a simple computing device they believe can help solve military logistic optimization problems in complex battles in the future. (Getty Images graphic)

Rochester researchers develop novel Ising machines with federal research and development funding support from DARPA.

鈥淲hy the Russian Military Is Bogged Down by Logistics.鈥 鈥淎llies Fail to Agree on Sending Tanks to Ukraine.鈥

These recent headlines underscore the importance of logistics in warfare. Which weapons and supplies are needed? In what quantity? And equally importantly, what is the most economical way to get these supplies to the right places, and at the right times, to soldiers in front lines spread over hundreds, even thousands of miles?

A team of 人妻少妇专区 electrical and computer engineers believe their invention鈥攁 simple computing device like no other鈥攃an help solve military logistic optimization problems in complex battles in the future.

To that end, the Defense Advanced Research Projects Agency (DARPA), a research and development agency of the United States Department of Defense, recently awarded the researchers a 鈥攐ne that could total $6.1 million over five years鈥攖o develop two novel Ising machines.

Ising machines that outperform quantum computers?

Named after German physicist Ernst Ising, the Ising model describes how atoms in natural magnets or spin glasses assume one of two values鈥攕pin up or spin down鈥攖o arrange themselves in the lowest energy state. Ising machines are designed to mimic and further refine this process to find optimal solutions to so-called combinatorial optimization problems, which involve large numbers of competing alternatives. Moreover, in such problems, the number of possible solutions increases exponentially as the number of independent variables increases.

The machines would be tested on combinatorial optimization problems posed, for example, when supplying dozens, even hundreds of combat units, says the project鈥檚 principal investigator , a professor of electrical and computer engineering. They could also be used in many commercial applications, such as finding efficient routes for package deliveries, generating test patterns to detect faults in chips, and efficiently correcting errors for 5G wireless radios.

Compared to conventional computers, 鈥渙ur devices have a much simpler architecture,鈥 Huang says. 鈥淚t can only solve these kinds of optimization problems. We cannot do Zoom calls on it. So, it鈥檚 a very special-purpose machine. But it鈥檚 extremely good at what it does.鈥

The devices are still in the early stages of development by the Rochester team, which includes , , , , and , also faculty members in the Department of Electrical and Computer Engineering. One of the devices, however, has undergone extensive simulations, which show that it would solve moderately sized optimization problems several orders of magnitude faster than conventional computers鈥攁nd at far less energy, Huang says.

Compared to already existing $15M quantum annealers (a type of quantum computer), the simulated device will be 鈥渄irt cheap鈥 to build and will be compatible with already existing CMOS (complementary metal-oxide semiconductor) 听integrated circuits, he adds.

Huang is confident the device will outperform even quantum computers in speed and power in solving optimization problems 鈥渁t least in the current [noisy intermediate-scale quantum] era,鈥 he says. Moreover, unlike quantum computers, which require cryogenic conditions, both devices his team proposes will operate at room temperature.

Leveraging nature鈥檚 laws of physics instead of conventional computation

Many occurrences in nature鈥攆or example, an object falling to the ground鈥攃an be modeled by writing and solving differential equations, according to Huang. 鈥淭his suggests that nature itself is effectively solving these differential equations somehow,鈥 he says.

Ising machines attempt to directly use the computation performed by nature. This is sometimes called 鈥渘ature-based computing鈥 or 鈥減hysical computation.鈥

Various Ising machines have been developed to date, including optics-based, quantum designs. However, all of them have important practical constraints imposed by their design, Huang says. Some have only near-neighbor coupling capabilities across the various spins, also called nodes. Others use conventional computing to emulate coupling, thereby losing efficiency; yet others require elements that are hard to integrate on a chip.

The first Ising machine the Rochester team is developing is based on a . Pioneered by Huang and Ignjatovic and their former PhD students Richard Afoakwa and Yiqiao Zhang, it would provide coupling across all nodes without emulation while using elements that are easy to integrate on a chip. 鈥淚 call it the world鈥檚 first Ising machine without major drawbacks,鈥 Huang says.

At this point, the researchers have simulated the device at tens of thousands of nodes. 鈥淲hen you get to a very large scale鈥攈undreds of thousands of nodes or more鈥攚e might run into a potential delay issue that could limit its performance,鈥 Huang says.

As a more futuristic alternative, the team will also develop a second, optics-based Ising machine that Huang and Lin started to explore almost six years ago. Higher-speed optics-based machines have the potential to address critical path delay issues. However, large-scale photonic systems tend to be 鈥渕ore challenging to build simply because they are as yet not supported by a mature fabrication technology,鈥 Huang says. 鈥淪o, this will be more of a high-risk, long-term solution.鈥

A third part of the grant, headed by Huang and Mateos, involves developing software/hardware codesign to efficiently map problems to the two hardware platforms. And if fully funded, the project will support the equivalent of 12 PhD students or six PhD students and three postdoctoral associates across the researchers鈥 labs.


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