ZDNet reports: Scientists from quantum computing company D-Wave have demonstrated that, using a method called quantum annealing, they could simulate some materials up to three million times faster than it would take with corresponding classical methods.

Together with researchers from Google, the scientists set out to measure the speed of simulation in one of D-Wave's quantum annealing processors, and found that performance increased with both simulation size and problem difficulty, to reach a million-fold speedup over what could be achieved with a classical CPU... The calculation that D-Wave and Google's teams tackled is a real-world problem; in fact, it has already been resolved by the 2016 winners of the Nobel Prize in Physics, Vadim Berezinskii, J. Michael Kosterlitz and David Thouless, who studied the behavior of so-called "exotic magnetism", which occurs in quantum magnetic systems....

Instead of proving quantum supremacy, which happens when a quantum computer runs a calculation that is impossible to resolve with classical means, D-Wave's latest research demonstrates that the company's quantum annealing processors can lead to a computational performance advantage... "What we see is a huge benefit in absolute terms," said Andrew King, director of performance research at D-Wave. "This simulation is a real problem that scientists have already attacked using the algorithms we compared against, marking a significant milestone and an important foundation for future development. This wouldn't have been possible today without D-Wave's lower noise processor."

Equally as significant as the performance milestone, said D-Wave's team, is the fact that the quantum annealing processors were used to run a practical application, instead of a proof-of-concept or an engineered, synthetic problem with little real-world relevance. Until now, quantum methods have mostly been leveraged to prove that the technology has the potential to solve practical problems, and is yet to make tangible marks in the real world.
Looking ahead to the future, long-time Slashdot reader schwit1 asks, "Is this is bad news for encryption that depends on brute-force calculations being prohibitively difficult?"

Lanodonal writes: A mathematician who tamed a nightmarish family of equations that behave so badly they make no sense has won the most lucrative prize in academia. Martin Hairer, an Austrian-British researcher at Imperial College London, is the winner of the 2021 Breakthrough prize for mathematics, an annual $3m award that has come to rival the Nobels in terms of kudos and prestige. Hairer landed the prize for his work on stochastic analysis, a field that describes how random effects turn the maths of things like stirring a cup of tea, the growth of a forest fire, or the spread of a water droplet that has fallen on a tissue into a fiendishly complex problem. His major work, a 180-page treatise that introduced the world to "regularity structures," so stunned his colleagues that one suggested it must have been transmitted to Hairer by a more intelligent alien civilisation.

Hairer, who rents a London flat with his wife and fellow Imperial mathematician, Xue-Mei Li, heard he had won the prize in a Skype call while the UK was still in lockdown. "It was completely unexpected," he said. "I didn't think about it at all, so it was a complete shock. We couldn't go out or anything, so we celebrated at home." The award is one of several Breakthrough prizes announced each year by a foundation set up by the Israeli-Russian investor Yuri Milner and Facebook's Mark Zuckerberg. A committee of previous recipients chooses the winners who are all leading lights in mathematics and the sciences. Other winners announced on Thursday include a Hong Kong scientist, Dennis Lo, who was inspired by a 3D Harry Potter movie to develop a test for genetic mutations in DNA shed by unborn babies, and a team of physicists whose experiments revealed that if extra dimensions of reality exist, they are curled up smaller than a third of a hair's width.

The American Mathematical Society has announced the passing of Ronald Graham, "one of the principal architects of the rapid development worldwide of discrete mathematics in recent years." He died July 6th at the age of 84. From the report: Graham published more than 350 papers and books with many collaborators, including more than 90 with his wife, Fan Chung, and more than 30 with Paul Erdos. In addition to writing articles with Paul Erdos, Graham had a room in his house reserved for Erdos's frequent visits, he administered the cash prizes that Erdos created for various problems, and he created the Erdos number, which is the collaboration distance between a mathematician and Erdo's. He also created Graham's number in a 1971 paper on Ramsey theory written with Bruce Rothschild, which was for a time the largest number used in a proof.

Graham received his PhD from the University of California, Berkeley in 1962 under the direction of D.H. Lehmer. He worked at Bell Laboratories until 1999, starting as director of information sciences and ending his tenure there as chief scientist. Graham then joined the faculty at the University of California, San Diego and later became chief scientist at the California Institute for Telecommunications and Information Technology, a joint operation between the university and the University of California, Irvine. [...] Graham was an AMS member since 1961. For more information, see his "special page," these video interviews by the Simons Foundation, an audio interview about the mathematics of juggling, and his page at the MacTutor website. Graham's most recent appearance on Slashdot was in 2016, when a trio of researchers used a supercomputer to generate the largest math proof ever at 200 terabytes in size. The math problem was named the boolean Pythagorean Triples problem and was first proposed back in the 1980's by mathematician Ronald Graham.

Forbes reports on ThreeFold, an ambitious new "long-term project to rewire the internet in the image of its first incarnation: decentralized, unowned, accessible, free." "We have 18,000 CPU cores and 90 million gigabytes, which is a lot of capacity," founder Kristof de Spiegeleer told me recently on the TechFirst podcast. "It's probably between five and ten times more than all of the capacity of all the blockchain projects together..."

"It's a movement," de Spiegeleer says about ThreeFold. "It's where we invite a lot of people to...basically help us to build a new internet. Now it sounds a little bit weird building a new internet. We're not trying to replace the cables... what we need help with is that we get more compute and storage capacity close to us." That would be a fundamentally different kind of internet: one we all collectively own rather than just one we all just use.

It requires a lot of different technology for backups and storage, for which ThreeFold is building a variety of related technologies: peer-to-peer technology to create the grid in the first place; storage, compute, and network technologies to enable distributed applications; and a self-healing layer bridging people and applications. Oh, and yes. There is a blockchain component: smart contracts for utilizing the grid and keeping a record of activities. "Farmers" (read: all of us) provide capacity and get micropayments for usage.

So instead of a Bitcoin scenario where some of the fastest computers in the world waste country-scale amounts of electricity doing arcane math to create an imaginary currency with dubious value (apologies, are my biases showing?) you have people providing actual tangible services for others in exchange for some degree of cryptocurrency reward. Which, in my (very) humble opinion, offers a lot more social utility...

ThreeFold and partners have invested more than $40 million in make it happen, de Spiegeleer says, and there are more than 30 partners working on the project or onboarding shortly. "So it's happening," he says.
In the interview, de Spiegeleer points out 80% of current internet capacity is owned by less than 20 companies, arguing on the podcast that "It really needs to be something like electricity.

"It needs to be everywhere and everyone needs to have access to it. It needs to be cost effective, it needs to be reliable, it needs to be independent..."

According to physicist Jason Steffen, letting slower passengers board airplanes first actually results in a more efficient process and less time before takeoff. An anonymous reader shares a report from Ars Technica: Back in 2011, Jason Steffen, now a physicist at the University of Nevada, Las Vegas, became intrigued by the problem and applied the same optimization routine used to solve the famous traveling salesman problem to airline boarding strategies. Steffen fully expected that boarding from the back to the front would be the most efficient strategy and was surprised when his results showed that strategy was actually the least efficient. The most efficient, aka the "Steffen method," has the passengers board in a series of waves. "Adjacent passengers in line will be seated two rows apart from each other," Steffen wrote at The Conversation in 2014. "The first wave of passengers would be, in order, 30A, 28A, 26A, 24A, and so on, starting from the back."

Field tests bore out the results, showing that Steffen's method was almost twice as fast as boarding back-to-front or rotating blocks of rows and 20-30 percent faster than random boarding. The key is parallelism, according to Steffen: the ideal scenario is having more than one person sitting down at the same time. "The more parallel you can make the boarding process, the faster it will go," he told Ars. "It's not about structuring things as much as it is about finding the best way to facilitate multiple people sitting down at the same time." Steffen used a standard agent-based model using particles to represent individual agents. This latest study takes a different approach, modeling the boarding process using Lorentzian geometry -- the mathematical foundation of Einstein's general theory of relativity. Co-author Sveinung Erland of Western Norway University and colleagues from Latvia and Israel exploited the well-known connection between microscopic dynamics of interacting particles and macroscopic properties and applied it to the boarding process. In this case, the microscopic interacting particles are the passengers waiting in line to board, and the macroscopic property is how long it takes all the passengers to settle into their assigned seats. The paper has been published in the journal Physical Review E.

Sabine Hossenfelder, research fellow at the Frankfurt Institute for Advanced Studies, writes: What we have here in the foundation of physics is a plain failure of the scientific method. All these wrong predictions should have taught physicists that just because they can write down equations for something does not mean this math is a scientifically promising hypothesis. String theory, supersymmetry, multiverses. There's math for it, alright. Pretty math, even. But that doesn't mean this math describes reality. Physicists need new methods. Better methods. Methods that are appropriate to the present century. And please spare me the complaints that I supposedly do not have anything better to suggest, because that is a false accusation. I have said many times that looking at the history of physics teaches us that resolving inconsistencies has been a reliable path to breakthroughs, so that's what we should focus on. I may be on the wrong track with this, of course.

Why don't physicists have a hard look at their history and learn from their failure? Because the existing scientific system does not encourage learning. Physicists today can happily make career by writing papers about things no one has ever observed, and never will observe. This continues to go on because there is nothing and no one that can stop it. You may want to put this down as a minor worry because -- $40 billion dollar collider aside -- who really cares about the foundations of physics? Maybe all these string theorists have been wasting tax-money for decades, alright, but in the large scheme of things it's not all that much money. I grant you that much. Theorists are not expensive. But even if you don't care what's up with strings and multiverses, you should worry about what is happening here. The foundations of physics are the canary in the coal mine. It's an old discipline and the first to run into this problem. But the same problem will sooner or later surface in other disciplines if experiments become increasingly expensive and recruit large fractions of the scientific community. Indeed, we see this beginning to happen in medicine and in ecology, too.

On Princeton's "Freedom to Tinker" site, the founder of the ENIAC Programmers Project summarizes 20 years of its research, remembering the "incredible acts of computing innovation during and just after WWII" that "established the foundation of modern computing and programming."

Commissioned in 1942, and launched in 1946, the ENIAC computer, with its 18,000 vacuum tubes, was the world's very first modern computer (all-electronic, programmable, and general-purpose). "Key technologists of the time, of course, told the Army that the ENIAC would never work."

Slashdot reader AmiMoJo quotes Cory Doctorow: The ENIAC programmers had to invent programming as we know it, working without programming codes (these were invented a few years later for UNIVAC by Betty Holberton): they "broke down the differential calculus ballistics trajectory program" into small steps the computer could handle, then literally wired together the program by affixing cables and flicking the machine's 3,000 switches in the correct sequences. To capture it all, they created meticulous flowcharts that described the program's workings.
From the site: Gunners needed to know what angle to shoot their artillery to hit a target 8 to 10 miles away.... The Army's Ballistics Research Labs (BRL) located women math graduates from schools nearby [who] worked day and night, six days a week, calculating thousands of ballistics trajectories which were compiled into artillery firing tables and sent to soldiers in the battlefields. It was a tremendous effort. Second, the Army and BRL agreed to commission a highly-experimental machine... [Six] women studied ENIAC's wiring and logical diagrams and taught themselves how to program it...

After the war, the Army asked all six ENIAC Programmers to continue their work -- no solider returning home from the battlefield could program ENIAC... Others made other pivotal contributions: Jean Bartik led the team that converted ENIAC to one of the world's first stored program computer and her best friend Betty Holberton joined Eckert Mauchly Computer Corporation and wrote critical new programming tools for UNIVAC I, the first commercial computer, including the C-10 instruction code (predecessor to programming languages). You can still find its original operating manual online. ("Do not open d-c fuse cabinet with the d-c power turned on. This not only exposes a person to voltage differences of around 1500 volts but the person may be burned by flying pieces of molten fuse wire in case a fuse should blow.")

It performed calculations that helped design the world's first hydrogen bomb.

A new report out of the University of Cambridge studied the experiences of a total of 2,700 primary and secondary students in the UK and Italy and found that primary and secondary school girls had higher levels of both math anxiety and general anxiety than boys. "The study also focuses on how parents and teachers shape math performance and attitudes, perhaps without even realizing it," adds Motherboard. "In the same way that anxious parents can shape their children's anxiety, math-anxious mentors can shape how kids view their own math anxiety." From the report: The new study builds on previous research by highlighting the importance of teachers and parents' own math anxieties impacting students. Most students that the researchers talked to said that their anxiousness started when the math topics became more challenging, and they felt like they couldn't do them. Another reason the students' said they were struggling was because multiple teachers were teaching them math, and it became confusing across teaching styles. "Importantly -- and surprisingly -- this new research suggests that the majority of students experiencing maths anxiety have normal to high maths ability," Josh Hillman, Director of Education at the Nuffield Foundation, said in a press release.

Several of the excerpts of the interviews conducted by researchers with math-anxious kids are heartbreaking: Many described feelings that they knew the answers but panicked, or tried to battle through initial confusion. One child, around 9 or 10 years old, said: "Once, I think it was the first day and he picked on me, and I just kind of burst into tears because everybody was staring at me and I didn't know the answer. Well I probably knew it but I hadn't thought it through." Another described doing a fractions test: "It means like enormously [nervous], and enormously means like massively... I felt very unwell and I was really scared and because my table's in the corner, I kind of just like tried to not be in the lesson."

An anonymous reader quotes a report from Motherboard: Last week, Motherboard published an investigation which revealed that law enforcement agencies around the country are using PredPol -- a predictive policing software that once cited the controversial, unproven "broken windows" policing theory as a part of its best practices. Our report showed that local police in Kansas, Washington, South Carolina, California, Georgia, Utah, and Michigan are using or have used the software. In a 2014 presentation to police departments obtained by Motherboard, the company says that the software is "based on nearly seven years of detailed academic research into the causes of crime pattern formation the mathematics looks complicated -- and it is complicated for normal mortal humans -- but the behaviors upon which the math is based are very understandable."

The company says those behaviors are "repeat victimization" of an address, "near-repeat victimization" (the proximity of other addresses to previously reported crimes), and "local search" (criminals are likely to commit crimes near their homes or near other crimes they've committed, PredPol says.) But academics Motherboard spoke to say that the mathematical theory that is used to power PredPol is flawed, and that its algorithm -- at least as pitched to police -- is far too simplistic to actually predict crime. Kristian Lum, who co-wrote a 2016 paper that tested the algorithmic mechanisms of PredPol with real crime data, told Motherboard in a phone call that although PredPol is powered by complicated-looking mathematical formulas, its actual function can be summarized as a moving average -- or an average of subsets within a data set. "The academic foundation for PredPol's software takes a statistical modeling method used to predict earthquakes and apply it to crime," reports Motherboard. "Much like how earthquakes are likely to appear in similar places, the papers argue, crimes are also likely to occur in similar places. Suresh Venkatasubramanian, a professor of computing at the University of Utah and a member of the board of directors for ACLU Utah, told Motherboard that earthquake data and crime data are, naturally, collected in different ways."

"I would say in our mind, the key difference is that in earthquake models, you have seismographs everywhere -- wherever an earthquake happens, you'll find it," Venkatasubramanian said. "The crux of the issue really is that to what extent are you able to get data about what you're observing that is not also totally on the model itself." "If you build predictive policing, you are essentially sending police to certain neighborhoods based on what what they told you -- but that also means you're not sending police to other neighborhoods because the system didn't tell you to go there," Venkatasubramanian said. "If you assume that the data collection for your system is generated by police whom you sent to certain neighborhoods, then essentially your model is controlling the next round of data you get."

chalsall (Slashdot reader #185), writes: The Great Internet Mersenne Prime Search (GIMPS) has discovered the largest known prime number, 2^82,589,933-1, having 24,862,048 digits. A computer volunteered by Patrick Laroche from Ocala, Florida made the find on December 7, 2018.

GIMPS has been on amazing lucky streak, finding triple the expected number of new Mersenne primes -- a dozen in the last fifteen years.
"This anomaly is not necessarily evidence that existing theories on the distribution of Mersenne primes is incorrect," notes GIMPS. "However, if the trend continues it may be worth further investigation. " They also report that the newly-discovered prime number "is more than one and a half million digits larger than the previous record prime number" -- and it's one of just 51 known Mersenne prime numbers ever discovered. "GIMPS, founded in 1996, has discovered the last 17..."

Patrick Laroche is one of thousands of volunteers using GIMPS' free software to hunt for prime numbers -- and is now eligible for a $3,000 "research discovery award," the group writes at mersenne.org. "GIMPS' next major goal is to win the $150,000 award administered by the Electronic Frontier Foundation offered for finding a 100 million digit prime number" -- of which $50,000 will be awarded to the discoverer, with another $50,000 going to a 501(c)(3) mathematics-related charity selected by GIMPS, and $50,000 retained by GIMPS to cover expenses and fund other awards.

An anonymous reader shares a report: Factorising numbers into their constituent primes may sound esoteric, but the one-way nature of the problem -- and of some other, closely related mathematical tasks -- is the foundation on which much modern encryption rests. Such encryption has plenty of uses. It defends state secrets, and the corporate sort. It protects financial flows and medical records. And it makes the $2trn e-commerce industry possible. Nobody, however, is certain that the foundation of all this is sound. Though mathematicians have found no quick way to solve the prime-factors problem, neither have they proved that there isn't one. In theory, any of the world's millions of professional or amateur mathematicians could have a stroke of inspiration tomorrow and publish a formula that unravels internet cryptography -- and most internet commerce with it.

In fact, something like this has already happened. In 1994 Peter Shor, a mathematician then working at Bell Laboratories, in America, came up with a quick and efficient way to find a number's prime factors. The only catch was that for large numbers his method -- dubbed Shor's algorithm -- needs a quantum computer to work. Quantum computers rely on the famous weirdness of quantum mechanics to perform certain sorts of calculation far faster than any conceivable classical machine. Their fundamental unit is the "qubit", a quantum analogue of the ones and zeros that classical machines manipulate. By exploiting the quantum-mechanical phenomena of superposition and entanglement, quantum computers can perform some forms of mathematics -- though only some -- far faster than any conceivable classical machine, no matter how beefy.

NBA superstar LeBron James is opening a new school that many are calling a "game changer." It extends the length of a traditional school day and focuses on teaching a STEM curriculum to students who have a higher probability of failing academically or dropping out of school. An anonymous Slashdot reader shares a report from SB Nation: LeBron James' I Promise School opened Monday to serve low-income and at-risk students in his hometown, and the public school could be an agent of change in the eastern Ohio city. The institution is the intersection of James' philanthropic Family Foundation and the I Promise Network he helped kickstart. I Promise began as an Akron-based non-profit aimed at boosting achievement for younger students from disadvantaged backgrounds. Now the movement has the means to educate these students year-round. I Promise will feature longer school days, a non-traditional school year, and greater access to the school, its facilities, and its teachers during down time for students. That's a formula aimed at replicating some of the at-home support children may be missing when it comes to schoolwork. The school has also anchored its curriculum in math and science-based teaching, dipping into the STEM -- science, technology, engineering, and math -- curriculum that prepares students for the jobs of the future.

xanthos writes: A fascinating article in Quanta magazine introduces us to Cohl Furey and the eight dimensional mathematics called octonions that she is using to model the interactions of strong and electromagnetic forces.

"Proof surfaced in 1898 that the reals, complex numbers, quaternions and octonions are the only kinds of numbers that can be added, subtracted, multiplied and divided. The first three of these "division algebras" would soon lay the mathematical foundation for 20th-century physics, with real numbers appearing ubiquitously, complex numbers providing the math of quantum mechanics, and quaternions underlying Albert Einstein's special theory of relativity. This has led many researchers to wonder about the last and least-understood division algebra. Might the octonions hold secrets of the universe?"

"In her most recent published paper she consolidated several findings to construct the full Standard Model symmetry group for a single generation of particles, with the math producing the correct array of electric charges and other attributes for an electron, neutrino, three up quarks, three down quarks and their anti-particles. The math also suggests a reason why electric charge is quantized in discrete units -- essentially, because whole numbers are."

Richard Chirgwin, writing for The Register: Consider this an item for the watch-list, rather than a reason to hit the panic button: a math error in the Go language could potentially affect cryptographic libraries. Security researcher Guido Vranken (who earlier this year fuzzed up some bugs in OpenVPN) found an exponentiation error in the Go math/big package. Big numbers -- particularly big primes -- are the foundation of cryptography. Vranken posted to the oss-sec mailing list that he found the potential issue during testing of a fuzzer he wrote that "compares the results of mathematical operations (addition, subtraction, multiplication, ...) across multiple bignum libraries." Vranken and Go developer Russ Cox agreed that the bug needs specific conditions to be manifest: "it only affects the case e = 1 with m != nil and a pre-allocated non-zero receiver."

An anonymous reader quotes a report from Quartz: As the world focuses its attention on this year's recipients of the planet's most prestigious prize, the Nobel, it feels like something's missing from the list: technology. Swedish inventor Alfred Nobel established the prizes more than century ago with the instruction that his entire estate be used to endow "prizes to those who, during the preceding year, shall have conferred the greatest benefit to mankind." The categories laid out in his will -- physics, chemistry, physiology or medicine, and peace -- have remained the basis of the awards, and a prize for economics was added in 1968. So, what gives? Why only those five original fields? Nobel didn't say, revealing only that he made his choices "after mature deliberation."

One way of looking at it is that when he was designing his categories, he wanted the prizes to only reflect advances in fundamental science. In this view, "lesser" sciences such as biology, geology, or computer science -- or technology-driven fields such as engineering or robotics -- don't qualify. As genome-sequencing pioneer Eric Lander once said, "You don't get a Nobel Prize for turning a crank." But what then of literature and peace, or the newer prize for economics (an applied science at best, and a pseudoscience at worst)? Technology isn't the only field to get the cold shoulder. Mathematics -- the international language, the foundation of so many scientific pursuits, and arguably the most fundamental theoretical discipline of all -- doesn't have a Nobel Prize, either. Mathematicians have complained about this for decades. One story suggests that Nobel disliked the Finnish mathematician Rolf Nevanlinna, and assumed that he would be the first winner of the mathematics prize, if he decided to award one. Alternatively, math undergraduates are often told that Nobel was jealous of a Swedish mathematician who had an affair with his wife (though this story is ruined by the fact that Nobel didn't actually have a wife).

An anonymous reader writes: On Tuesday, Sweden's prime minister tweeted that Hans Rosling "made human progress across our world come alive for millions," and the public educator will probably best be remembered as the man who could condense 200 years of global history into four minutes. He was a geek's geek, a former professor of global health who "dropped out" because he wanted to help start a nonprofit about data. Specifically, it urged data-based decisions for global development policy, and the Gapminder foundation created the massive Trendalyzer tool which let users build their own data visualizations. Eventually they handed off the tool to Google who used it with open-source scientific datasets. The BBC describes Rosling as a "public educator" with a belief that facts "could correct 'global ignorance' about the reality of the world, which 'has never been less bad.'" Rosling's TED talks include "The Best Data You've Never Seen" and "How Not To Be Ignorant About The World," and in 2015 he also gave a talk titled "How to Beat Ebola." Hans Rosling died Tuesday at age 68.

An anonymous Slashdot reader writes: The Linux Foundation held its "LinuxCon Europe" this week, "where developers, sys admins, architects and all types and levels of technical talent gather together under one roof for education, collaboration and problem-solving to further the Linux platform." They've now updated their web site with photos and slide presentations.

The 44 presentations included a talk about Linux kernel security subsystem by kernel developer James Morris and an interesting talk by GitHub's Carol Smith arguing that mandatory math requirements can create a "steep barrier to entry" for people trying to launch programming careers. Karsten Gerloff also described how Siemens is making "strategic" use of free software.

theodp writes: Q. How is K-12 computer science like the Cold War? A. It could use a Sputnik moment, at least that's the gist of an op-ed penned by Senator Jerry Moran (R., KS) and Microsoft President Brad Smith. From the article: "In the wake of the Soviet Union's 1957 Sputnik launch, President Eisenhower confronted the reality that America's educational standards were holding back the country's opportunity to compete on a global technological scale. He responded and called for support of math and science, which resulted in the National Defense Education Act of 1958 and helped send the country to the moon by the end of the next decade. It also created the educational foundation for a new generation of technology, leadership and prosperity. Today we face a similar challenge as the United States competes with nations across the globe in the indispensable field of computer science. To be up to the task, we must do a better job preparing our students for tomorrow's jobs." Smith is also a Board member of tech-bankrolled Code.org, which invoked Sputnik in its 2014 Senate testimony ("learning computer science is this generation's Sputnik moment") as it called for "comprehensive immigration reform efforts that tie H-1B visa fees to a new STEM education fund [...] to support the teaching and learning of more computer science," nicely echoing Microsoft's National Talent Strategy. Tying the lack of K-12 CS education to the need for tech visas is a time-honored tradition of sorts for Microsoft and politicians. As early as 2004, Bill Gates argued that CS education needed its own Sputnik moment, a sentiment shared by Senator Hillary Clinton in 2007 as she and fellow Senators listened to Gates make the case for more H-1B visas as he lamented the lack of CS-savvy U.S. high school students.

An anonymous reader writes: Funded by grants from the National Science Foundation and built at the University of Texas at Austin, the Stampede 2 supercomputer looks to contend with the global supercomputer Top 5. With 18 petaflops of processing power, it aims to help any researcher with a problem requiring intense number crunching. For example, atomic and atmospheric science simulations would take years to work-out on a desktop PC but only days on a supercomputer. Texas Advanced Computing Center director Dan Stanzione said in a UT press release, "Stampede has been used for everything from determining earthquake risks to help set building codes for homes and commercial buildings, to computing the largest mathematical proof ever constructed." The Stampede 2 is about twice as powerful as the original Stampede, which was activated in March of 2013. Instead of the 22nm fabrication tech in the original Stampede, the Stampede 2 will feature 14nm Xeon Phi chips codenamed "Knights Landing" forming 72 cores compared the original system's 61 cores. With double the RAM, storage and data bandwidth, the Stampede 2 can shift up to 100 gigabits per second, and its DDR4 RAM can perform fast enough to work as a third-level cache as well as fulfill ordinary memory roles. In addition, it will feature 3D Xpoint non-volatile memory. It will be at least a year before the Stampede 2 is powered up since it just received funding.

theodp writes: In A New Chapter for Computer Science Education, the U.S. Department of Education explained earlier this month that the federal STEM Education Act of 2015 'provides an unprecedented opportunity to fully leverage federal resources' to address large gaps in students' participation in Advanced Placement (AP) computer science classes based on gender and race. "In three states," lamented the DOE, "not a single female student took the AP computer science exam" (that only 8 boys took the AP CS exam in those same 3 states was apparently not a concern). And the DOE has good news for those hoping to tap Title I and II funds for CS, but don't have any computer science teachers. "A background in math or science isn't necessarily a requirement to teach CS," explains the Dept. of Ed, "as disciplines like English, history and civics can also provide a solid foundation for teaching CS concepts."