Say Hello to China's New 11-Barrel Hypersonic Missile Killer

The future of naval warfare will likely include lasers, auto-cannons, andhypersonic missiles launched from the other side of the horizon.

It reportedly does so by spewing 10,000 rounds per minute—166 rounds per second—perforating any inbound threat well before it can do any damage to the PLA Type 054A frigate that the 1130 has been installed on. According to the Want China Times, a Chinese news outlet, the Type 1130 carries a pair of 1280-round magazines—enough to shoot down as many as 40 threats before requiring a reload. It's also reportedly quite accurate, notching 90 percent accuracy against hypersonic threats. It can also target fixed wing and rotary aircraft, surface ships, terrestrial targets along a coast, and even sea mines with its 30 mm rounds.

Details on the weapon system are scarce, but if its 6 to 10-barreled predecessors are any indication, the Type 1130 should be able to target threats anywhere from 8 to 20 km out. Due to the limited range of the Gatling gun it employs, however, the system shouldn't actually be able to engage until the threat is right on top of it, around 3 km.

The system is guided by radar, which are what those two dishes are located above the barrel, but due to its weight and power requirements, is limited to large PLA frigates and destroyers. The system has also been spotted on China's newest aircraft carrier, the Liaoning. Future iterations are expected to be installed on China's upcoming Type 055 Destroyer. Combined with the PLA's new WU-14 hypersonic glide vehicle, naval battles may soon be over in the blink of an eye.

The World's Most Powerful Computer Network Is Being Wasted On Bitcoin

Bitcoin mining machines are insane powerhouses, and they’re only getting crazier. How much power is getting sunk into the digital crypto currency? More than the world’s top 500 supercomputers combined. What a waste.

According to Bitcoin Watch, the whole Bitcoin network hit a record-breaking high of 1 exaFLOPS this weekend. When you're talking about FLOPS, you're really talking about the number of Floating-point Operations a computer can do Per Second, or more simply, how fast it can tear through math problems. It's a pretty common standard for measuring computer power. An exaFLOPS is 10¹⁸, or 1,000,000,000,000,000,000 math problems per second. The most powerful supercomputer in the world, Sequoia, can manage a mere 16 petaFLOPS, or just 1.6 percent of the power geeks around the world have brought to bear on mining Bitcoin. The world's top 10 supercomputers can muster 5 percent of that total, and even the top 500 can only muster a mere 12.8 percent.

And that 1 exaFLOPS number is probably a little low. Because Bitcoin miners actually do a simpler kind of math (integer operations), you have to do a little (messy) conversion to get to FLOPS. And because the new ASIC miners-machines that are built from scratch to do nothing but mine Bitcoins-can't even do other kinds of operations, they're left out of the total entirely. So what we've got here is a representation of the total power spent on Bitcoin mining that could theoretically be spent on something else, like real problems.

Because of the way Bitcoin self-regulates, the math problems Bitcoin mining rigs have to do to get more 'coin get harder and harder as time goes on. Not to any particular end, but just to make sure the world doesn't get flooded with Bitcoins. So all these computers aren't really accomplishing anything other than solving super difficult and necessarily arbitrary puzzles for cyber money. It's kind of like rounding up the world's greatest minds and making them do Sudokus for nickels.

Projects like Folding-Home and SETI-Home use similarly networked power for the less-pointless practices of parsing information that could lead to more effective medicines or finding extra-terrestrial life, respectively, and either are hard-pressed to scrounge up even half of a percent of the power the Bitcoin network is rocking. And with specialized Bitcoin-mining hardware on the rise, there's going to be an army of totally powerhouse PCs out there that are good for literally nothing but digging up cybercoins.

It's incredible to think about the amount of power being directed at this one, singular purpose; power that's essentially being ""donated"" by thousands of people across the globe just because they have skin in the game. It's by far the most computational effort that has ever been devoted to a single purpose. And sure, Bitcoins are fine and all, but can you imagine what we could do if this energy was put behind other tough problems? We'll you're going to have to because so long as mining Bitcoins can earn you money and folding proteins can't, it's pretty clear which one is gonna get done.

Five Dimensional Super Computer Will Silence Jet Engines

How Stanford's Million-Core, Five Dimensional Super Computer Will Silence Jet Engines

The modern day jet engine may be powerful enough to shuttle travelers across a continent in just six hours but it's also unbearably loud—for both the ground crews that work around them and residents within earshot of airports. And while aircraft engineers are developing quieter designs, building and testing these hushed prototypes can run into the six figures. But with the help of Livermore National Labs' supercomputer and some open-source modeling software, commercial airliners may soon be whisper quiet.

The 3,000 square-foot Sequoia IBM Bluegene/Q supercomputer at Lawrence Livermore (CA) National Laboratories is among the most powerful parallel computing systems on the planet. It sports over 1.5 million embedded processors 1.6 PB of memory and crunches numbers at a staggering 16.32 PFLOPS. The Sequoia's cores are arranged in a 5D Torus design wherein each core is directly connected to ten others. This greatly reduces latency even with cores two and three connections away. Read/Write functions are handled by these processors as well—some of which tap directly to the system's primary input/output channel through an 11th connection.

While all 1.5 million cores may be necessary to calculate the nuclear weapons simulations that it is normally charged with, Joseph Nichols' research team from Stanford Engineering's Center for Turbulence Research harnessed just over a million of them for the jet engine research. They worked in conjunction with teams from the NASA Glenn Research Center in Ohio and the US Navy's NAVAIR to develop a quieter jet engine without actually having to build one.

"These runs represent at least an order-of-magnitude increase in computational power over the largest simulations performed at the Center for Turbulence Research previously," said Nichols "The implications for predictive science are mind-boggling."

The technique is known as predictive modeling and it is an exacting process. The noise that a jet engine produces constitutes less than one percent of the device's total energy output, which means that accurately reproducing them in Computational fluid dynamics (CFD) simulations requires incredibly precise calculations.

Computational fluid dynamics (CFD) simulations, like the one Nichols solved, are incredibly complex. Only recently, with the advent of massive supercomputers boasting hundreds of thousands of computing cores, have engineers been able to model jet engines and the noise they produce with accuracy and speed," said Parviz Moin, the Franklin M. and Caroline P. Johnson Professor in the School of Engineering and Director of the CTR told Wired.