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An anonymous reader writes: While many recognize Yann LeCun as the father of convolutional neural networks, the momentum of which has ignited artificial intelligence at companies like Google, Facebook and beyond, LeCun has not been strictly rooted in algorithms. Like others who have developed completely new approaches to computing, he has an extensive background in hardware, specifically chip design and this recognition of specialization of hardware, movement of data around complex problems, and ultimately core performance, has proven handy. He talks in depth this week about why FPGAs are coming onto the scene as companies like Google and Facebook seek a move away from "proprietary hardware" and look to "programmable devices" to do things like, oh, say, pick out a single face of one's choosing from an 800,000 strong population in under five seconds.

An anonymous reader writes with a link to a story about one of the unexciting but vital bits of technology that will need to be even further developed as autonomous cars' presence grows: making sure that those cars don't hit people. Google researchers have recently presented findings about a method that tops previous ones for real-time pedestrian detection using neural nets "that is both extremely fast and extremely accurate." From the article: There are other approaches that provide a real-time solution on the GPU but in doing so, have not achieved accuracy targets (in this real-time approach there was a miss rate of 42% on the Caltech pedestrian detection benchmark). Another approach called the VeryFast method can run at 100 frames per second (compared to the Google team's 15) but the miss rate is even greater. Others that emphasize accuracy, even with GPU acceleration, are up to 195 times slower.

An anonymous reader writes: 19-year-old Thomas Sohmers, who launched his own supercomputer chip startup back in March, has won a DARPA contract and funding for his company. Rex Computing, is currently finishing up the architecture of its final verified RTL, which is expected to be completed by the end of the year. The new Neo chips will be sampled next year, before moving into full production in mid-2017.The Platform reports: "In addition to the young company’s first round of financing, Rex Computing has also secured close to $100,000 in DARPA funds. The full description can be found midway down this DARPA document under 'Programming New Computers,' and has, according to Sohmers, been instrumental as they start down the verification and early tape out process for the Neo chips. The funding is designed to target the automatic scratch pad memory tools, which, according to Sohmers is the 'difficult part and where this approach might succeed where others have failed is the static compilation analysis technology at runtime.'"

An anonymous reader writes For the first time in over twenty years of supercomputing history, a chipmaker [Intel] has been awarded the contract to build a leading-edge national computing resource. This machine, expected to reach a peak performance of 180 petaflops, will provide massive compute power to Argonne National Laboratory, which will receive the HPC gear in 2018. Supercomputer maker Cray, which itself has had a remarkable couple of years contract-wise in government and commercial spheres, will be the integrator and manufacturer of the "Aurora" super. This machine will be a next-generation variant of its "Shasta" supercomputer line. The new $200 million supercomputer is set to be installed at Argonne's Leadership Computing Facility in 2018, rounding out a trio of systems aimed at bolstering nuclear security initiatives as well as pushing the performance of key technical computing applications valued by the Department of Energy and other agencies.

An anonymous reader shares this story that takes a look at some of the advances SpaceX is working on. "Getting a small group of human beings to Mars and back is no easy task, we learned at the recent GPU Technology Conference in San Jose hosted graphics chip and accelerator maker Nvidia. One of the problems with such a mission is that you need a very large and efficient rocket engine to get the amount of material into orbit for the mission, explained Adam Lichtl, who is director of research at SpaceX and who with a team of a few dozen programmers is try to crack the particularly difficult task of better simulating the combustion inside of a rocket engine. You need a large engine to shorten the trip to Mars, too....Not only do you need a lot of stuff to get to Mars and sustain a colony there, but you also need a way to generate fuel on Mars to come back to Earth. All of these factors affect the design of the rocket engine....As if these were not problems enough, there is another really big issue. The computational fluid dynamics, or CFD, software that is used to simulate the movement of fluids and gases and their ignition inside of all kinds of engines is particularly bad at assisting in rocket engine design. 'Methane is a fairly simple hydrocarbon that is perfectly good as a fuel,' Lichtl said. 'The challenge here is to design an engine that works efficiently with such a compound. But rocket engine CFD is hard. Really hard.'"