• November 2019
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China’s Policing Robot: Cattle Prod Meets Supercomputer

Computerworld (10/31/16) Patrick Thibodeau

Chinese researchers have developed AnBot, an “intelligent security robot” deployed in a Shenzhen airport. The backend of AnBot is linked to China’s Tianhe-2 supercomputer, where it has access to cloud services. AnBot uses these technologies to conduct patrols, recognize threats, and identify people with multiple cameras and facial recognition. The cloud services give the robots petascale processing power, well beyond the processing capabilities in the robot itself. The supercomputer connection enhances the intelligent learning capabilities and human-machine interface of the devices, according to a U.S.-China Economic and Security Review report that focuses on China’s autonomous systems development efforts. The report found the ability of robotics to improve depends on the linking of artificial intelligence (AI), data science, and computing technologies. In addition, the report notes simultaneous development of high-performance computing systems and robotic mechanical manipulation give AI the potential to unleash smarter robotic devices that are capable of learning as well as integrating inputs from large databases. The report says the U.S. government should increase its own efforts in developing manufacturing technology in critical areas, as well as monitoring China’s growing investments in robotics and AI companies in the U.S.

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A Billion Billion Calculations per Second: Where No Computer Has Gone Before

South China Morning Post (Hong Kong) (10/29/16) Viola Zhou

China has launched the development of its first exascale high-performance computer to maintain its lead position in the global supercomputing race. The system will run at 1,000 petaflops, topping the speed of China’s Sunway TaihuLight computer by a factor of 10. China’s Ministry of Science and Technology has allocated funding to three research institutions to devise prototypes to meet its five-year target of putting an exascale computer into operation. The participating institutions include Sugon, the National University of Defense Technology, and the National Research Center of Parallel Computer Engineering and Technology (developer of Sunway TaihuLight, currently the top supercomputer in the world). University of Science and Technology of China professor An Hong says once the prototypes are finished, the ministry will choose two teams with the best designs to construct the fully functioning exascale system. For the first time this year, China dethroned the U.S. as the country with the most supercomputers in the Top500 ranking. “The demand for computing speed has no limits,” An says. “Now we have the money and technology, we can build better computers for scientists to use.”

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More Computations for Less Energy

Electronic Specifier (11/03/16) Enaie Azambuja

EUROSERVER, a leading European Union-funded research project, is clearing a path toward lower energy consumption in data centers. EUROSERVER combines the concept of chiplets, where multiple silicon subsystems are mounted in an integrated device, and a new system architecture to enable more energy-efficient servers. The project has yielded system architecture and runtime software innovations that include sharing of peripheral devices, access to system-wide memory, data compression to better use memory, and lightweight hypervisor capabilities. The growing capacity and number of data centers is accompanied by increasing financial and environmental impacts of their energy consumption. EUROSERVER will develop a new type of server derived from efficient and scalable ARM processors and the flexibility of a system-on-chip (SoC) design. “The SoC architectures and advanced packaging solutions being developed bring us one step closer to scalability and power efficiency in data centers,” says EUROSERVER coordinator Isabelle Dor. “We are also delighted that two startups have been created to leverage innovations from the project.” The startups include KALEAO, which has rolled out a unique generation of Web-scale, true-converged server appliance with physicalized resource sharing, OpenStack virtualization services, and extreme core density, supporting low energy consumption and significant computing capabilities.

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New Hikari Supercomputer Starts Solar HVDC

Texas Advanced Computing Center (09/14/16) Jorge Salazar

The Hikari computing system at the Texas Advanced Computing Center (TACC) in Austin, TX, is the first supercomputer in the U.S. to use solar and high-voltage direct current (HVDC) for power. Launched by the New Energy and Industrial Technology Development Organization in Japan, NTT FACILITIES, and the University of Texas at Austin, the project aims to demonstrate the potential of HVDC, which allows for ease of connection to renewable energy sources, including solar, wind, and hydrogen fuel cells. During the day, solar panels shading a TACC parking lot provide nearly all of Hikari’s power, up to 208 kilowatts, and at night the microgrid connected to the supercomputer switches back to conventional AC power from the utility grid. The Hikari power feeding system, which is expected to save 15 percent on energy consumption compared to conventional systems, could change how data centers power their systems. The new supercomputer came online in late August, and it consists of 432 Hewlett Packard Enterprise (HPE) Apollo 8000 XL730f servers coupled with HPE DL380 and DL360 nodes interconnected with a first-of-its-kind Mellanox End-to-End EDR InfiniBand system operating at 100 Gbps. More than 10,000 cores from Intel “Haswell” Xeon processors will deliver more than 400 teraflops.

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Reconfigurable Chaos-Based Microchips Offer Possible Solution to Moore’s Law

NCSU News (09/20/16) Tracey Peake

Nonlinear, multi-functional integrated circuits could lead to novel computer architectures that can do more with fewer transistors, according to researchers at North Carolina State University (NCSU). As the number of transistors on integrated circuits increases to keep up with processing demands, the semiconductor industry is seeking new ways to create computer chips without continually shrinking the size of individual transistors. The NCSU researchers utilized chaos theory to leverage a circuit’s nonlinearity and enable transistors to be programmed to perform different tasks. “In current processors you don’t utilize all the circuitry on the processor all the time, which is wasteful,” says NCSU researcher Behnam Kia. “Our design allows the circuit to be rapidly morphed and reconfigured to perform a desired digital function in each clock cycle.” Kia and NCSU professor William Ditto developed the design and fabrication of the integrated circuit chip, which is compatible with existing technology and utilizes the same processes and computer-aided design tools as existing computer chips. Ditto says the design is nearing commercial size, power, and ease of programming and could be of commercial relevance within a few months.

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Transistors Will Stop Shrinking in 2021, Moore’s Law Roadmap Predicts

IEEE Spectrum (07/22/16) Rachel Courtland

The 2015 International Technology Roadmap for Semiconductors (ITRS) predicts the transistor could stop shrinking in only five years. The report predicts that after 2021, it will no longer be economically feasible for companies to continue to shrink the dimensions of transistors in microprocessors. Transistor miniaturization was still a part of the long-term forecast as recently as 2014, but three-dimensional (3D) concepts have gained momentum. A company could continue to make transistors smaller well into the 2020s, but the industry wanted to send the message that it is now more economic to go 3D, says ITRS chair Paolo Gargini. In the years before 3D integration is adopted, ITRS predicts leading-edge chip companies will seek to boost density by turning the transistor from a horizontal to a vertical geometry and building multiple layers of circuitry, one on top of another. The report also predicts the traditional silicon channel will be made with alternative materials. The changes will enable companies to pack more transistors in a given area, but keeping to the spirit of Moore’s Law is another matter.

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Nvidia GPU-Powered Autonomous Car Teaches Itself to See and Steer

Network World (04/28/16) Steven Max Patterson

An Nvidia engineering team built an autonomous car that combines a camera, a Drive-PX embedded computer, and 72 hours of training data. The researchers trained a convolutional neural network (CNN) to map raw pixels from the camera directly to steering commands. Three cameras and two computers were utilized by the training system to obtain three-dimensional video images and steering angles from the vehicle driven by a human. Nvidia researchers watched for changes in the steering angle as the training signal mapped the human driving patterns into bitmap images recorded by the cameras, and learning was enabled using the CNN to generate the internal representations of the processing steps of driving. The open source machine-learning system Torch 7 was used to render the learning into the processing steps that autonomously saw the road, other vehicles, and obstacles to steer the test vehicles. The steering directions the CNN performed in a simulated response to the 10-frames-per-second images captured by the human-driven car were compared to the human steering angles, teaching the system to see and steer. On-road testing proved CNNs can learn the task of lane detection and road following without manually and explicitly deconstructing and classifying road or lane markings, semantic abstractions, path planning, and control.

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