Microsoft’s joint venture with a supercomputing center in Barcelona aims to develop a processor that will scale from a data center server to a smartphone, which would save energy and require less space. The researchers hope to apply vector processing technology to commercial applications such as making data centers and mobile handsets run more efficiently. The goal of the energy-efficient, composable vector processor project is to build a device that uses grid computing techniques to analyze multiple streams of data in parallel, and for the device to reconfigure itself on the fly in response to the workload it receives, say Microsoft researchers Timothy Hayes and Oscar Palomar. The technique uses some of the concepts of reduced instruction set computing, as well as new programming so that a single instruction can initiate an array of complex processes. The researchers also are working on scheduling algorithms to allocate work efficiently and to accurately recombine results from processes.
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Yale University researchers have described why computers tend to malfunction more than living organisms by analyzing the control networks in both an E-coli bacterium and the Linux operating system. Both systems are arranged in hierarchies, but with some key differences in how they achieve operational efficiencies. The molecular networks in the bacteria are arranged in a pyramid, with a limited number of master regulator genes at the top that control a wide base of specialized functions. The Linux operating system is set up more like an inverted pyramid, with many different top-level routines controlling a few generic functions at the bottom. This organization arises because software engineers tend to save money and time by building on existing routines rather than starting systems from scratch, says Yale professor Mark Gerstein. “But it also means the operating system is more vulnerable to breakdowns because even simple updates to a generic routine can be very disruptive,” Gerstein says.
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German researchers have developed a prototype safety system that would reduce the injuries of humans working alongside robots using household tools. The collision detection system uses torque sensors to determine when a kitchen knife, screwdriver, or scissors hits a different substance, and halts the movements of the sharp tool. The team from the Institute of Robotics and Mechatronics conducted strike tests on a silicon lump, a leg from a dead pig, and the arm of a human volunteer, using a robot arm. When the safety system was turned off, the robot produced deep cuts that could prove to be lethal to a living subject.
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