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SummaryAn innovative new method to engineer computer chips more easily and cheaper than conventioanl methods have been developed by researchers who from the University of Exeter.This new technique to produce cutting-edge,versatile microchips could revolutionize the speed,efficiency and capability of the next-gen of computers.About the researchThe discovery could revolutionise the production of optoelectronic materials – or devices that produce, detect and control light – which are vital to the next generation of renewable energy, security and defence technologies, the researchers said.Dr Anna Baldycheva, from Exeter's Centre for Graphene Science and author of the paper said:"This breakthrough will hopefully lead to a revolution in the development of vital new materials for computer electronics. The work provides a solid platform for the development of novel next-generation optoelectronic devices. Additionally, the materials and methods used are extremely promising for a wide range of further potential applications beyond the current devices." This innovative new research focused on developing a versatile,multi-functional technology to significantly enhance future computing capabilities. The team used microfluidics technology, which uses a series of minuscule channels in order to control the flow and direction of tiny amounts of fluid. For this research, the fluid contains graphene oxide flakes,that are mixed together in the channels, to construct the chips.While the graphene oxide flakes are two-dimensional- consisting of length and width only- the research team used a new sophisticated light-based system to drive the assembly of the three-dimensional chip structures.Crucially, the research team have analysed their methodology to not only confirm the technique is successful, but also to provide a blueprint for others to use to help manufacture the chips. "We are very excited about the potential of this breakthrough and look forward to seeing where it can take the optoelectronics industry in the future." added by professor Monica Craciun, co-author of the paper and Associate Professor of Nanoscience at Exeter.  This article provide by University of Exeter,and the research is  published in the respected journal Scientific Reports.Article edited by kynix. 

SummaryRecently engineers discover the two-dimensional atomic sheets for memory storage when they were developing alternative ways to provide greater memory storage capacity on thiner computer chips. Most of us are curious about how engineers discover them?DiscoverA team of electrical engineers at The University of Texas at Austin, in collaboration with Peking University scientists, has developed the thinnest memory storage device with dense memory capacity, paving the way for faster, smaller and smarter computer chips for everything from consumer electronics to big data to brain-inspired computing. Discussion"For a long time, the consensus was that it wasn't possible to make memory devices from materials that were only one atomic layer thick," said Deji Akinwande, associate professor in the Cockrell School of Engineering's Department of Electrical and Computer Engineering. "With our new 'atomristors,' we have shown it is indeed possible." Made from 2-D nanomaterials, the "atomristors"—a term Akinwande coined—improve upon memristors, an emerging memory storage technology with lower memory scalability. He and his team published their findings in the January issue of Nano Letters. "Atomristors will allow for the advancement of Moore's Law at the system level by enabling the 3-D integration of nanoscale memory with nanoscale transistors on the same chip for advanced computing systems," Akinwande said.Memory storage and transistors have, to date, always been separate components on a microchip, but atomristors combine both functions on a single, more efficient computer system. By using metallic atomic sheets (graphene) as electrodes and semiconducting atomic sheets (molybdenum sulfide) as the active layer, the entire memory cell is a sandwich about 1.5 nanometers thick, which makes it possible to densely pack atomristors layer by layer in a plane. This is a substantial advantage over conventional flash memory, which occupies far larger space. In addition, the thinness allows for faster and more efficient electric current flow.Given their size, capacity and integration flexibility, atomristors can be packed together to make advanced 3-D chips that are crucial to the successful development of brain-inspired computing. One of the greatest challenges in this burgeoning field of engineering is how to make a memory architecture with 3-D connections akin to those found in the human brain. "The sheer density of memory storage that can be made possible by layering these synthetic atomic sheets onto each other, coupled with integrated transistor design, means we can potentially make computers that learn and remember the same way our brains do," Akinwande said. The research team also discovered another unique application for the technology. In existing ubiquitous devices such as smartphones and tablets, radio frequency switches are used to connect incoming signals from the antenna to one of the many wireless communication bands in order for different parts of a device to communicate and cooperate with one another. This activity can significantly affect a smartphone's battery life. The atomristors are the smallest radio frequency memory switches to be demonstrated with no DC battery consumption, which can ultimately lead to longer battery life. All in all,this discovery has real commercialization value as it won't disrupt existing technologies. Rather, it has been designed to complement and integrate with the silicon chips already in use in modern tech devices.  

A Tomsk Polytechnic University study reveals how topological vortices found in low-dimensional materials can be both displaced and erased and restored again by the electrical field within nanoparticles. This may open exciting opportunities for memory devices or quantum computers in which information will be encrypted in the characteristics of topological vortices.(Vortices in nanoparticles exposed by the electrical field. Credit: Tomsk Polytechnic University (TPU))Scientists from TPU and international collaborators have discovered unusual self-organization of atoms in the volume of nanoparticles and have learned to control it via an electric field. Such controlled nanoparticles can be used to generate capacious non-volatile random access memory (NRAM), quantum computers and other next-generation electronics. The main author is Dmitriy Karpov, engineer of the Department of General Physics, TPU, who explains that in modern materials science, the defects of matter are divided into two large groups. The first group includes classical, well-studied defects, when atoms in matter are mechanically disordered, i.e., atoms are either removed or inserted into the lattice. In the other group, the spatial organization of the lattice itself changes and such defects are called topological. Topological defects can strongly influence matter, making it superfluid or superconductive, and therefore, it is very important to study them. Topological defects can be found only in low-dimensional materials—two-dimensional nanorods and nanofilms (just several atoms thick) and one-dimensional nanodots or nanoparticles, which are spherical particles consisting of several tens or hundreds of identical atoms. "One of the important topological defects is a topological vortex which looks like a discernible twisting caused by a small displacement of all atoms. The vortex core is a nanostrand which can be both displaced by the field, and erased and restored again within nanoparticles," explains Edwin Fohtung, Professor of Los Alamos National Laboratory and New Mexico State University . The scientists studied barium titanate nanoparticles whose internal structure was visualized with the help of penetrating X-ray radiation from the synchrotron Advanced Photon Source (Chicago, USA). They obtained an image of the volume of nanoparticles with a resolution of 18 nanometers, which enabled them to analyze the slightest changes in the structure. As a result, the researchers showed that an external electric field can displace the core of the topological vortex inside the nanoparticle, and when the field is removed, it returns to its original position. Modern components of electronics are gradually becoming smaller. This can significantly influence the efficiency of devices, which will be significantly reduced due to quantum effects. One way to circumvent these limitations is to use topological vortices. Thus, they can be used to generate high density NRAM or quantum computers in which information will be encrypted in the characteristics of topological vortices. "All in all, the possibility to control and adjust topological vortices in nanoparticles is important for the creation of new electronics," concludes Dmitriy Karpov. Further reading>>>Topological defectA topological defect can be proven to exist[when?] because the boundary conditions entail the existence of homotopically distinct solutions. Typically, this occurs because the boundary on which the conditions are specified has a non-trivial homotopy group which is preserved in differential equations; the solutions to the differential equations are then topologically distinct, and are classified by their homotopy class. Topological defects are not only stable against small perturbations, but cannot decay or be undone or be de-tangled, precisely because there is no continuous transformation that will map them (homotopically) to a uniform or "trivial" solution. Reference>>>KY259-BB910KY259-CXA1512MKY32-K9T1G08U0M-YIBO 

How many users get exasperated when their hard drive slows down? We've all found ourselves annoyed and feeling stressed watching that little spinning wheel. Will it ever stop? Usually the problem is with the hard drive. More often than not has been cluttered with all sorts of unnecessary information either malicious or otherwise. At the extreme, the hard drive becomes so corrupted that a data recovery specialist is needed. However if you keep your hard drive healthy, it can serve you well for many years.Delete your temporary files.The first port of call when your hard drive slows is to delete your temporary files. Internet browsers store these temporary files on your hard drive in an effort to speed up performance. Often they are not needed and many users never delete them. Potentially this can mean than hundreds of thousands of unnecessary files are indexed and stored on your hard disk drive. You can also remove files from your recycle bin that you are sure you want to be deleted forever. These simple actions will create a little bit more space in the data areas. Next time you attempt a read or write, there is much less ‘clutter' for the heads to work through. The result – a faster hard drive! You can always setup an automatic delete function through the operating system, weekly or monthly.Partition your hard drive.Partitioning your hard drive can reduce the risk of files being corrupted by viruses. Viruses are responsible for many performance issues and are very difficult to get rid of. Make sure your hard drive is organised by storing frequently used files and programs near each other. This also boosts the speed of your hard drive. It uses short stroking technology to minimize head repositioning delays. Although this greatly increases speed and performance it also decreases the capacity so is not always the best option, especially if you are nearing full capacity already.Install good anti-virus and anti-Trojan software.All of us understand the need for anti-virus software but how many know the difference between viruses and Trojans? Anti-virus software will not detect Trojans and these are primarily responsible for slow hard drives. Routinely run ‘on demand' scans from various different anti-Trojan applications and be sure to keep your anti-virus software upgraded.   Defrag your hard drive.Defragmenting your hard drive increases the efficiency. Ordering all the blocks and rationalising the free space is a little like tidying up your garage. Next time you need to find something, it won't take you nearly as long! You can use specialised software easily found on your machine which looks at the physical location of the files on your hard drive and optimizes those files so the computer doesn't need to search around to find the information it needs. MyDefrag is a free program that once set up will run at least every other week to ensure that your hard drive is kept running effectively.Upgrade!Sometimes it's simply hardware issues which are affecting the speed of your hard drive. This means you need to just upgrade. Do some research into your current hard drive as well as other popular ones. Consider upgrading to a high efficiency hard drive, or consider an solid state drive（SSD）.ReferenceKY259-SFSA128GV1AA4TO-I-NC-216-STDKY259-SFSA128GM1AA4TO-I-NC-616-STDKY259- SFSA128GV1AA4TO-C-NC-216-STD  

In today's computer chips, memory management is based on what computer scientists call the principle of locality: If a program needs a chunk of data stored at some memory location, it probably needs the neighboring chunks as well.But that assumption breaks down in the age of big data, now that computer programs more frequently act on just a few data items scattered arbitrarily across huge data sets. Since fetching data from their main memory banks is the major performance bottleneck in today's chips, having to fetch it more frequently can dramatically slow program execution.This week, at the International Conference on Parallel Architectures and Compilation Techniques, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) are presenting a new programming language, called Milk, that lets application developers manage memory more efficiently in programs that deal with scattered data points in large data sets.In tests on several common algorithms, programs written in the new language were four times as fast as those written in existing languages. But the researchers believe that further work will yield even larger gains.The reason that today's big data sets pose problems for existing memory management techniques, explains Saman Amarasinghe, a professor of electrical engineering and computer science, is not so much that they are large as that they are what computer scientists call "sparse." That is, with big data, the scale of the solution does not necessarily increase proportionally with the scale of the problem."In social settings, we used to look at smaller problems," Amarasinghe says. "If you look at the people in this [CSAIL] building, we're all connected. But if you look at the planet scale, I don't scale my number of friends. The planet has billions of people, but I still have only hundreds of friends. Suddenly you have a very sparse problem."Similarly, Amarasinghe says, an online bookseller with, say, 1,000 customers might like to provide its visitors with a list of its 20 most popular books. It doesn't follow, however, that an online bookseller with a million customers would want to provide its visitors with a list of its 20,000 most popular books.Thinking locallyToday's computer chips are not optimized for sparse data—in fact, the reverse is true. Because fetching data from the chip's main memory bank is slow, every core, or processor, in a modern chip has its own "cache," a relatively small, local, high-speed memory bank. Rather than fetching a single data item at a time from main memory, a core will fetch an entire block of data. And that block is selected according to the principle of locality.It's easy to see how the principle of locality works with, say, image processing. If the purpose of a program is to apply a visual filter to an image, and it works on one block of the image at a time, then when a core requests a block, it should receive all the adjacent blocks its cache can hold, so that it can grind away on block after block without fetching any more data.But that approach doesn't work if the algorithm is interested in only 20 books out of the 2 million in an online retailer's database. If it requests the data associated with one book, it's likely that the data associated with the 100 adjacent books will be irrelevant.Going to main memory for a single data item at a time is woefully inefficient. "It's as if, every time you want a spoonful of cereal, you open the fridge, open the milk carton, pour a spoonful of milk, close the carton, and put it back in the fridge," says Vladimir Kiriansky, a PhD student in electrical engineering and computer science and first author on the new paper. He's joined by Amarasinghe and Yunming Zhang, also a PhD student in electrical engineering and computer science.Batch processingMilk simply adds a few commands to OpenMP, an extension of languages such as C and Fortran that makes it easier to write code for multicore processors. With Milk, a programmer inserts a couple additional lines of code around any instruction that iterates through a large data collection looking for a comparatively small number of items. Milk's compiler—the program that converts high-level code into low-level instructions—then figures out how to manage memory accordingly.With a Milk program, when a core discovers that it needs a piece of data, it doesn't request it—and a cacheful of adjacent data—from main memory. Instead, it adds the data item's address to a list of locally stored addresses. When the list is long enough, all the chip's cores pool their lists, group together those addresses that are near each other, and redistribute them to the cores. That way, each core requests only data items that it knows it needs and that can be retrieved efficiently.That's the high-level description, but the details get more complicated. In fact, most modern computer chips have several different levels of caches, each one larger but also slightly less efficient than the last. The Milk compiler has to keep track of not only a list of memory addresses but also the data stored at those addresses, and it regularly shuffles both around between cache levels. It also has to decide which addresses should be retained because they might be accessed again, and which to discard. Improving the algorithm that choreographs this intricate data ballet is where the researchers see hope for further performance gains."Many important applications today are data-intensive, but unfortunately, the growing gap in performance between memory and CPU means they do not fully utilize current hardware," says Matei Zaharia, an assistant professor of computer science at Stanford University. "Milk helps to address this gap by optimizing memory access in common programming constructs. The work combines detailed knowledge about the design of memory controllers with knowledge about compilers to implement good optimizations for current hardware."