The Kynix Blog

New research, led by the University of Southampton, has demonstrated that a nanoscale device, called a memristor, could be used to power artificial systems that can mimic the human brain.Artificial neural networks (ANNs) exhibit learning abilities and can perform tasks which are difficult for conventional computing systems, such as pattern recognition, on-line learning and classification. Practical ANN implementations are currently hampered by the lack of efficient hardware synapses; a key component that every ANN requires in large numbers.In the study, published in Nature Communications, the Southampton research team experimentally demonstrated an ANN that used memristor synapses supporting sophisticated learning rules in order to carry out reversible learning of noisy input data.Memristors are electrical components that limit or regulate the flow of electrical current in a circuit and can remember the amount of charge that was flowing through it and retain the data, even when the power is turned off.Lead author Dr Alex Serb, from Electronics and Computer Science at the University of Southampton, said: "If we want to build artificial systems that can mimic the brain in function and power we need to use hundreds of billions, perhaps even trillions of artificial synapses, many of which must be able to implement learning rules of varying degrees of complexity. Whilst currently available electronic components can certainly be pieced together to create such synapses, the required power and area efficiency benchmarks will be extremely difficult to meet -if even possible at all- without designing new and bespoke 'synapse components'."Memristors offer a possible route towards that end by supporting many fundamental features of learning synapses (memory storage, on-line learning, computationally powerful learning rule implementation, two-terminal structure) in extremely compact volumes and at exceptionally low energy costs. If artificial brains are ever going to become reality, therefore, memristive synapses have to succeed."Acting like synapses in the brain, the metal-oxide memristor array was capable of learning and re-learning input patterns in an unsupervised manner within a probabilistic winner-take-all (WTA) network. This is extremely useful for enabling low-power embedded processors (needed for the Internet of Things) that can process in real-time big data without any prior knowledge of the data.Co-author Dr Themis Prodromakis, Reader in Nanoelectronics and EPSRC Fellow in Electronics and Computer Science at the University of Southampton, said: "The uptake of any new technology is typically hampered by the lack of practical demonstrators that showcase the technology's benefits in practical applications. Our work establishes such a technological paradigm shift, proving that nanoscale memristors can indeed be used to formulate in-silico neural circuits for processing big-data in real-time; a key challenge of modern society."We have shown that such hardware platforms can independently adapt to its environment without any human intervention and are very resilient in processing even noisy data in real-time reliably. This new type of hardware could find a diverse range of applications in pervasive sensing technologies to fuel real-time monitoring in harsh or inaccessible environments; a highly desirable capability for enabling the Internet of Things vision."Reference:KY259-SDUS5EB-002GKY259-SDUS5AB-002GKY259-SDUS5AB-001G 

What about using wax with a processor as part of a technique to stave off smartphone overheating? Can wax be the answer to the thermal problem confronting smartphones? That is the proposal coming from a University of Pensylvania and University of Michigan team of researchers, who have been studying ways to manage the chip performance of smartphones. Milo Martin, an associate professor with the University of Pennsylvania and his colleagues at the two schools believe the answer is in computational sprinting involving wax. "When someone cranks the chip well beyond its recommended speeds, the wax absorbs the extra heat coming off the silicon, and at 54 degrees Celsius, it starts to melt," said a report about their research in Wired. Small mobile devices don't have room for the large fans that cool a laptop. If mobile phones actually used all of their transistors at the same time, they would overheat. Only a portion of a smartphone chip's transistors can operate at once. If you hear the term "dark silicon" it refers to the large portions of a silicon chip that must remain off at a given time. As transistors get smaller, the heat problems may only get worse.This is where computational sprinting comes into view. Under the concept of computational sprinting, a chip temporarily exceeds its sustainable thermal power budget to provide instantaneous throughput, after which the chip returns to nominal operation to cool down. The team from the two schools have been exploring computational sprinting for several years. This is a technique that uses all transistors at once, using the sprint-and-rest technique of periodic boosts.In 2012, the researchers presented a paper at the High Performance Computer Architecture (HPCA) symposium, where they noted how many mobile applications do not demand sustained performance; rather, they comprise short bursts of computation in response to sporadic user activity. To improve responsiveness for such applications, the authors explored activating otherwise powered-down cores for subsecond bursts of intense parallel computation.The authors concluded that "Although numerous engineering challenges remain (in cost, thermal materials, packaging, and power supply), our study indicates that it is feasible to capture the responsiveness of a 16W chip within the engineering constraints of a 1W mobile device via parallel computational sprinting."Back in 2012 they had wax in mind as a heat-spreading structure that includes an encapsulated phase change material—like candle wax—which would absorb heat by melting during the sprint, then slowly dissipate it by hardening while the device is at rest, according to a University of Michigan News Services report.This year, reported Wired, "they set up an Intel Core i7 test processor with a custom cooling system that could run comfortably at a maximum of 10 watts of power. In their tests, though, they would periodically boost the chip to 50 watts."That is enough to overheat the chip in seconds, "but it speeds up the chip's clock speed and it uses more transistors." The team thinks they could possibly boost the chip up to 100 watts for short periods, becoming very hot, and that is where the wax could absorb much of the heat quickly until it melts.Related products:KY56-KST2222KY56-KST06KY56-KSH2955 

Bird’s new Wideband Power Sensor series of USB Thruline power meters feature five models each suited to a particular application. All capable of measuring True Average Power, Peak Power and Duty Cycle, as well as VSWR/Return Loss, Average Burst Power and CCDF, the WPS series will work with any modulation scheme.The vast majority of RF power meters on the market today, in the milliwatt range, are all focussed on measuring power levels of typically -10dBm +/- 30dB. However, Bird Technologies are one of the few manufacturers to offer RF enquirers equipment capable of measuring “real world” transmitter power levels without the need to use directional couplers or high power attenuators.These new USB Power Meters for “real world” RF power measurements cover; 350MHz to 4GHz (150mW to 150W); 350MHz to 4GHz (25mW to 25W); 25MHz to 1GHz (500mW to 500W); 150MHz to 4GHz (100mW to 25W) and 25MHz to 1GHz (100mW to 100W).Insertion loss is less than 0.1dB (typically 0.05dB) with a VSWR of 1.1:1max (typically 1.05:1), plus a directivity specification of typically 30dB. These parameters contribute to an average power accuracy for all models of ±4% of reading, or 0.17dB, over the full power range at +15 to +350C.All Bird Wideband Power Sensors come with ‘Virtual Power Meter’ software to allow connection to a PC. In addition the WPS will interface with the Bird 5000-XT Digital Power meter, or the majority of the Bird SA / SH series of Site Analysers or SignaHawks.Also announced is the new 7020 Power Sensor, a low cost USB Power Meter similar in operation to the 501XB range. The 7020 contains the same ‘True Average Power’ measurement capabilities within the frequency range of 350MHz to 4GHz (0.15W to 150W), and has an identical accuracy of reading at ±4% +0.05W, or 0.17dB. The 7020 Power Sensor is an ideal low cost, but accurate, USB power meter for many applications.Reference:1005919-1PCUC30M72AV  

The latest buzz in the information technology industry regards "the Internet of things"—the idea that vehicles, appliances, civil-engineering structures, manufacturing equipment, and even livestock would have their own embedded sensors that report information directly to networked servers, aiding with maintenance and the coordination of tasks.Realizing that vision, however, will require extremely low-power sensors that can run for months without battery changes—or, even better, that can extract energy from the environment to recharge.Last week, at the Symposia on VLSI Technology and Circuits, MIT researchers presented a new power converter chip that can harvest more than 80 percent of the energy trickling into it, even at the extremely low power levels characteristic of tiny solar cells. Previous experimental ultralow-power converters had efficiencies of only 40 or 50 percent.Moreover, the researchers' chip achieves those efficiency improvements while assuming additional responsibilities. Where its predecessors could use a solar cell to either charge a battery or directly power a device, this new chip can do both, and it can power the device directly from the battery.All of those operations also share a single inductor—the chip's main electrical component—which saves on circuit board space but increases the circuit complexity even further. Nonetheless, the chip's power consumption remains low."We still want to have battery-charging capability, and we still want to provide a regulated output voltage," says Dina Reda El-Damak, an MIT graduate student in electrical engineering and computer science and first author on the new paper. "We need to regulate the input to extract the maximum power, and we really want to do all these tasks with inductor sharing and see which operational mode is the best. And we want to do it without compromising the performance, at very limited input power levels—10 nanowatts to 1 microwatt—for the Internet of things."The prototype chip was manufactured through the Taiwan Semiconductor Manufacturing Company's University Shuttle Program.Ups and downsThe circuit's chief function is to regulate the voltages between the solar cell, the battery, and the device the cell is powering. If the battery operates for too long at a voltage that's either too high or too low, for instance, its chemical reactants break down, and it loses the ability to hold a charge.To control the current flow across their chip, El-Damak and her advisor, Anantha Chandrakasan, the Joseph F. and Nancy P. Keithley Professor in Electrical Engineering, use an inductor, which is a wire wound into a coil. When a current passes through an inductor, it generates a magnetic field, which in turn resists any change in the current.Throwing switches in the inductor's path causes it to alternately charge and discharge, so that the current flowing through it continuously ramps up and then drops back down to zero. Keeping a lid on the current improves the circuit's efficiency, since the rate at which it dissipates energy as heat is proportional to the square of the current.Once the current drops to zero, however, the switches in the inductor's path need to be thrown immediately; otherwise, current could begin to flow through the circuit in the wrong direction, which would drastically diminish its efficiency. The complication is that the rate at which the current rises and falls depends on the voltage generated by the solar cell, which is highly variable. So the timing of the switch throws has to vary, too.Electric hourglassTo control the switches' timing, El-Damak and Chandrakasan use an electrical component called a capacitor, which can store electrical charge. The higher the current, the more rapidly the capacitor fills. When it's full, the circuit stops charging the inductor.The rate at which the current drops off, however, depends on the output voltage, whose regulation is the very purpose of the chip. Since that voltage is fixed, the variation in timing has to come from variation in capacitance. El-Damak and Chandrakasan thus equip their chip with a bank of capacitors of different sizes. As the current drops, it charges a subset of those capacitors, whose selection is determined by the solar cell's voltage. Once again, when the capacitor fills, the switches in the inductor's path are flipped."In this technology space, there's usually a trend to lower efficiency as the power gets lower, because there's a fixed amount of energy that's consumed by doing the work," says Brett Miwa, who leads a power conversion development project as a fellow at the chip manufacturer Maxim Integrated. "If you're only coming in with a small amount, it's hard to get most of it out, because you lose more as a percentage. [El-Damak's] design is unusually efficient for how low a power level she's at.""One of the things that's most notable about it is that it's really a fairly complete system," he adds. "It's really kind of a full system-on-chip for power management. And that makes it a little more complicated, a little bit larger, and a little bit more comprehensive than some of the other designs that might be reported in the literature. So for her to still achieve these high-performance specs in a much more sophisticated system is also noteworthy."Related products:XC7Z100-2FFG900IXC7Z010-1CLG400IA2F200M3F-1FGG256 

A bump circuit with flexible tuning ability that uses 500 times less power and is smaller than previous circuits has been demonstrated by researchers at the University of Tennessee in the US."The challenges and requirements of the analogue deep-learning system inspired us to come up with this radically new design," said Junjie Lu, the lead author. "We implemented the bump circuit by preceding the current correlator with a novel nano-power tunable transconductor to achieve variable width and height. By significantly reducing the power consumption of the bump circuit, this work makes possible the realisation of analogue learning and signal processing systems that achieve better energy efficiency than their digital equivalents, and ultimately fully autonomous systems, which are able to get both information and energy from the environment without external intervention."Towards flexible transferThe bump circuit is a family of circuits with bell-shaped, non-linear transfer functions. First appearing in 1991, they are widely used to provide similarity or distance measures in analogue signal processing systems such as support vector machines, neural networks and analogue machine-learning systems.The original bump circuit design lacked the ability to change the width of its transfer function, which is desirable in many applications to represent distributions with different variance or templates with different model parameters. A common approach to solve this is to pre-scale the input voltage, but the circuits required are physically large and consume a lot of power. Other approaches also have limitations such as complex circuitry, large physical size, and a restricted number of possible widths achievable.Hidden depthsThe researchers from the University of Tennessee designed their circuit as an important building block in an analogue deep-learning machine, which is able to perform unsupervised learning and extract salient features from high-dimensional input data, with a much better power efficiency than the existing digital machine learning implementations.Large-scale systems require the computational element, or bump circuit in this case, to be very efficient in both power and area. It is also important that the output features, which are the confidence scores that the current input belongs to each of the previous observations, take both the mean distances and probabilistic variances into account. A bump circuit that has a tunable centre for mean tuning, width for variance tuning, and height for normalisation is therefore highly desirable, and if these three bump parameters can be individually tuned and controlled by a single signal, this would greatly help with on-chip trainability.To achieve the variable height and width, the researchers designed and incorporated a novel transconductor, linearised using the drain resistances of saturated transistors. They adopted a pseudo-differential structure to allow operation with a low supply voltage, and designed a common mode feedback circuit to provide common mode rejection for the pseudo-differential structure to get a tunable bump height.The whole circuit uses 18.9 nW power from 3 V supply which is 1/500 th of the power of the next best bump circuit with tunable width. Implemented in 0.13 µm CMOS, it is smaller in area by 6%, and has maximum flexibility through the individual tunability of the three key bump function parameters. Another feature is that multiple bump circuits can be easily cascaded to represent multivariate probability.A vision of the futureWith power scaling in CMOS tapering off, there has been renewed interest in analogue computation recently, and the researchers expect to see some very exciting results in this area. They are currently working to integrate low-power circuits, such as their bump circuit, into larger systems for real-world applications."One application area we've been working on is machine vision," said Lu. "We've been working with image processing and machine vision researchers to build a complete pipeline using analogue circuits. This circuit helps to provide a path to implementing multi-dimensional kernel methods for machine learning."Systems using the bump circuit could find application in many areas such as healthcare monitoring, environmental monitoring, process control and battlefield surveillance. In addition, the nano-power tunable linear transconductor developed in this work, which has the advantages of ultra-low power, large input range and gm tunability, could be used in a huge range of applications such as amplifiers, filters and oscillators.Related products:LMV1031UR-20LM4889MALM4867MTE

Parts fail and things break. It's a fact of life and engineering. Some component failures can be avoided by good design practices, but many are out of the hands of designers. Identifying the offending component and why is might have failed is the first step to refining the design and increasing the reliability of a system that has been experiencing component failures.How Components FailThere are numerous reasons for why components fail.Some failures are slow and graceful where there is time to identify the component and replace it before it fails completely and the equipment is down. Other failures are rapid, violent, and unexpected, all of which are tested for during product certification testing. Some of the most common reasons for components to fail include:Over currentOver voltageOver temperatureConnected incorrectlyChange in operating environmentManufacturing defectMechanical shockMechanical stressRadiationContaminationPackagingConnectionsAgingCascading failureCorrosionRustingOxidizingThermal runawayLoose connectionsElectroStatic Discharge (ESD)Electrical stressBad circuit design Component failures do follow a trend. In the early life of an electronic system, component failures are more common and the chance of failure drops as they are used. The reason for the drop in failure rates is that the components that have packaging, soldering, and manufacturing defects often fail within minutes or hours of first using the device. This is why many manufacturers include a several hour burn in period for their products.This simple test eliminates the chance a bad component can slip through the manufacturing process and result in a broken device within hours of the end user first using it.After the initial burn in period, component failures typically bottom out and happen randomly. As components are used or even just sit, they age.Chemical reactions reduce the quality of the packaging, wires, and the component, and mechanical and thermal cycling take their toll on the mechanical strength of the component. These factors cause failure rates to continuously increase as a product ages. This is why failures are often classified by either their root cause or by when the failed in the life of the component.Identifying a Failed ComponentWhen a component fails there are a few indicators that can help identify the component that failed and aid in troubleshooting electronics. These indicators are:Visible-The most obvious indicator that a specific component has failed is through a visual inspection. Failed components often have burnt or melted areas, or have bulged out and expanded. Capacitors are often found bulged out, especially electrolytic capacitors around their metal tops. IC packages often have a small hole burned in them where the hot stop on the component vaporized the plastic around the hot spot all the way through the IC package.Smell- When components fail, a thermal overload often occurs which causes the magic blue smoke and other colorful smoke to be released by the offending component. The smoke also has a very distinct smell and varies by type of component. This is often the first sign of a component failure beyond the device not working. Often the distinct smell of a failed component will stay around the component for days or weeks which can aid in identifying the offending component during troubleshooting.Sound- Sometimes components make a sound when they fail. This happens more often with rapid thermal failures, over voltages, and over current events. When a component fails this violently, a smell often accompanies the failure. Hearing a component fail is rarer, and it often means that pieces of the component will be found loose in the product so identifying the component that failed may come down to finding which component is no longer on the PCB or in the system.Testing- Sometimes the only way to identify a component that has failed is to test individual components. This can be very challenging on a PCB since often other components will influence the measurement since all measurements involve applying a small voltage or current, the circuit will respond to it and readings can be thrown off. If a system uses several subassemblies, often replacing subassemblies is a great way to narrow down on where the issue with the system is located.