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Carnegie Mellon University develops the next generation of ultra efficient silicon chips

the National Science Foundation (NSF) recently funded the Carnegie Mellon University (CMU) silicon system implementation Center (CSSI) with us $2.6 million to develop the next generation of ultra efficient silicon chips, which may bring a revolution in chip design and operation

Shawn Blanton, the leader of CSSI, said that NSF's funding will help researchers realize the ability of silicon chips to learn from their own big data, so that the chips can meet the needs of users by changing their own tasks

this three-year research plan includes experts from various fields of electronic and computer engineering, including circuit design, computer architecture, integrated circuit chip manufacturing, network security and statistical learning. The research institutions also include the Robotics Institute

at present, the core of almost all electronic systems is silicon chips. Blanton said that it is also OK. 3. The rubber tensile strength testing machine must ensure that the protective ground wire is well connected, waterproof and dust-proof. At present, the management of internal resources and infrastructure of silicon chips is largely temporary and scattered, which also leads to the optimization of chip resources. This lack of technological maturity also means that existing chips actually waste a lot of energy, resulting in shorter battery life, higher data center power demand and inefficient use of global energy

due to the complexity of the existing chip technology, CMU researchers have launched a project called "statistical learning in chips" (SLIC), which aims to use machine learning to achieve the overall integration of silicon chip resource management

blanton said that SLIC integrated circuits can continuously monitor their own performance and conditions to ensure that they always operate with the best efficiency. At the same time, the high-speed and efficient SLIC engine will also enhance the application performance of the chip, such as improving new intelligent systems (such as sensors for predicting blood glucose levels) and simplifying the man-machine interface for controlling prosthetic limbs. SLIC technology can also be applied to the monitoring and data of key infrastructure, and multiple sets of equipment range production systems can be purchased at the same time, such as power, air traffic control and communication infrastructure

C3. Adding 20% of fly ash and different inorganic powders to polypropylene for physical performance comparison test, ed Schlesinger, Professor of Mu electronic and computer engineering, said that this research will have a huge impact, because the research team is essentially developing a new paradigm in the field of integrated circuit technology, so that the chip itself has some intelligence, so as to provide more superior performance for its system

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