System Bits: Nov. 13


Deep learning device identifies airborne allergens To identify and measure airborne biological particles, or bioaerosols, that originate from living organisms such as plants or fungi, UCLA researchers have invented a portable device that uses holograms and machine learning. The device is trained to recognize five common allergens — pollen from Bermuda grass, oak, ragweed and spores from t... » read more

System Bits: Oct. 30


Ethics, regional differences for programming autonomous vehicles MIT researchers have revealed some distinct global preferences concerning the ethics of autonomous vehicles, as well as some regional variations in those preferences based on a recently completed survey. [caption id="attachment_24139620" align="alignleft" width="300"] Ethical questions involving autonomous vehicles are the foc... » read more

Week In Review: Design, Low Power


Tools OneSpin launched a formal verification tool that integrates with all major simulators, coverage databases and viewers, and chip design verification planning tools to provide a comprehensive view of verification progress. Comprised of two new formal apps, it can identify unreachable coverage points and provide them to the simulator to reduce wasted effort. Synopsys released the latest ... » read more

System Bits: Oct. 16


Solving the quantum verification problem UC Berkeley doctoral candidate Urmila Mahadev spent 8 years in graduate school solving one of the most basic questions in quantum computation, which is how to know whether a quantum computer has done anything quantum at all, according to Quanta Magazine. In her paper, Mahadev presents the first protocol allowing a classical computer to interactively ... » read more

RISC-V: More Than a Core


The open-source RISC-V instruction set architecture (ISA) is attracting a lot of attention across the semiconductor industry, but its long-term success will depend on levels of cooperation never seen before in the semiconductor industry. The big question now is how committed the industry is to RISC-V's success. The real value that RISC-V brings is the promise of an ecosystem and the opportun... » read more

RISC-V Inches Toward The Center


RISC-V is pushing further into the mainstream, showing up across a wide swath of designs and garnering support from a long and still-growing list of chipmakers, tools vendors, universities and foundries. In most cases it is being used as a complementary processor than a replacement for something else, but that could change in the future. What makes RISC-V particularly attractive to chipmaker... » read more

System Bits: Aug. 14


Machine-learning system determines the fewest, smallest doses that could still shrink brain tumors In an effort to improve the quality of life for patients by reducing toxic chemotherapy and radiotherapy dosing for glioblastoma, the most aggressive form of brain cancer, MIT researchers are employing novel machine-learning techniques. According to the team, glioblastoma is a malignant tumor ... » read more

Safety, Security And PPA Tradeoffs


Safety and security are emerging as key design tradeoffs as chips are added into safety-critical markets, adding even more complexity into an already complicated optimization process. In the early days of semiconductor design, performance and area were traded off against each other. Then power became important, and the main tradeoffs became power, performance and area (PPA). But as chips inc... » read more

FD-SOI Going Mainstream


Semiconductor Engineering sat down to discuss changes in the FD-SOI world and what's behind them, with James Lamb, deputy CTO for advanced semiconductor manufacturing and corporate technical fellow at Brewer Science; Giorgio Cesana, director of technical marketing at STMicroelectronics; Olivier Vatel, senior vice president and CTO at Screen Semiconductor Solutions; and Carlos Mazure, CTO at Soi... » read more

Five DAC Keynotes


The ending of Moore's Law may be about to create a new golden age for design, especially one fueled by artificial intelligence and machine learning. But design will become task-, application- and domain-specific, and will require that we think about the lifecycle of the products in a different way. In the future, we also will have to design for augmentation of experience, not just automation... » read more

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