Articles tagged with Computer Hardware
Researchers at Purdue University have created a device that can dynamically rewire itself to adapt to new data, enabling artificial intelligence to learn and remember information like the human brain. This breakthrough could lead to more efficient AI systems for tasks such as image recognition and decision-making.
A team of researchers from Osaka University has developed a simple system based on electrochemical reactions that can perform complex calculations. The system uses polyoxometalate molecules and deionized water to process information and solve nonlinear problems.
Washington University researchers have designed a new processing-in-memory (PIM) circuit that can increase PIM computing's performance by orders of magnitude. The circuit uses resistive random-access memory PIM, allowing for analog computations and eliminating the need for digital conversions.
Researchers at University of Missouri and University of Chicago develop an artificial material that can respond to its environment, make decisions, and perform actions not directed by humans. The material uses a computer chip to control information processing and convert energy into mechanical energy.
A team of researchers at Aarhus University aims to develop an optical sensor using terahertz light to decode the direction of tiny magnetic 'tornadoes' called skyrmions. Skyrmions offer a promising candidate for future bits in computer technology, requiring less power and generating less heat than current methods.
Researchers from North Carolina State University developed a software toolkit to test Apple device security, identifying a previously unknown vulnerability called iTimed. The team used this toolkit to reverse-engineer key components of Apple hardware and demonstrated the vulnerability's potential impact.
GraphIt, a state-of-the-art graph programming language, has been extended to run on graphics processing units (GPUs), enabling faster graph analysis. This advance accelerates graph algorithms, particularly those that benefit from parallelism, such as recommendation algorithms and internet search functions.
Xiaochen Guo, a Lehigh University professor, aims to improve data movement efficiency by revamping memory systems. Her goal is to proactively create and redefine locality in hardware, unlocking fundamental improvements for machine learning applications.
Researchers from UConn, University of Maryland, and Rice University will analyze and upgrade security protections for nanoscale computer hardware with a $7.5 million grant. The project aims to elevate security as a fundamental design parameter for next-generation nanoscale devices.