Computer Memory

Inspired by the brain, researchers build smarter, more efficient computer hardware

Manchester awarded a prestigious third IEEE Milestone Award for Manchester Code

The University of Manchester has been recognized for its significant contribution to computer science with the third IEEE Milestone Award, honoring the invention of Manchester Code in 1948-1949. The code's self-clocking design enables reliable transmission and remains a key feature in modern digital systems.

New AI Tool Helps Computer Architects Boost Processor Performance

Researchers developed a new AI-assisted tool called CacheMind to improve cache performance and reduce evictions. The tool uses causal reasoning to analyze fine-grained details about system behavior, enabling computer architects to identify patterns and implement fixes.

ACM Prize in Computing honors Matei Zaharia for foundational contributions to data and machine learning systems

Matei Zaharia's work on open-source systems like Apache Spark, Delta Lake, and MLflow has enabled large-scale machine learning, analytics, and AI at global scale. His innovations have made scalable computing accessible to researchers, nonprofits, and enterprises across every industry.

A 'smart' chip that reduces both consumption and computing time marks a breakthrough in high-performance computing at Politecnico di Milano

Researchers at Politecnico di Milano developed a 'smart' chip that dramatically reduces energy consumption while accelerating data processing, achieving similar accuracy to digital systems with lower power consumption and faster performance.

How brain-inspired algorithms could drive down AI energy costs

Researchers propose integrating processing capability within memory units to reduce energy consumption and latency in AI applications. Inspired by the brain's efficient processing mechanisms, spiking neural networks (SNNs) can respond to irregular events and store information in the same place.

Frontiers in Science Deep Dive series: How breaking the ‘memory wall’ using brain-inspired algorithms could help overcome AI energy costs

Researchers propose a novel approach to AI hardware design by integrating neuromorphic systems and compute-in-memory techniques to overcome the limitations of modern computing hardware. This could lead to more efficient data center energy use and enable real-time intelligence in compact, power-constrained systems.

Powered by mushrooms, living computers are on the rise

Researchers from Ohio State University have developed shiitake-based devices that can act as organic memristors, a type of data processor. These devices demonstrated similar reproducible memory effects to semiconductor-based chips and showed potential for creating low-cost, environmentally friendly brain-inspired computing components.

Stowers Institute appoints first AI Fellow to help advance biological research with artificial intelligence

The Stowers Institute has appointed its first AI Fellow, Sumner Magruder, to harness the potential of artificial intelligence in biological research. He will collaborate with researchers to design new algorithms and unlock insights from large datasets.

A new method to build more energy-efficient memory devices for a sustainable data future

Researchers at Kyushu University have developed a new method to build more energy-efficient magnetic random-access memory (MRAM) using thulium iron garnet. The team successfully produced thin films of platinum on the TmIG material, enabling high-speed and low-power information rewriting at room temperature.

Researchers tackle the memory bottleneck stalling quantum computing

A new international project aims to protect fragile quantum information from decoherence and loss, a key barrier to quantum computing's progression. The Magenium qubit design stores information in small, symmetric clusters of qubits, potentially allowing quantum data to last significantly longer than current methods.

New method to steer electricity in atom-thin metals may revolutionize devices

Researchers at the University of Minnesota have discovered a way to manipulate charge flow in ultrathin metallic films using light. This breakthrough could lead to energy-efficient optical sensors, detectors, and quantum information devices.

A brain-inspired approach for resilient AI processing

The team aims to deliver AI power directly to devices, improving resilience and speed in constrained environments. By processing data step-by-step across a network of devices, they can create a safe and adaptable system that can withstand attacks and extreme conditions.

Researchers demonstrate a new material to reduce power consumption of electronics

Researchers at the University of Minnesota have developed a new material called Ni₄W that can generate spin currents to control magnetization in electronic devices. This material has the potential to significantly reduce power usage in devices like smartphones and data centers.

Scientists unveil new way to control magnetism in super-thin materials

Researchers have developed a new way to precisely tune magnetism using ultra-thin CrPS₄ material. This breakthrough could solve long-standing scientific problems and pave the way for smarter magnetic technologies.

Magnetism recharged: A new method for restoring magnetism in thin films

Researchers from The University of Osaka developed a technique to recover magnetization in degraded spintronics devices using molecular hydrogen and Pt underlayers. This method can improve the robustness of semiconductor memory.

Skia: Shedding light on shadow branches

Skia identifies and decodes shadow branches, storing them in a memory area to alleviate bottlenecks and improve throughput. The technique can lead to quicker performance and less power consumption for data centers.

Layered semiconductor shows potential for next-gen data storage

Researchers at Washington State University have discovered a hybrid zinc telluride-based material that undergoes structural changes when subjected to pressure, making it a strong candidate for phase change memory. The material's layered structure and directional sensitivity open the door to additional uses in photonics.

New photon-avalanching nanoparticles could enable next-generation optical computers

Researchers developed new photon avalanching nanoparticles that exhibit high nonlinearities, overcoming challenges in realizing intrinsic optical bistability at the nanoscale. The breakthrough paves the way for fabricating optical memory and transistors on a nanometer scale comparable to current microelectronics.

Terabytes of data in a millimeter crystal

The UChicago Pritzker Molecular Engineering team has developed a technique to store classical computer memory in crystal gaps where atoms should be, enabling terabytes of data storage in a small millimeter-sized cube. This innovation combines quantum techniques with solid-state physics to revolutionize classical non-quantum computers.

UT Dallas professor named National Academy of Inventors Fellow

Dr. Ted Moise, UT Dallas professor and director of the North Texas Semiconductor Institute, has been honored as a National Academy of Inventors Fellow for his groundbreaking work on ferroelectric random-access memory (FRAM). This technology enables faster data storage while using less power, with applications in ultra-low power microco...

Smarter memory paves the way for EU independence in computer manufacturing

Chalmers University researchers develop new ways to make cache memory work smarter, enabling faster data retrieval and improving computer performance. The innovation is part of the European Processor Initiative aimed at securing European independence in high-performance computing chips.

New optical memory unit poised to improve processing speed and efficiency

Researchers developed a fast and scalable programmable photonic latch, enabling temporary data storage in optical processing systems. This technology could enhance AI operations by storing and retrieving data at high speeds.

A new optical memory platform for super fast calculations

Researchers developed a groundbreaking photonic platform to overcome limitations in in-memory computing, enabling faster calculations and greater efficiency. The innovative magneto-optical memories consume about one-tenth the power of traditional electronics and can be rewritten billions of times.

Smarter memory: next-generation RAM with reduced energy consumption

Researchers from Osaka University have developed a new technology to lower power consumption for modern memory devices, enabling an electric-field-based writing scheme. The proposed technology could provide an alternative to traditional RAM and is a promising step towards implementing practical magnetoelectric (ME)-MRAM devices.

MIT engineers grow “high-rise” 3D chips

Researchers create multilayered chip design that doesn't require silicon wafer substrates, allowing for better communication and computation between layers. This breakthrough enables the construction of fast and powerful AI hardware comparable to supercomputers.

Jefferson Lab devotes $3 million to testing new ideas

Jefferson Lab is investing $3 million in 13 proof-of-principle projects to explore new ideas and technologies, including nuclear physics, particle accelerator science, and computational science. The LDRD program aims to foster creativity and exploration of cutting-edge research.

Researchers discover new third class of magnetism that could transform digital devices

A new class of magnetism called altermagnetism has been imaged for the first time, offering potential to increase operation speeds of up to a thousand times in digital devices. Altermagnets combine favorable properties of ferromagnets and antiferromagnets into a single material.

Flaw in computer memory leads to global security fixes

Researchers discovered a key security weakness in AMD computer processors due to 'BadRAM', rogue memory modules providing false information to the processor. This allows attackers to bypass CPU memory protections and access sensitive data or cause disruptions in shared cloud environments.

Battery-like computer memory keeps working above 1000°F

Researchers developed a heat-tolerant memory device that can store and rewrite information at temperatures over 1100°F, comparable to the surface of Venus and the melting temperature of lead. The device uses oxygen ions instead of electrons, allowing for precise control of voltage states and potential in-memory computing applications.

Multipurpose memory

Technion researchers create new platform, PyPIM, to support in-memory computing. This enables developers to write software directly for in-memory-computing architecture, improving performance and reducing data transfer time.

Breakthrough in energy-efficient avalanche-based amorphization could revolutionize data storage

Researchers developed a new method for amorphizing indium selenide wires, requiring as little as one billion times less power density. The process resembles an avalanche and an earthquake, triggering rapid deformation and linking small areas into larger ones, potentially unlocking wider applications for phase-change memory technology.

Self shocks turn crystal to glass at ultralow power density

Scientists have developed a new method for converting crystal to glass using electric current, reducing the need for high-power melt-quench processes. The discovery could transform data storage in devices and unlock wider applications for phase-change memory technology.

A multi-level breakthrough in optical computing

Researchers from Pitt, UC Santa Barbara, University of Cagliari, and Institute of Science Tokyo have developed a new method for photonic in-memory computing that combines non-volatility, multibit storage, high switching speed, low switching energy, and high endurance in a single platform.

Solving a memristor mystery to develop efficient, long-lasting memory devices

Researchers discovered phase separation plays a crucial role in memristors retaining information over time. The team developed a device with improved retention behavior, yielding results comparable to 10 years of storage without power.

For first time, DNA tech offers both data storage and computing functions

Researchers have demonstrated DNA-based technologies that can store, retrieve, compute, erase, and rewrite data. The technology uses soft polymer materials with unique morphologies to create a structure with high surface area for depositing DNA, enabling the full range of operations found in traditional electronic devices.

AI poses no existential threat to humanity – new study finds

Researchers at University of Bath and Technical University of Darmstadt found that large language models like ChatGPT cannot learn independently or acquire new skills, making them controllable and predictable. The study concluded that LLMs remain inherently safe, but misuse is still possible.

Researchers develop state-of-the-art device to make artificial intelligence more energy efficient

A new device called computational random-access memory (CRAM) reduces energy consumption for artificial intelligence applications. CRAM enables true computation in and by memory, breaking down the bottleneck in traditional computing architecture.

Aluminum scandium nitride films: Enabling next-gen ferroelectric memory devices

Researchers have discovered aluminum scandium nitride (AlScN) films that remain stable and maintain their ferroelectric properties at temperatures up to 600°C, making them promising candidates for next-generation ferroelectric memory devices. The films exhibit a high remnant polarization value and only a slight increase in coercive fie...

Researchers developed a new metamaterial that can detect the order of external operations

A novel mechanical metamaterial, 'Chaco,' exhibits history-dependent behavior, allowing it to remember the sequence of actions performed on it. This property enables potential applications in memory storage and robotics.

Skyrmions move at record speeds: a step towards the computing of the future

Researchers have achieved record speeds of up to 900 m/s by moving magnetic skyrmions using electrical currents. This breakthrough offers new prospects for developing higher-performance and less energy-intensive computing devices.

New technique lets scientists create resistance-free electron channels

Researchers visualize chiral interface state at atomic scale for the first time, allowing on-demand creation of conducting channels. The technique has promise for building tunable networks of electron channels and advancing quantum computing.

Staying in the loop: how superconductors are helping computers “remember”

Researchers at the University of California San Diego developed superconducting loops that can demonstrate associative memory, allowing computers to remember relationships between unrelated items. The technology has significant power savings, with a million times less energy requirement than traditional computing architecture.

Computer scientists invent simple method to speed cache sifting

Researchers have invented a simple yet effective algorithm called SIEVE to optimize cache management. By labeling objects as 'zero' or 'one', the system efficiently evicts the least recently used items, reducing computational complexity and bugs.

New candidate for universal memory is fast, low-power, stable and long-lasting

Researchers at Stanford University have developed a new phase-change memory that could help computers process large amounts of data faster and more efficiently. The technology improves several metrics simultaneously, including speed, endurance, and stability, while operating below 1 volt.

Manipulated hafnia paves the way for next-gen memory devices

Researchers outline new method to stabilize bulk hafnia in metastable ferroelectric and antiferroelectric states, paving the way for non-volatile memory technology. The approach requires less yttrium, improving material quality and purity.

2D material reshapes 3D electronics for AI hardware

Researchers developed a novel approach to integrate multiple functions into a single chip using monolithic 3D integration of layered 2D materials. This technology offers unprecedented efficiency and performance in AI computing tasks, enabling faster processing, less energy consumption, and enhanced security.

Straining memory leads to new computing possibilities

Researchers at University of Rochester developed a new form of computing memory by straining materials to create hybrid phase-change memristors. This approach combines the benefits of memristors and phase-change materials, overcoming limitations of existing forms of memory.

Tough memory device aims for space missions

Gallium oxide-based flash memory device demonstrates high performance and stability in extreme temperatures and radiation, retaining data for over 80 minutes. The team aims to improve device properties through further material quality and design advancements.

NTU Singapore-led scientists discover novel way of reading data in antiferromagnets, unlocking their use as computer memory

Researchers at NTU Singapore have developed a method to read data stored in antiferromagnets, allowing for potential energy-efficient and high-speed computing. This breakthrough could lead to the creation of new memory chips with improved performance and capacity.

A ferroelectric transistor that stores and computes at scale

A new FE-FET design demonstrates record-breaking performances in computing and memory, achieving large memory window with impressively small device dimensions. The combination of molybdenum disulfide and aluminum scandium nitride materials enables energy-efficient devices for both computing and non-volatile memory applications.

Cutting edge transistors for semiconductors of the future

Researchers at Lund University have created ferroelectric 'grains' that control tunnel junctions in transistors, allowing for individual-level control and optimization of material properties. This breakthrough enables the development of new circuit architectures for neuromorphic computing and energy-efficient semiconductors.

New type of computer memory could greatly reduce energy use and improve performance

Researchers at the University of Cambridge have developed a new type of computer memory that can process data in a way similar to the human brain. This technology uses hafnium oxide and tiny self-assembled barriers to store and process information, enabling greater density, higher performance, and lower energy consumption.

Wonderful and weird

Ferroelectric materials like hafnia show promise for non-volatile random-access memory (RAM) due to their stability at high temperatures. Hafnia's unique properties, including the movement of oxygen vacancies, make it an attractive candidate for memristors that mimic brain-like computer architectures.

New method improves efficiency of ‘vision transformer’ AI systems

Researchers at North Carolina State University have developed a new methodology called Patch-to-Cluster attention (PaCa) that addresses the challenges of vision transformers. PaCa improves ViT's ability to identify, classify, and segment objects in images while reducing computational demands and enhancing model interpretability.

Ultrasmall swirling magnetic vortices detected in iron-containing material

Researchers at Argonne National Laboratory have discovered ultrasmall swirling magnetic vortices, known as merons and skyrmions, in an iron-containing material. These tiny magnetic structures show promise for future computer memory storage and high-efficiency microelectronics due to their stability and adaptability to binary code.

Make them thin enough, and antiferroelectric materials become ferroelectric

Researchers discovered a size threshold beyond which antiferroelectric materials become ferroelectric, losing energy storage advantages. At thicknesses below 40 nm, the material becomes completely ferroelectric, while above 270 nm, ferroelectric regions appear.

A possible game changer for next generation microelectronics

Scientists at Argonne National Laboratory have discovered tiny magnetic vortices called skyrmions that could store data in computers, promising 100-1000 times better energy efficiency than current memory. The team used AI and a high-power electron microscope to visualize and study the behavior of these micro-scale magnetic structures.

Learning on the edge

Researchers developed a new technique that enables on-device training using less than a quarter of a megabyte of memory, reducing the need for powerful computers and central servers. This approach preserves privacy by keeping data on the device, making deep learning more accessible for low-power edge devices.

Wearables take ‘logical’ step toward onboard control

Researchers create textile-based pneumatic computers capable of digital logic, onboard memory, and user interaction. The technology aims to assist people with functional limitations in daily tasks without electricity.