Articles tagged with Computer Architecture
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
A new device from NIST scientists helps reduce noise in quantum computers by introducing a programmable toggle switch. This allows for more versatile quantum processors with clearer outputs and easier reprogramming, addressing long-standing challenges in quantum computing.
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.
Optical memristors have the potential to transform high-bandwidth neuromorphic computing, machine learning hardware, and artificial intelligence. However, scalability is a significant challenge that needs to be addressed to unlock their full potential.
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.
A new Danish research project, CP-SENS, aims to develop a digital twin platform for the mechanical and construction industries. The project will provide companies with access to intelligent IT systems tailored to their needs, enabling them to adopt digital twins without significant financial investment.
EPFL researchers have discovered a way to store and process data using magnetic waves, potentially solving the issue of energy-hungry computing technology. This approach enables non-volatile storage within the same system, reducing the need for separate processors and memory storage.
The TANGO project seeks to establish a symbiotic relationship between humans and machines, enabling effective and innovative AI systems that expand human reasoning and decision-making capabilities. Real-world use cases will be evaluated to assess the framework's potential impact on individuals and society.
The new architecture reduces physical qubits required for error correction to 10% of conventional architectures, enabling better performance than classical computers. This breakthrough accelerates progress toward practical quantum computing, with the aim of applying quantum computing applications to various societal issues.
Researchers developed memristors based on halogenated perovskite nanocrystals for more powerful and energy-efficient computing. Inspired by the human brain's synapses, these components combine data storage and processing, reducing energy consumption.
Researchers developed novel memristors with halide perovskite nanocrystals, enabling complex calculations similar to brain processes. The new memristors are faster, more energy-efficient, and easier to manufacture than predecessors.
Scientists from the University of Groningen develop complex oxide devices for energy-efficient computing, including magneto-electric spin-orbit and memristive devices. These materials have potential applications in novel computing architectures, such as random number generators.
Researchers have developed a new device that can effectively redistribute noise and reduce its impact on quantum measurements. By 'squeezing' the noise, they can make more accurate measurements, enabling faster and more precise quantum systems. The device has the potential to improve multi-qubit systems and metrological applications.
Researchers have developed a quantum computing architecture that enables directional photon emission, the first step toward extensible quantum interconnects. This breakthrough enables the creation of larger-scale devices by linking multiple processing modules along a common waveguide.
Researchers at Shinshu University demonstrate the transformation of isolated skyrmions into bimerons in a magnetic disk, showcasing a potential new operation for future computing architectures. The discovery opens up novel spintronic applications based on different topological spin textures.
Researchers at the University of Innsbruck have developed a new architecture for universal quantum computers using parity-based qubits. This design reduces the complexity of implementing complex algorithms while also offering hardware-efficient error correction.
Researchers at MIT have developed a new method that uses optics to accelerate machine-learning computations on low-power devices. By encoding model components onto light waves, data can be transmitted rapidly and computations performed quickly, leading to over a hundredfold improvement in energy efficiency.
Researchers propose a new solution called labeled von Neumann architecture (LvNA) to tackle challenges in cloud computing. LvNA incorporates label-powered control mechanisms to differentiate, isolate, and prioritize user-defined application requests, mitigating resource contentions and guaranteeing performance.
A University at Buffalo-led research team has been awarded a $5 million grant to develop digital tools that can help older adults recognize and protect themselves from online deceptions. The project, DART, aims to reduce online fraud among older adults, who lose billions of dollars each year due to scams.
The new computer chip uses a transistor-free design that eliminates data transfer time and minimizes energy consumption. It offers up to 100 times faster performance than conventional computing architectures, making it ideal for AI applications.
Researchers at Stanford University have created a new chip architecture called NeuRRAM that performs AI computing directly within memory, reducing energy consumption and increasing efficiency. The chip has been tested on various AI tasks and shown high accuracy rates.
The NeuRRAM chip demonstrates wide range of AI applications with equivalent accuracy while reducing energy consumption by up to 70% compared to traditional compute platforms. It also supports various neural network models and architectures, enabling diverse AI applications on edge devices.
Researchers at Columbia University have developed a new verification technology for the Arm Confidential Compute Architecture, demonstrating the first formal verification of a prototype. This breakthrough enables the creation of confidential computing architectures that can protect sensitive user data.
Researchers at Carnegie Mellon University are developing a new approach to harness the power of nanosatellites, collecting data insights while in orbit and reducing latency issues. This initiative will lay groundwork for innovative applications in fields like carbon mapping, traffic management, and precision agriculture.
Researchers designed a modular AI chip that can be easily upgraded by swapping out layers, reducing the need for new devices. The chip uses optical communication to transmit information between layers, enabling high versatility in edge computing applications.
Researchers at University of Virginia are developing long-lived sensors for the Internet of Things (IoT) to reduce maintenance costs and upgrade challenges. The goal is to create an ecosystem that enables sensors to adapt to changing environments, reducing electronic waste.
A team of researchers from Waseda University developed a novel solution to efficiently solve complex optimization problems using Ising machines. Their hybrid algorithm reduces residual energy and reaches more optimal results in shorter time, increasing the machine's applicability across industries and sustainability practices.
Researchers at North Carolina State University have developed FAXID, a hardware-based approach for detecting ransomware that is significantly faster than software-based methods. In proof-of-concept testing, FAXID demonstrated accuracy comparable to XGBoost but with speeds up to 65.8 times faster.
Researchers have developed a new encryption technique that leverages hardware and software to improve file system security for next-generation non-volatile memories. This approach allows for faster performance than existing software security technologies, making it suitable for large data centers and cloud systems.
Researchers at Washington State University have demonstrated a way to make memristors using honey, which can mimic the work of human synapses and process data in memory. The honey memristor chips could lead to the development of neuromorphic computing systems that function like the human brain.
Researchers developed a new reading method for SOT-RAMs that can nullify the readout disturbance, reducing it by at least 10 times. The method involves creating a bi-directional read path, cancelling out the disturbances produced by spin currents.
GIST researchers propose a new strategy for crime prevention using artificial intelligence, trained on a large-scale dataset of deviant incident reports and corresponding images. The model, called DevianceNet, can accurately classify and detect deviant places, making it a useful tool in urban safety development.
Researchers developed DAGguise, a scheme that shapes memory requests into a predefined pattern to prevent contention attacks and enable faster computation. The technique represents programs' memory access requests as a graph, where each request is stored in a node, and the edges are time dependencies between requests.
Scientists have developed a new approach to mimic synapse functions using magneto-ionics, which drastically decreases power consumption. The study reveals that thinner films of cobalt oxide exhibit faster magnetization generation and can emulate 'learning' and 'forgetting' functionalities.
A study by the University of Texas at Austin found that software development teams given greater autonomy are more productive and have higher customer satisfaction rates. The researchers tested 461 projects over 50 months and found a 39% increase in value added for autonomous teams compared to traditional teams.
A team of scientists from Gwangju Institute of Science and Technology developed a deep learning-based approach to predict SC2 battle outcomes by considering army composition and terrain type. The proposed model leveraged parameter sharing, enabling it to analyze complex factors accurately and make predictions.
A new AI algorithm, APOLLO, accurately predicts microprocessor power consumption by analyzing just 100 signals out of millions, offering potential to improve efficiency and develop new processors. The technique has been validated on high-performance microprocessors and could help designers inform future chip design.
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.
The University of Texas at Arlington has received a $1.5 million grant from the US Department of Education to support domestic doctoral students specializing in Internet-of-Things study and research. The project aims to increase diversity among computer science researchers, with a focus on women and minorities.
Fred Martin, a UMass Lowell computer scientist, is being recognized for developing an educational framework that introduces robotics and AI to K-12 students. His work has guided the development of primary and secondary AI education initiatives worldwide.
A new brain-inspired computing device harnesses randomness to improve AI and machine learning performance. The device, called hetero-memristor, emulates the stochastic properties of neurons, allowing for more efficient optimization and reduced power consumption.
Scientists at Aarhus University are working on a nano-sized brain-inspired computer that can harvest its own energy, making it the smallest and most efficient AI system yet. The project aims to reduce power consumption by 12 orders of magnitude compared to modern supercomputers.
A new molecule discovered by researchers at University of Limerick in Ireland enables fast decision-making in computers, breaking the von Neumann bottleneck. The device can solve problems even if individual components fail, providing smaller, faster, and more energy-efficient computing.
Researchers at George Washington University have created a nanophotonic analog processor capable of solving partial differential equations. The processor can process arbitrary inputs at the speed of light and is integrated at chip-scale.
Researchers at Tokyo Institute of Technology developed a tunable neural network framework that achieves high accuracy and efficiency for sparse CNNs. The new architecture employs a Cartesian-product MAC array and pipelined activation aligners to enable dense computing of sparse convolution, resulting in better resource utilization.
Quantum engineers at the University of New South Wales have discovered a new technique to control millions of spin qubits, a critical step towards building a practical quantum computer. This breakthrough uses a novel component called a dielectric resonator to focus microwave power and deliver uniform magnetic fields across the chip.
Lehigh University researcher Roberto Palmieri aims to make RDMA technology even faster by revisiting a long-held theory. His goal is to enable all machines to interact with local memory, reducing latency and improving performance.
Columbia Engineering researchers have developed new techniques to bolster memory safety, creating a processor for the Air Force Research Lab. The novel solution, ZeRØ, protects code and data pointers without affecting system performance, while No-FAT speeds up fuzz testing and makes security checks faster with minimal impact on speed.
Margaret Martonosi's work on power-aware microarchitectures and narrow bit-widths has led to new fields of research. She has authored over 175 publications, including papers on dynamic thermal management and formal control-theoretic approaches for balancing power and performance.
A team of University of Virginia researchers has uncovered a new line of attack that breaks all Spectre defenses, leaving billions of computers and devices vulnerable to hackers. The attackers can steal data by exploiting micro-op caches, which have been built into Intel processors since 2011.
A new system called SpAtten enables more streamlined NLP with less computing power, achieving speeds of over 100 times faster than competing general-purpose processors and reducing energy consumption by over 1,000 times.
Researchers study the role of memristors in neuromorphic computing to mimic biological brain architectures. Memristor devices can memorize current to reduce device size and increase processing speed.
Researchers at EPFL's LANES laboratory have created a revolutionary circuit that combines logic operations and data storage into a single architecture, reducing energy losses and increasing efficiency. This breakthrough technology uses a 2D material called MoS2 to enable smaller, more powerful devices with improved performance.
A recent study proposes a collaborative system architecture that enables MNO-CSP collaboration to improve the performance of advanced 5G applications. By sharing information and resources, CSPs and MNOs can optimize their systems for better agility, flexibility, and efficiency.
Rice University researchers have demonstrated methods to optimize data-centric processing, improving energy efficiency by up to two orders of magnitude. Two complementary approaches, TIMELY and SmartExchange, were presented at ISCA 2020, leveraging innovative hardware architecture and co-designing with machine-learning algorithms.
Barroso's designs paired inexpensive hardware with powerful distributed systems software to dramatically change system design. His work led to the development of hyperscale datacenters and has had a significant impact on industry, resulting in reduced hardware and operating costs.
The ACM Transactions on Internet of Things (TIOT) journal chronicles the transformative development of the IoT. The journal covers a broad range of topics, including low-power wireless networking, embedded systems, data analytics, and security, with a strong emphasis on experimental validation.
Scientists at Tokyo Institute of Technology have developed a new processor architecture, STATICA, that can efficiently solve combinatorial optimization problems. The proposed system is fully connected and considers all spin-to-spin interactions, enabling parallel updating using stochastic cell automata, which reduces calculation time.
Researchers propose hybrid architectures to advance brain-inspired neuromorphic computing, focusing on operational functions needed to process information efficiently. The future of computing will not be about scaling components, but rethinking processor architecture to emulate brain efficiency.
The University of North Carolina at Chapel Hill is leading a $20 million project to create a platform for testing novel internet architectures. FABRIC, funded by the National Science Foundation, will allow scientists to explore what a new internet could look like at scale.
Researchers have developed a brain-inspired, analog neural network that provides probabilistic responses for complex decision-making. The device is more energy efficient and produces less heat than current computing architectures.