Computer Architecture: Difference between revisions

Revision as of 09:32, 6 July 2025

Computer Architecture is the conceptual design and fundamental operational structure of a computer system. It encompasses the various components that constitute the hardware and outlines the performance characteristics of those components, as well as the methods for connecting them to enable efficient operation. This discipline combines aspects of electrical engineering and computer science, giving rise to a rich field of study that covers a wide variety of topics, including instruction set architecture (ISA), microarchitecture, memory hierarchy, system interconnects, and the integration of hardware and software.

History

The origins of computer architecture can be traced back to the early developments in computing during the mid-20th century. The first electronic computers, such as the ENIAC (Electronic Numerical Integrator and Computer), laid the groundwork for future architectures. It was programmable but not easily reconfigurable or generalizable, leading to the development of the von Neumann architecture. Proposed by John von Neumann in 1945, this architecture introduced the concept of a stored-program computer, which allowed instructions and data to reside in the same memory, fundamentally changing the way computers processed information.

Over the following decades, various architectures emerged, driven by technology advancements and evolving computational needs. The Burroughs large systems in the 1960s introduced the concept of an architectural approach that integrated concurrent processing, while the introduction of RISC (Reduced Instruction Set Computing) and CISC (Complex Instruction Set Computing) architectures in the 1980s further refined how processors were designed. RISC architecture, which simplifies the set of instructions the CPU must handle, contrasts with CISC, which aims to accomplish more complex tasks with fewer lines of assembly code.

With the rise of parallel processing in the 1990s, computer architecture began to embrace multi-core processors and multi-threading capabilities, enabling more efficient use of resources. The late 20th and early 21st centuries saw the emergence of distributed systems and cloud computing, leading to new architectural paradigms. Contemporary architectures focus not only on processing power and efficiency but also on energy consumption and fault tolerance, reflecting a growing concern for sustainability and reliability in computing.

Architectural Models

Computer architecture can be broadly classified into a few distinct models that govern their design and functionality. These models influence how computer systems process data and manage resources effectively.

Von Neumann Architecture

The von Neumann architecture, foundational to most traditional computer systems, consists of components such as the central processing unit (CPU), memory, and input/output devices. One of the defining features of this architecture is the stored-program concept, which allows instructions to be stored in the same memory unit as data. This architecture's simplicity has contributed to its widespread use and served as the foundation for numerous subsequent models. However, the von Neumann bottleneck, a limitation caused by a single data bus for all computations, poses challenges for throughput in modern systems.

Harvard Architecture

In contrast, the Harvard architecture separates storage and signal pathways for instructions and data, allowing simultaneous access to both. This dual-bus design improves data throughput and is particularly useful in applications where performance is critical, such as digital signal processing (DSP) and certain embedded systems. The architecture facilitates the execution of multiple instructions in parallel, a key feature of modern high-performance CPUs. However, the complexity of the design can lead to increased costs and reduced flexibility in general-purpose computations.

RISC and CISC Architectures

RISC (Reduced Instruction Set Computing) architectures focus on a small, highly optimized instruction set executed within a single cycle, promoting faster performance through pipelining techniques. In contrast, CISC (Complex Instruction Set Computing) architectures include a wider variety of instructions that can often execute multi-step operations, which may reduce the number of instructions required for a particular task but can also lead to performance inefficiencies due to the complexity of decoding these instructions. The debate between RISC and CISC has significantly influenced the design of modern CPUs, with many contemporary systems incorporating elements of both models to harmonize performance and flexibility.

Components of Computer Architecture

The study of computer architecture encompasses several key components, each contributing to the overall functionality and efficiency of a system.

Central Processing Unit (CPU)

The CPU, often referred to as the brain of the computer, carries out instructions from computer programs through arithmetic, logic, control, and input/output operations. The CPU comprises several critical units, including the arithmetic logic unit (ALU), which performs mathematical and logical operations, and the control unit (CU), which manages the movement of data within the CPU and orchestrates overall operations based on instruction flow. The development of multi-core CPUs has allowed for greater parallel processing capabilities, significantly enhancing computational power and efficiency for various applications.

Memory Hierarchy

The memory hierarchy is instrumental in determining system performance, comprising several levels of storage that vary in speed and cost. Typically, the memory hierarchy includes registers, cache memory, main memory (RAM), and secondary storage (hard drives and SSDs). High-speed registers and cache are employed to provide rapid access to frequently used data, significantly improving processing speeds while reducing reliance on slower main memory and storage devices. Optimization of the memory hierarchy is a critical focus in modern computer architecture, as bottlenecks in data retrieval can lead to significant slowdowns in overall system performance.

Input/Output (I/O) Systems

Input/output systems serve as the interface between the computer system and the external environment. Efficient I/O management is vital to maintaining system performance, given that peripheral devices can vary significantly in speed and capacity. Various I/O models exist, including polling, interrupts, and direct memory access (DMA). Each model has its own benefits and trade-offs, affecting how data is transferred between the CPU and peripheral devices. Recent advances have introduced technologies that allow for faster and more efficient communication, such as NVMe (Non-Volatile Memory Express) for solid-state drives.

Modern Architectures

With rapid advancements in technology, several modern computer architectures have emerged, each tailored to specific applications while challenging conventional models.

High-Performance Computing (HPC)

High-Performance Computing systems utilize architectures designed to handle large-scale computations rapidly. These systems often employ clusters of interconnected computers that can effectively share resources, a configuration that is often seen in supercomputers. HPC architectures focus on maximizing floating-point operations per second (FLOPS) through parallel processing and optimized memory utilization, proving essential for scientific simulations, complex calculations, and data-intensive applications. Furthermore, advances in graphics processing units (GPUs) have transformed HPC, as their design allows for highly parallelized mathematical computations which are particularly advantageous in fields such as machine learning and artificial intelligence.

Embedded Systems

Embedded systems are specialized computing systems designed to perform dedicated tasks within larger systems. These devices often feature constraints on power, size, and processing capabilities, distinguishing them from general-purpose computers. Architectures used in embedded systems prioritize efficiency and performance, often utilizing microcontrollers and system-on-chip (SoC) designs. Common applications include autonomous vehicles, industrial automation, and consumer electronics like smart home devices. The surge in IoT (Internet of Things) has led to the development of increasingly energy-efficient embedded architectures to support connectivity and real-time data processing.

Cloud Computing Architectures

The rise of cloud computing has revolutionized how organizations deploy and manage computing resources. Cloud architectures often utilize distributed computing models that abstract hardware complexities and allow for scalable, on-demand resource utilization. Users can access vast pools of computing power through virtualization technologies, enabling businesses and individuals to deploy applications without the need for substantial physical infrastructure. This shift has spurred new considerations in architecture design, focusing on resource allocation, load balancing, and fault tolerance to ensure reliable service delivery.

Applications and Implications

Computer architecture plays a crucial role in a myriad of applications across different sectors, influencing how technology is integrated into daily life and industry.

Consumer Electronics

Consumer electronics leverage sophisticated computer architectures to enhance functionality and performance. Smartphones, tablets, and smart home devices depend on compact and energy-efficient designs that enable complex processing in a portable form. The advent of highly integrated SoC architectures has made it possible to include enhanced graphics capabilities, connectivity options, and user interfaces within these small devices, directly impacting user experience and functionality.

Data Centers and Enterprise Solutions

Data centers utilize advanced computer architectures designed for reliability and high availability. Critical enterprise applications often run on multi-tier architectures that prioritize transactions and data security, leveraging distributed systems for load balancing and redundancy. The architecture of data centers enables them to process vast amounts of data, support high transactional capacities, and maintain performance in operations ranging from web hosting to financial transactions.

Scientific Research and Simulation

In the realm of scientific research, computer architecture is fundamental for running simulations and processing large datasets. The performance of scientific applications frequently depends on advancements in hardware, such as enhanced memory capabilities and specialized processing units (e.g., GPUs). This reliance on cutting-edge architecture allows researchers to explore complex simulations in fields like climate modeling, genetics, and particle physics, driving forward our understanding in those domains.

Challenges and Future Directions

As technology continues to evolve, several significant challenges and opportunities within computer architecture must be addressed.

Power Efficiency

The drive towards greater computational performance leads to increasing power demands, prompting researchers and architects to explore solutions that optimize energy consumption. Innovations such as dynamic voltage and frequency scaling (DVFS), low-power design techniques, and energy-aware processing can significantly reduce the environmental impact of computing. As data centers and high-performance systems account for substantial energy use globally, addressing power efficiency is a pressing concern for future architectural designs.

Security Concerns

With the growing interconnectedness of computer systems comes an exacerbated risk of security vulnerabilities. Hardware security has become an essential focus within architecture research, leading to developments in secure computing environments, hardware-based isolation mechanisms, and trusted execution environments. Addressing these security challenges is pivotal to maintaining system integrity and protecting sensitive data in a landscape where cyber threats are continually evolving.

Adaptation to Emerging Technologies

The rise of artificial intelligence, machine learning, and quantum computing presents both challenges and opportunities for computer architecture. Architectures that best leverage specialized hardware and parallel processing capabilities are increasingly critical in training and deploying AI models. Likewise, the nascent field of quantum computing requires entirely new architectural paradigms that address fundamentally different operational methods and incorporate qubits and quantum gates. Adapting to and capitalizing on these emerging technologies will define the next generation of computer architecture.

References

Intel - What is Computer Architecture?
IBM - Insights into Modern Computer Architecture
Oracle - Understanding Computer Architecture
AMD - An Overview of Computer Architecture
NVIDIA - Introduction to Computer Architecture

@@ Line 1: / Line 1: @@
-'''Computer Architecture''' is a comprehensive framework that defines the structure and organization of a computer's hardware components along with their interconnections. It serves as the blueprint for designing computer systems, influencing performance, efficiency, and functionality. This field covers a wide range of topics, including the design of instruction sets, data processing capabilities, control flow mechanisms, and input/output operations.
+'''Computer Architecture''' is the conceptual design and fundamental operational structure of a computer system. It encompasses the various components that constitute the hardware and outlines the performance characteristics of those components, as well as the methods for connecting them to enable efficient operation. This discipline combines aspects of electrical engineering and computer science, giving rise to a rich field of study that covers a wide variety of topics, including instruction set architecture (ISA), microarchitecture, memory hierarchy, system interconnects, and the integration of hardware and software.
-== Background ==
+== History ==
-Computer architecture has its roots in early computing devices that emerged in the mid-20th century. The evolution of this discipline can be traced back to the vacuum tube technology used in mainframe computers of the 1940s and 1950s. As technology advanced, the introduction of transistors revolutionized computing by allowing for more compact and energy-efficient designs. The concept of architecture, as it relates to computer systems, became more formalized with the development of Integrated Circuits (ICs) in the 1960s, which further enabled increased computational power and complexity.
-Researchers such as John von Neumann made significant contributions to the underlying principles of architecture with the introduction of the von Neumann architecture. This model describes a system where program instructions and data are stored in the same memory space, allowing for a simple design that is still foundational in modern computer systems. Over the years, various architectures have emerged, including Reduced Instruction Set Computing (RISC) and Complex Instruction Set Computing (CISC), each catering to different use cases and performance needs.
+The origins of computer architecture can be traced back to the early developments in computing during the mid-20th century. The first electronic computers, such as the ENIAC (Electronic Numerical Integrator and Computer), laid the groundwork for future architectures. It was programmable but not easily reconfigurable or generalizable, leading to the development of the von Neumann architecture. Proposed by John von Neumann in 1945, this architecture introduced the concept of a stored-program computer, which allowed instructions and data to reside in the same memory, fundamentally changing the way computers processed information.
-== Architecture ==
+Over the following decades, various architectures emerged, driven by technology advancements and evolving computational needs. The Burroughs large systems in the 1960s introduced the concept of an architectural approach that integrated concurrent processing, while the introduction of RISC (Reduced Instruction Set Computing) and CISC (Complex Instruction Set Computing) architectures in the 1980s further refined how processors were designed. RISC architecture, which simplifies the set of instructions the CPU must handle, contrasts with CISC, which aims to accomplish more complex tasks with fewer lines of assembly code.
-The architecture of a computer system is broadly categorized into three essential layers: the hardware architecture, instruction set architecture, and the microarchitecture. Understanding these components is crucial for grasping how computer systems operate.
-=== Hardware Architecture ===
+With the rise of parallel processing in the 1990s, computer architecture began to embrace multi-core processors and multi-threading capabilities, enabling more efficient use of resources. The late 20th and early 21st centuries saw the emergence of distributed systems and cloud computing, leading to new architectural paradigms. Contemporary architectures focus not only on processing power and efficiency but also on energy consumption and fault tolerance, reflecting a growing concern for sustainability and reliability in computing.
-Hardware architecture encompasses the physical components of a computer system, including the central processing unit (CPU), memory, storage devices, and input/output interfaces. The design of these components impacts the overall performance and capabilities of the computer. For example, advancements in multicore processors have led to improved performance through parallel processing techniques.
-One critical aspect of hardware architecture is the bus system, which facilitates communication between different components. Various types of buses, such as data buses and address buses, play integral roles in data transfer and retrieval from memory.
+== Architectural Models ==
-=== Instruction Set Architecture ===
+Computer architecture can be broadly classified into a few distinct models that govern their design and functionality. These models influence how computer systems process data and manage resources effectively.
-The instruction set architecture (ISA) defines the set of instructions that a CPU can understand and execute. It serves as the interface between software and hardware, allowing programs to perform operations such as arithmetic calculations, data manipulation, and control functions. ISAs can be classified into two primary categories: RISC and CISC.
-RISC architectures focus on a small set of simple instructions that execute in a single clock cycle, leading to efficient pipeline utilization. In contrast, CISC architectures feature a more extensive instruction set that includes more complex operations, which can reduce the number of instructions needed for certain tasks but may increase execution time.
+=== Von Neumann Architecture ===
+The von Neumann architecture, foundational to most traditional computer systems, consists of components such as the central processing unit (CPU), memory, and input/output devices. One of the defining features of this architecture is the stored-program concept, which allows instructions to be stored in the same memory unit as data. This architecture's simplicity has contributed to its widespread use and served as the foundation for numerous subsequent models. However, the von Neumann bottleneck, a limitation caused by a single data bus for all computations, poses challenges for throughput in modern systems.
+=== Harvard Architecture ===
-=== Microarchitecture ===
+In contrast, the Harvard architecture separates storage and signal pathways for instructions and data, allowing simultaneous access to both. This dual-bus design improves data throughput and is particularly useful in applications where performance is critical, such as digital signal processing (DSP) and certain embedded systems. The architecture facilitates the execution of multiple instructions in parallel, a key feature of modern high-performance CPUs. However, the complexity of the design can lead to increased costs and reduced flexibility in general-purpose computations.
-Microarchitecture refers to the concrete implementation of the ISA within a CPU. It covers the internal organization of the processor, including the data paths, control units, and the way instructions are executed. Innovations in microarchitecture have been pivotal in enhancing performance, such as techniques like speculative execution, out-of-order execution, and superscalar architectures.
-Modern processors often implement features such as caches to enhance memory access speed. The hierarchy of cache (L1, L2, and L3) plays a significant role in balancing latency and bandwidth.
+=== RISC and CISC Architectures ===
-== Implementation and Applications ==
+RISC (Reduced Instruction Set Computing) architectures focus on a small, highly optimized instruction set executed within a single cycle, promoting faster performance through pipelining techniques. In contrast, CISC (Complex Instruction Set Computing) architectures include a wider variety of instructions that can often execute multi-step operations, which may reduce the number of instructions required for a particular task but can also lead to performance inefficiencies due to the complexity of decoding these instructions. The debate between RISC and CISC has significantly influenced the design of modern CPUs, with many contemporary systems incorporating elements of both models to harmonize performance and flexibility.
-The practical implementations of computer architecture are vast and varied. Different types of computer systems exhibit distinct architectural designs tailored for their specific applications. This section explores various implementations in personal computing, servers, and specialized systems.
-=== Personal Computing ===
+== Components of Computer Architecture ==
-In personal computing, the architecture largely revolves around the desktop and mobile systems designed for everyday users. Most personal computers today utilize a variation of the x86 architecture, a CISC design that supports a broad range of software applications. The performance requirements for personal computers have led to the adoption of multicore processors that enable multitasking and enhance user experience.
-=== Server Architecture ===
+The study of computer architecture encompasses several key components, each contributing to the overall functionality and efficiency of a system.
-Server architecture is characterized by a focus on scalability, reliability, and power efficiency. Servers often use RISC architectures due to their performance advantages in handling concurrent requests. Furthermore, in cloud computing environments, server architectures can be designed around virtualization and containerization, optimizing resource utilization and allowing flexible deployment of services.
+=== Central Processing Unit (CPU) ===
+The CPU, often referred to as the brain of the computer, carries out instructions from computer programs through arithmetic, logic, control, and input/output operations. The CPU comprises several critical units, including the arithmetic logic unit (ALU), which performs mathematical and logical operations, and the control unit (CU), which manages the movement of data within the CPU and orchestrates overall operations based on instruction flow. The development of multi-core CPUs has allowed for greater parallel processing capabilities, significantly enhancing computational power and efficiency for various applications.
+=== Memory Hierarchy ===
+The memory hierarchy is instrumental in determining system performance, comprising several levels of storage that vary in speed and cost. Typically, the memory hierarchy includes registers, cache memory, main memory (RAM), and secondary storage (hard drives and SSDs). High-speed registers and cache are employed to provide rapid access to frequently used data, significantly improving processing speeds while reducing reliance on slower main memory and storage devices. Optimization of the memory hierarchy is a critical focus in modern computer architecture, as bottlenecks in data retrieval can lead to significant slowdowns in overall system performance.
+=== Input/Output (I/O) Systems ===
+Input/output systems serve as the interface between the computer system and the external environment. Efficient I/O management is vital to maintaining system performance, given that peripheral devices can vary significantly in speed and capacity. Various I/O models exist, including polling, interrupts, and direct memory access (DMA). Each model has its own benefits and trade-offs, affecting how data is transferred between the CPU and peripheral devices. Recent advances have introduced technologies that allow for faster and more efficient communication, such as NVMe (Non-Volatile Memory Express) for solid-state drives.
+== Modern Architectures ==
+With rapid advancements in technology, several modern computer architectures have emerged, each tailored to specific applications while challenging conventional models.
+=== High-Performance Computing (HPC) ===
+High-Performance Computing systems utilize architectures designed to handle large-scale computations rapidly. These systems often employ clusters of interconnected computers that can effectively share resources, a configuration that is often seen in supercomputers. HPC architectures focus on maximizing floating-point operations per second (FLOPS) through parallel processing and optimized memory utilization, proving essential for scientific simulations, complex calculations, and data-intensive applications. Furthermore, advances in graphics processing units (GPUs) have transformed HPC, as their design allows for highly parallelized mathematical computations which are particularly advantageous in fields such as machine learning and artificial intelligence.
 === Embedded Systems ===
-Embedded systems represent a specialized segment where architecture is designed for specific tasks within larger systems, such as automotive controls, home appliances, and medical devices. These systems typically utilize microcontrollers and are optimized for power efficiency, cost-effectiveness, and real-time operation, demonstrating a divergence from general-purpose computing.
-== Real-world Examples ==
+Embedded systems are specialized computing systems designed to perform dedicated tasks within larger systems. These devices often feature constraints on power, size, and processing capabilities, distinguishing them from general-purpose computers. Architectures used in embedded systems prioritize efficiency and performance, often utilizing microcontrollers and system-on-chip (SoC) designs. Common applications include autonomous vehicles, industrial automation, and consumer electronics like smart home devices. The surge in IoT (Internet of Things) has led to the development of increasingly energy-efficient embedded architectures to support connectivity and real-time data processing.
-Understanding computer architecture is made clearer through various real-world examples that illustrate its diverse applications in technology.
-=== Von Neumann Architecture ===
+=== Cloud Computing Architectures ===
-The von Neumann architecture remains a cornerstone of modern computing, exemplifying a model where data and instructions share a common memory. This architecture is employed in countless devices, from personal computers to embedded systems, ensuring compatibility and facilitation of processing tasks.
+The rise of cloud computing has revolutionized how organizations deploy and manage computing resources. Cloud architectures often utilize distributed computing models that abstract hardware complexities and allow for scalable, on-demand resource utilization. Users can access vast pools of computing power through virtualization technologies, enabling businesses and individuals to deploy applications without the need for substantial physical infrastructure. This shift has spurred new considerations in architecture design, focusing on resource allocation, load balancing, and fault tolerance to ensure reliable service delivery.
+== Applications and Implications ==
+Computer architecture plays a crucial role in a myriad of applications across different sectors, influencing how technology is integrated into daily life and industry.
+=== Consumer Electronics ===
+Consumer electronics leverage sophisticated computer architectures to enhance functionality and performance. Smartphones, tablets, and smart home devices depend on compact and energy-efficient designs that enable complex processing in a portable form. The advent of highly integrated SoC architectures has made it possible to include enhanced graphics capabilities, connectivity options, and user interfaces within these small devices, directly impacting user experience and functionality.
+=== Data Centers and Enterprise Solutions ===
+Data centers utilize advanced computer architectures designed for reliability and high availability. Critical enterprise applications often run on multi-tier architectures that prioritize transactions and data security, leveraging distributed systems for load balancing and redundancy. The architecture of data centers enables them to process vast amounts of data, support high transactional capacities, and maintain performance in operations ranging from web hosting to financial transactions.
+=== Scientific Research and Simulation ===
+In the realm of scientific research, computer architecture is fundamental for running simulations and processing large datasets. The performance of scientific applications frequently depends on advancements in hardware, such as enhanced memory capabilities and specialized processing units (e.g., GPUs). This reliance on cutting-edge architecture allows researchers to explore complex simulations in fields like climate modeling, genetics, and particle physics, driving forward our understanding in those domains.
+== Challenges and Future Directions ==
+As technology continues to evolve, several significant challenges and opportunities within computer architecture must be addressed.
-=== ARM Architecture ===
+=== Power Efficiency ===
-The ARM architecture has gained prominence in mobile devices due to its energy efficiency and performance capabilities. ARM processors are widely used in smartphones, tablets, and even in single-board computers like the Raspberry Pi, demonstrating the versatility of RISC architectures in addressing various computing needs.
-=== Graphics Processing Units ===
+The drive towards greater computational performance leads to increasing power demands, prompting researchers and architects to explore solutions that optimize energy consumption. Innovations such as dynamic voltage and frequency scaling (DVFS), low-power design techniques, and energy-aware processing can significantly reduce the environmental impact of computing. As data centers and high-performance systems account for substantial energy use globally, addressing power efficiency is a pressing concern for future architectural designs.
-Graphics Processing Units (GPUs) introduced an architecture distinctly designed for parallel processing, optimizing performance in graphics rendering and computationally intensive tasks such as deep learning and scientific simulations. The architecture of GPUs contrasts significantly with traditional CPUs, yet both play critical roles in achieving high-performance computing.
-== Criticism and Limitations ==
+=== Security Concerns ===
-Despite the advancements in computer architecture, several criticisms and limitations persist within the field. These challenges impact both performance and efficiency in practical applications.
-=== Performance Bottlenecks ===
+With the growing interconnectedness of computer systems comes an exacerbated risk of security vulnerabilities. Hardware security has become an essential focus within architecture research, leading to developments in secure computing environments, hardware-based isolation mechanisms, and trusted execution environments. Addressing these security challenges is pivotal to maintaining system integrity and protecting sensitive data in a landscape where cyber threats are continually evolving.
-One significant criticism lies in performance bottlenecks associated with memory access. The speed disparity between the CPU and main memory can hinder system performance, necessitating the use of multi-level caching and optimized algorithms to reduce latency.
-=== Complexity and Cost ===
+=== Adaptation to Emerging Technologies ===
-The increasing complexity of both hardware and software architectures can lead to higher development costs and longer design cycles. The sophistication required in modern architectures poses challenges in debugging and verification processes, potentially introducing design flaws.
-=== Energy Consumption ===
+The rise of artificial intelligence, machine learning, and quantum computing presents both challenges and opportunities for computer architecture. Architectures that best leverage specialized hardware and parallel processing capabilities are increasingly critical in training and deploying AI models. Likewise, the nascent field of quantum computing requires entirely new architectural paradigms that address fundamentally different operational methods and incorporate qubits and quantum gates. Adapting to and capitalizing on these emerging technologies will define the next generation of computer architecture.
-Energy consumption remains a critical area of concern, particularly in large-scale data centers where operational costs are heavily influenced by power usage. Striking a balance between performance and energy efficiency is vital for sustainable computing practices, driving ongoing research into low-power architectures and technologies.
 == See also ==
-* [[Von Neumann architecture]]
+* [[Computer Science]]
-* [[Processor architecture]]
+* [[Embedded System]]
-* [[RISC]]
-* [[CISC]]
 * [[Microprocessor]]
+* [[Parallel Computing]]
+* [[Graphical Processing Unit]]
+* [[Cloud Computing]]
 == References ==
-* [https://www.intel.com/content/www/us/en/computer-architecture/what-is-computer-architecture.html Intel: What is Computer Architecture?]
+* [https://www.intel.com/content/www/us/en/comarchitecture/what-is-computer-architecture.html Intel] - What is Computer Architecture?
-* [https://www.arm.com/architecture ARM: Architecture Overview]
+* [https://www.ibm.com/cloud/learn/computer-architecture IBM] - Insights into Modern Computer Architecture
-* [https://www.semanticscholar.org/paper/Computer-Architecture-and-Instruction-Set-Duval-Price/2b6dc3b30b292e8d3082411d75c2482dda843092 Computer Architecture and Instruction Set]
+* [https://www.oracle.com/what-is/computer-architecture.html Oracle] - Understanding Computer Architecture
-* [https://www.microsoft.com/en-us/research/wp-content/uploads/2016/06/ComputerArchitecture.pdf Microsoft Research on Computer Architecture]
+* [https://www.amd.com/en/technologies/computer-architecture AMD] - An Overview of Computer Architecture
-* [https://www.nvidia.com/en-us/deep-learning-ai/solutions/what-is-a-gpu/ NVIDIA: What is a GPU?]
+* [https://www.nvidia.com/en-us/deep-learning-ai/education/what-is-computer-architecture/ NVIDIA] - Introduction to Computer Architecture
 [[Category:Computer science]]
 [[Category:Computer engineering]]
-[[Category:Computer hardware]]
+[[Category:Computer systems]]