Computing Paradigms: Single, Parallel, Distributed

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Questions and Answers

Which computing paradigm is best suited for applications requiring high scalability and fault tolerance, but requires efficient communication?

  • Cloud Computing
  • Distributed Computing (correct)
  • Single Computing
  • Parallel Computing

Which of the following is a primary characteristic of edge computing that distinguishes it from cloud computing?

  • Dependence on consistent internet connectivity
  • Processing data closer to the source, reducing latency (correct)
  • Unlimited resources for processing data
  • Centralized data processing in large data centers

What is a key advantage of cloud computing over traditional computing paradigms?

  • Enhanced real-time processing capabilities
  • Lower dependency on internet connectivity
  • Greater control over physical hardware
  • Cost-efficiency and scalability through on-demand resources (correct)

In parallel computing, what is the primary role of 'shared memory'?

<p>To allow all processing units to access a common memory space (A)</p> Signup and view all the answers

What is the main advantage of using distributed computing for large-scale data analytics?

<p>Ability to process massive amounts of data by leveraging multiple nodes (C)</p> Signup and view all the answers

Which of the following best describes the 'ABA problem' in the context of lock-free data structures?

<p>A scenario where a value changes and reverts to its original state, misleading atomic operations. (C)</p> Signup and view all the answers

Which type of memory model is most likely to be implemented in distributed systems due to the delays in communication?

<p>Eventual Consistency (A)</p> Signup and view all the answers

In parallel computing, under what condition would Amdahl's Law predict minimal gains from increasing the number of processors?

<p>When a large portion of the program is inherently sequential. (B)</p> Signup and view all the answers

What role do 'memory barriers' play in ensuring correct execution in parallel computing?

<p>They enforce the ordering of memory operations to avoid race conditions. (C)</p> Signup and view all the answers

What is the primary goal of 'load balancing' in parallel computing?

<p>To distribute tasks evenly across processors to prevent bottlenecks (A)</p> Signup and view all the answers

Which of the following computing types is most suitable for cryptography, AI, and complex simulations, but is still under heavy research and requires specialized conditions?

<p>Quantum Computing (B)</p> Signup and view all the answers

Which of the following is a disadvantage of Parallel Computing?

<p>Expensive hardware and requires parallel programming (B)</p> Signup and view all the answers

Which feature is used to describe the ability of a system to handle increased load by adding more resources?

<p>Scalability (B)</p> Signup and view all the answers

Which of the following best describes the difference between concurrency and parallelism?

<p>Concurrency involves task overlap, while parallelism involves simultaneous execution. (D)</p> Signup and view all the answers

What is a 'critical section' in concurrent programming, and why is mutual exclusion important in this context?

<p>A section of code where shared resources are accessed; mutual exclusion avoids inconsistencies. (A)</p> Signup and view all the answers

Which of the following algorithms or techniques is used to solve mutual exclusion problems?

<p>Peterson's Algorithm (C)</p> Signup and view all the answers

Which condition is NOT necessary for a deadlock to occur?

<p>Preemption (C)</p> Signup and view all the answers

What is the primary function of 'cache coherence' protocols in shared-memory multiprocessor systems?

<p>To maintain consistency of data across multiple caches (C)</p> Signup and view all the answers

Which of the following techniques can help to minimize 'false sharing' in parallel programs?

<p>Aligning data to avoid sharing cache lines unintentionally (A)</p> Signup and view all the answers

In the context of interconnection networks, what is a primary advantage of a 'switched network'?

<p>Dynamic routing of communication between processors to reduce contention (C)</p> Signup and view all the answers

Flashcards

Single Computing

A computing approach that uses a single processor to execute tasks sequentially.

Parallel Computing

Computing that uses multiple processors or cores to perform tasks simultaneously.

Distributed Computing

Computing that uses multiple networked computers working together to complete tasks.

Cloud Computing

The delivery of computing services over the internet.

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Edge Computing

Processing data closer to the source, reducing latency.

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Mobile Computing

Computing performed on portable devices like smartphones and tablets.

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Quantum Computing

Computing that uses quantum bits to perform calculations exponentially faster than classical computers.

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Concurrency

Performing multiple tasks simultaneously.

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Parallelism

Simultaneous execution of multiple tasks to increase computational speed.

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Threads

Lightweight processes that share the same memory space within a process.

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Cores

Independent processing units within a single CPU.

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Shared Memory

A memory architecture where multiple processors access a common memory pool.

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Synchronization

Coordination mechanisms that ensure proper execution when multiple threads access shared resources.

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Granularity

Indicates the amount of work or data each task performs in parallel computing.

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Load Balancing

Distributing work evenly across processors to avoid idle time and maximize performance.

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Amdahl's Law

The part of a program that cannot be parallelized limits potential speedup.

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Node

An independent computing device in a distributed system.

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Cluster

A group of interconnected nodes working together as a single system.

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Speedup

The ratio of the time taken to solve a problem on a single processor to the time taken on multiple processors.

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Efficiency

Measure of how effectively computational resources are utilized.

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Study Notes

Computing Paradigms Overview

  • Different methods for structuring computer architecture to execute tasks

Single Computing

  • Uses a single processor
  • Executes tasks sequentially
  • Simple and cost-effective
  • Limited performance
  • Suited for personal computers and embedded systems

Parallel Computing

  • Employs multiple processors or cores
  • Executes tasks simultaneously
  • Achieves faster execution for complex computations
  • Used in AI and scientific computing
  • Examples: multi-core processors, GPUs, supercomputers

Distributed Computing

  • Multiple networked computers collaborate
  • Computers work together to complete tasks
  • Highly scalable and fault-tolerant
  • Requires efficient communication
  • Applies to cloud computing, blockchain, and big data clusters

Cloud Computing

  • Delivers computing services, including storage, processing, and software via the internet
  • Cost-efficient and scalable
  • Depends on internet connectivity
  • Examples include AWS, Google Cloud, and Microsoft Azure

Edge Computing

  • Processes data closer to the source, like IoT devices
  • Reduces latency and enhances real-time processing
  • Limited resources
  • Examples include smart cities, autonomous vehicles, and IoT

Mobile Computing

  • Allows computing on portable devices like smartphones and tablets
  • Convenient and mobile
  • Limited by hardware and battery life
  • Smartphones, tablets, and laptops

Quantum Computing

  • Employs quantum bits (qubits) to achieve exponentially faster calculations
  • Useful for cryptography, AI, and simulations
  • Still under research and development
  • Examples include IBM Quantum, Google Sycamore, and D-Wave

Advantages & Disadvantages of Paradigms

Single Computing

  • Advantages: Simple, cost-effective, and easy to maintain.
  • Disadvantages: Slow performance, limited scalability.

Parallel Computing

  • Advantages: Faster processing, efficient for complex tasks.
  • Disadvantages: Expensive hardware, requires parallel programming.

Distributed Computing

  • Advantages: Scalable, high fault tolerance, efficient resource utilization
  • Disadvantages: High communication overhead, security concerns

Cloud Computing

  • Advantages: On-demand resources, cost-effective, scalable.
  • Disadvantages: Internet dependency, potential security risks.

Edge Computing

  • Advantages: Low latency, real-time processing, reduces cloud workload.
  • Disadvantages: Limited processing power, potential security issues.

Mobile Computing

  • Advantages: Portable, flexible, convenient.
  • Disadvantages: Battery limitations, lower processing power.

Quantum Computing

  • Advantages: Exponentially faster for complex problems, future potential.
  • Disadvantages: Expensive, still in early development, requires special conditions.

Comparative Analysis of Computing Paradigms

  • These factors help compare different paradigms
  • Processing Unit: Single CPU, Multiple CPUs/Cores, Multiple computers, Virtual Resources, Local IoT devices, Mobile devices, Qubits
  • Execution: Sequential, Parallel, Distributed Tasks, Cloud-based, Real-time, On-device, Quantum
  • Speed: Slow, Fast, Network Dependent, High Speed, Moderate, Exponentially Fast
  • Scalability: Low, Moderate, High, Very High, Quantum type has High Scalability
  • Fault Tolerance: Low, Moderate, High, Still Evolving
  • Cost: Low, Moderate, (Hardware or Infrastructure), Very High
  • Best for: Basic tasks, Scientific tasks, Cloud, IoT, Mobile, Cryptography

Summary of Computing Paradigms

  • Single Computing: Suitable for personal and small tasks.
  • Parallel Computing: Ideal for AI, simulations, and performance-intensive tasks.
  • Distributed Computing: Used in cloud-based services, big data, and large-scale applications.
  • Cloud Computing: Provides scalable online services and computing resources.
  • Edge Computing: Best for IoT and real-time applications with low latency.
  • Mobile Computing: Enables portable computing with smartphones, tablets, and laptops.
  • Quantum Computing: A future technology capable of solving complex problems exponentially faster.

Overview of Single Computing

  • Relies on one processor to perform tasks
  • Differs from parallel/distributed computing

Characteristics of Single Computing

  • Uses single CPU to execute instructions
  • Tasks done in linear sequence
  • Limited processing power
  • Simple design, easy to implement
  • System does not rely on networks for processing

Types of Single Computing Systems

  • Single-core processing handles all tasks
  • Early PCs and embedded systems are examples
  • Single-user system design
  • Personal Computer(PC) an example
  • Executes tasks in a single task (MS-DOS)
  • Shares time to run all tasks but relies on single CPU (Windows, macOS)
  • Embedded systems dedicate tasks to appliances
  • A microcontroller is an example of embedded systems

Benefits of Single Computing

  • Lower hardware costs
  • Consumes less power
  • Easy to operate
  • Reliable as the system has low chances of failure

Drawbacks of Single Computing

  • Cannot handle extensive computation well
  • Slower than multi-core
  • Cannot be upgraded easily to handle higher workloads
  • I/O operations overload and cause bottlenecks

Applications of Single Computing

  • Used in personal computers
  • Used in laptops and workstations
  • Embedded systems are an example
  • Used for simple data processing tasks
  • Used in small business servers

Conclusion of Single Computing

  • Ideal for less intensive applications
  • Essential for personal and embedded systems

Comparison of Computing

  • Sequential is used for single computing while parallel is used for parallel processing
  • Single CPU for single computing, multiple for parallel or distributed
  • Execution done in time for single, processed in parallel for others
  • Faster processing for parallel, even faster for distributed
  • Scalability is distributed, network determines it
  • Fault tolerance high for distributed
  • Communication overhead none for single unit, required for networked

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