Parallel Processing Unit 1
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Questions and Answers

What is the relationship between speed and the complexity of chip structures?

  • Speed is independent of the structure complexity.
  • More speed is associated with complex structures. (correct)
  • More speed is achieved with simpler structures.
  • Less speed is associated with more complex structures.

    • Which design approach is suggested for building more power-efficient chips?

  • Maximizing the clock speed of processors.
  • Utilizing more, simpler processors. (correct)
  • Implementing fewer, more complex processors.
  • Increasing the complexity of the control hardware.

    • What does decreasing latency primarily focus on in chip design?

  • Increasing the speed of task completion. (correct)
  • Completing tasks in more time.
  • Increasing the complexity of the tasks.
  • Reducing the number of tasks processed.

    • What differentiates multi-core CPUs from GPUs, according to the content?

    <p>Multi-core CPUs can handle both sequential and parallel programming. (A)</p> Signup and view all the answers

    What is the primary focus of GPU design?

    <p>Optimizing for throughput rather than latency. (B)</p> Signup and view all the answers

    Which of the following is NOT a traditional way hardware designers make computers run faster?

    <p>Longer Clock Period (C)</p> Signup and view all the answers

    What is a key feature of modern GPUs that distinguishes them from traditional CPUs?

    <p>Hundreds of processors (C)</p> Signup and view all the answers

    What has primarily contributed to the increased processing capability of today’s computers?

    <p>More transistors available for computation (D)</p> Signup and view all the answers

    Why are traditional CPU-like processors considered less energy efficient compared to GPU-like processors?

    <p>They have complex control hardware (A)</p> Signup and view all the answers

    What is one of the main challenges in programming for modern parallel computing?

    <p>Adapting to a different programming model (D)</p> Signup and view all the answers

    Which comparison best illustrates the concept of parallel processing?

    <p>Using two strong oxen for plowing fields (B)</p> Signup and view all the answers

    What has limited the ability to keep increasing the clock speed of a single processor?

    <p>Power and heat generation (D)</p> Signup and view all the answers

    What does GPGPU stand for, and what does it signify?

    <p>General Purpose GPU; it indicates the versatility of GPUs for general computing tasks (A)</p> Signup and view all the answers

    Flashcards

    Parallel Processing

    Using multiple processors to perform tasks simultaneously, improving speed and efficiency.

    Moore's Law

    The observation that the number of transistors in an integrated circuit doubles approximately every two years, leading to more powerful and smaller computing devices

    Clock Speed (limit)

    The maximum speed at which a computer's processor can execute instructions, a factor no longer significantly increasing speed.

    Multiprocessors

    A system that uses multiple processing units to perform work, increasing speed compared to a single processor.

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    Power Efficiency (GPU-like)

    Building simple processors, using more transistors for data paths, to improve power usage and performance.

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    Traditional CPUs

    Central Processing Units, known for flexibility and performance, but less power-efficient than more specialized designs

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    GPGPU (General Purpose computation on GPUs)

    Utilizing Graphics Processing Units (GPUs) for general-purpose computing tasks.

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    More Transistors = More Computation

    Increasing the number of transistors in a processor directly leads to greater computational capacity.

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    Power Efficiency Techniques in Chips

    Computer designers use fewer, more complex processors to create power-efficient chips.

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    Power Efficiency Goals

    Power efficiency aims for reduced latency (time to complete a task) and increased throughput (tasks per unit time).

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    CPU vs. GPU Design

    CPUs prioritize decreasing latency, while GPUs prioritize increasing throughput for parallel tasks.

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    GPU's Parallelism

    GPUs excel at parallel programming by having many simple processing units, not relying on the compiler to distribute tasks.

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    GPU Design Focus

    GPUs optimize for throughput, not latency, making them suitable for tasks requiring high processing speed per unit time.

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    Study Notes

    Parallel Processing Unit 1

    • Parallel processing is a method of computation where multiple calculations are carried out simultaneously rather than sequentially.
    • Hardware designers use traditional methods to make computers faster, these include faster clocks, more work per clock cycle, and more processors.
    • Seymour Cray, a prominent supercomputer designer, exemplified the concept of parallel processing with the analogy of using oxen instead of chickens to plow a field. Oxen (multiple stronger resources) operate much more efficiently.
    • Modern computers and mobile devices now employ parallel processing.
    • Modern GPUs utilize hundreds of processors, including thousands of ALUs.
    • These devices utilize concurrent threads.
    • Programming for parallel systems differs significantly from programming traditional serial systems, requiring different programming techniques.
    • This shift towards parallel processing is driven by the limitations of scaling clock speed, as shown by Moore's Law related data about transistors.
    • Increasing clock speed was a traditional approach to boost computer speed, but this approach plateaus at a certain point, due to diminishing returns related to heat generation and power consumption, as opposed to utilizing more processors.
    • A key driving force behind parallel processing is the desire to increase throughput (completing more tasks per unit time) alongside maintaining low latency (reducing the time it takes to complete a single task).
    • GPU design emphasizes a parallel processing model and relies less on compiler intervention for parallel task execution, focusing on throughput.

    Quiz Questions and Answers

    • Traditional methods to improve computer speed include: faster clocks, more work per clock cycle, and more processors.
    • Modern faster processing is a consequence of adding more processors and transistors, not making individual processors faster.
    • The current design constraint is power, not speed. CPUs are not as energy-efficient as alternative designs since they have complex control structures, increasing power consumption and design complexity.
    • To enhance power efficiency, GPU-like designs adopt simpler control structures, enabling better use of available transistors to focus on processing data paths.
    • The biggest challenge in these designs is effectively programming these structures for optimal performance.

    Additional Points

    • Computer designers employ fewer, yet more complex processors.
    • Efficiency is achieved by maximizing the speed of the processors clock and simplifying the processor structure.
    • The two primary goals in design are not always aligned: decreasing latency (time) and increasing throughput (number of completed tasks).
    • For example, image processing applications prioritize higher throughput, while other types of applications might prioritize lower latency.

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    Parallel Processing Unit 1 PDF

    Description

    This quiz explores the fundamentals of parallel processing, its significance in modern computing, and its impact on hardware design. Learn about the evolution from traditional sequential processing to advanced methods utilized in GPUs and mobile devices. Understand how programming techniques differ when working with parallel systems.

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