Data-Level Parallelism Quiz

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Questions and Answers

What can SIMD architectures exploit significant data-level parallelism for?

  • Matrix-oriented scientific computing (correct)
  • Operating system development
  • Sequential programming languages
  • Database management

Which type of architecture is more energy efficient than MIMD?

  • SIMD (correct)
  • MIMD
  • Vector
  • GPU

Who is known as the Father of Vector Processing & Supercomputing?

  • Alan Turing
  • Charles Babbage
  • Symour Cray (correct)
  • John von Neumann

What do vector processors work on?

<p>Linear arrays of numbers (C)</p> Signup and view all the answers

What type of operations do vector processors perform?

<p>Multiple (N) operations (C)</p> Signup and view all the answers

SIMD architectures are more energy efficient than MIMD.

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

Vector processors work on linear arrays of numbers called 'vectors' only.

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

SIMD variations include vector architectures, SIMD extensions, and Graphics Processor Units (GPUs).

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

Cray supercomputers are associated with Vector Processing and Supercomputing.

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

SIMD allows programmers to think sequentially, making it attractive for personal mobile devices.

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

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Study Notes

SIMD Architectures

  • SIMD (Single Instruction, Multiple Data) architectures exploit significant data-level parallelism, allowing simultaneous execution of operations on multiple data points.
  • SIMD is known for being more energy efficient than MIMD (Multiple Instruction, Multiple Data) architectures.

Vector Processing

  • The Father of Vector Processing and Supercomputing is widely recognized as William Kahan, who contributed greatly to the field.
  • Vector processors operate on linear arrays of numbers known as 'vectors', performing computations on these sets of data.
  • Vector processors are designed to carry out operations such as addition, subtraction, multiplication, and division across elements in a vector, enhancing the speed of mathematical calculations.

SIMD Variations

  • Major variations of SIMD include vector architectures, SIMD extensions found in modern CPUs, and Graphics Processing Units (GPUs), which are optimized for handling multiple data streams in parallel.
  • SIMD architectures enable programmers to adopt a sequential thinking style, which is particularly beneficial in applications for personal mobile devices, where power efficiency and performance are crucial.

Supercomputing

  • Cray supercomputers are historically associated with advanced Vector Processing and Supercomputing applications, pushing the boundaries of computation during their time.

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