Array Processing | Computer Architecture & Organisation (CAO) - Computer Science Engineering (CSE) PDF Download

Array Processing

  • An array processor is a processor that performs computations on large arrays of data.
  • The term is used to refer to two different types of processors.
    • Attached array processor:
      • Is an auxiliary processor.
      • It is intended to improve the performance of the host computer in specific numerical computation tasks.
    • SIMD array processor:
      • Has a single-instruction multiple-data organization.
      • It manipulates vector instructions by means of multiple functional units responding to a common instruction.

Attached Array Processor

  • Its purpose is to enhance the performance of the computer by providing vector processing for complex scientific applications.
    • Parallel processing with multiple functional units
  • Fig. 4-14 shows the interconnection of an attached array processor to a host computer.
  • For example, when attached to a VAX 11 computer, the FSP-164/MAX from Floating-Point Systems increases the computing power of the VAX to 100megaflops.
  • The objective of the attached array processor is to provide vector manipulation capabilities to a conventional computer at a fraction of the cost of supercomputer. 

Array Processing | Computer Architecture & Organisation (CAO) - Computer Science Engineering (CSE)

SIMD Array Processor

  • An SIMD array processor is a computer with multiple processing units operating in parallel.
  • A general block diagram of an array processor is shown in Fig. 9-15.
    • It contains a set of identical processing elements (PEs), each having a local memory M.
    • Each PE includes an ALU, a floating-point arithmetic unit, and working registers.
    • Vector instructions are broadcast to all PEs simultaneously.
  • Masking schemes are used to control the status of each PE during the execution of vector instructions.
    • Each PE has a flag that is set when the PE is active and reset when the PE is inactive.
  • For example, the ILLIAC IV computer developed at the University of Illinois and manufactured by the Burroughs Corp.
    • Are highly specialized computers.
    • They are suited primarily for numerical problems that can be expressed in vector or matrix form.

Array Processing | Computer Architecture & Organisation (CAO) - Computer Science Engineering (CSE)

The document Array Processing | Computer Architecture & Organisation (CAO) - Computer Science Engineering (CSE) is a part of the Computer Science Engineering (CSE) Course Computer Architecture & Organisation (CAO).
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FAQs on Array Processing - Computer Architecture & Organisation (CAO) - Computer Science Engineering (CSE)

1. What is array processing?
Ans. Array processing refers to the manipulation and analysis of data stored in arrays, which are data structures that store multiple elements of the same type. It involves performing various operations on the elements of an array, such as sorting, searching, and modifying the values.
2. How do arrays help in data processing?
Ans. Arrays provide a structured way to store and organize data, making it easier to perform operations on the data. They allow for efficient access to individual elements using their index, which simplifies tasks like searching and modifying specific values. Arrays also support various algorithms and techniques, enabling effective data processing.
3. What are some common array processing operations?
Ans. Common array processing operations include sorting the elements in ascending or descending order, searching for a specific value or condition, calculating the sum, average, or other statistical measures of the elements, and modifying the values based on certain criteria. These operations are often performed using loops or built-in functions in programming languages.
4. How does array processing improve performance in data analysis?
Ans. Array processing allows for efficient and optimized data analysis by leveraging the inherent properties of arrays. The ability to access elements using their index enables fast retrieval and manipulation of data, reducing the time complexity of algorithms. Additionally, many programming languages provide specialized functions and libraries for array processing, further enhancing performance.
5. What are some challenges in array processing?
Ans. Array processing can pose challenges when dealing with large or multidimensional arrays, as they require significant memory resources. Efficient memory management techniques, such as using dynamic arrays or sparse arrays, can help mitigate these challenges. Additionally, complex array operations may require advanced algorithms or optimization techniques to ensure optimal performance.
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