Introduction to parallel processing
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Introduction to Parallel Processing. CS147 Tung Sze Ming. Topics Covered. An Overview of Parallel Processing Parallelism in Uniprocessor Systems Parallelism in Multiprocessor Systems Flynn ’ s Classification System Topologies. An Overview of Parallel Processing.

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Topics covered
Topics Covered

  • An Overview of Parallel Processing

  • Parallelism in Uniprocessor Systems

  • Parallelism in Multiprocessor Systems

    • Flynn’s Classification

    • System Topologies


An overview of parallel processing
An Overview of Parallel Processing

  • What is parallel processing?

    • Parallel processing is a method to improve computer system performance by executing more than one instructions at the same time.


Misconception
Misconception

  • When speaking of parallel processing, most people would think of multi-processor systems


Parallelism in uniprocessor systems
Parallelism in Uniprocessor Systems

  • It is possible to achieve parallelism with a uniprocessor system.

    • Some examples are the instruction pipeline, arithmetic pipeline, I/O processor.

    • Only if the system processes two different instructions simultaneously can it be considered parallel

    • A system that performs different operations on the same instruction is not considered parallel.


Parallelism in a uniprocessor system
Parallelism in a Uniprocessor System

  • A reconfigurable arithmetic pipeline is an example of parallelism in a uniprocessor system.

    Each stage of a reconfigurable arithmetic pipeline has a multiplexer at its input. The multiplexer may pass input data, or the data output from other stages, to the stage inputs. The control unit of the CPU sets the select signals of the multiplexer to control the flow of data, thus configuring the pipeline.


A reconfigurable pipeline with data flow for the computation a i b i c i d i
A Reconfigurable Pipeline With Data Flow for the Computation A[i]  B[i] * C[i] + D[i]

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Data Inputs

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Although arithmetic pipelines can perform many iterations of the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.


Vector arithmetic unit
Vector Arithmetic Unit the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

A vector arithmetic unit contains multiple functional units that perform addition, subtraction, and other functions. The control unit routes input values to the different functional units to allow the CPU to execute multiple instructions simultaneously.


A vectored arithmetic unit
A Vectored Arithmetic Unit the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

Data

Input

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Parallelism in multiprocessor systems
Parallelism in Multiprocessor Systems the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

  • Parallel processing systems achieve parallelism by having more than one processor performing tasks simultaneously. Since multiprocessor systems are more complicated than uniprocessor systems, there are many different ways to organize the processors and memory


Flynn s classification
Flynn’s Classification the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

  • SISD: Single instruction with single data

  • SIMD: Single instruction with multiple data

  • MISD: Multiple instruction with single data

  • MIMD: Multiple instruction with multiple data


Topologies
Topologies the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

Topology of a multiprocessor system refers to the pattern of connections between its processors. Various factors, typically involving a cost-performance tradeoff, determine which topology a computer designer will select for a multiprocessor system.


Types of topology
Types of Topology the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

  • Shared Bus Topology

  • Ring Topology

  • Tree Topology

  • Mesh Topology

  • Hypercube Topology

  • Completely connected Topology


Shared bus topology
Shared Bus Topology the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

  • processors communicate with each other exclusively through this bus. However, the bus can only handle only one data transmission at a time. In most shared busses, processors directly communicate with their own local memory.


Ring topology
Ring Topology the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

  • The ring topology uses direct connections between processors instead of a shared bus. This allows all communication links to be active simultaneously. Data may have to travel through several processors to reach its destination


Tree topology
Tree Topology the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

  • Like the ring, it uses direct connections between processors; each having three connections. There is only one unique path between any pair of processors


Mesh topology
Mesh Topology the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

  • In the mesh topology, every processor connects to the processors above and below it, and to its right and left.


Hypercube topology
Hypercube Topology the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

  • The hypercube is a multidimensional mesh topology. Each processor connects to all other processors whose binary values differ by one bit.


Completely connected topology
Completely connected Topology the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.

  • In the most extreme connection scheme, the processors are completely connected. Every processor has (n-1) connections, one to each of the other processors. This increases the complexity of the processors as the system grows, but offers maximum communication capabilities.


  • THE END the same operation in parallel, they cannot perform different operations simultaneously. To perform different arithmetic operations in parallel, a CPU must include a vectored arithmetic unit.


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