Explain SIMD and MIMD with its architecture

SIMD [ Single Instruction, Multiple Data ] :

> All processing units execute the same instruction at any given clock cycle
> Each processing unit can operate on a different data element
> Best suited for specialized problems characterized by a high degree of regularity, such as graphics/image processing
> Synchronous (lockstep) and deterministic execution
> Two varieties: Processor Arrays and Vector Pipelines
> Most modern computers, particularly those with graphics processor units (GPUs) employ SIMD instructions and execution units.

MIMD [ Multiple Instruction, Multiple Data ] :
> Every processor may be executing a different instruction stream

> Every processor may be working with a different data stream

> Execution can be synchronous or asynchronous, deterministic or non- deterministic

> Currently, the most common type of parallel computer - most modern supercomputers fall into this category.

> Many MIMD architectures also include SIMD execution sub-components

What is meant by shared memory parallel computer? Explain its advantages and disadvantages.

General Characteristics:

> all processors can access all memory as global address space

> Multiple processors can operate independently

> If any processor modify any memory location, visible to other processors

> Historically, shared memory machines have been classified as UMA and NUMA, based upon memory access times.

Fig. UMA Fig. NUMA

Advantages:

> Global address space provides a user-friendly programming perspective to memory

> Data sharing between tasks is both fast and uniform due to the proximity of memory to CPUs

Disadvantages:

> Lack of scalability between memory and CPUs.

Adding more CPUs can geometrically increases traffic on the shared memory-CPU path, and for cache coherent systems, geometrically increase traffic associated with cache/memory management.

> Programmer responsibility for synchronization constructs that ensure "correct" access of global memory.

Who use Parallel Computing?

Companies that I know which are working in parallel computing area are Intel , IBM, calligo tech, TCS and Wipro.

          

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• Science and Engineering
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What is Parallel Computing and Why Use Parallel Computing?

Serial Computing: 

In Serial Computing, problem is broken down into instructions that are execute on single processor one at time.

Parallel Computing: 

In Parallel Computing, problem is broken down into discrete parts. These parts are further broken down into instructions execute sequentially. Ultimately, Discrete parts can execute concurrently on different processor.

Advantages : 

• SAVE TIME AND/OR MONEY
• as cheap, commodity components can be used
• SOLVE MORE COMPLEX PROBLEMS
• as no limiting computing like traditional
• PROVIDE CONCURRENCY
• as we use multiple processor
• TAKE ADVANTAGE OF NON-LOCAL RESOURCES
• by wide area network
• MAKE BETTER USE OF UNDERLYING PARALLEL HARDWARE
• as modern laptops also based on parallel architecture