Seminar on :- Parallel Computing

Submitted ByKartik N. Kalpande..!

INTRODUCTION:

Parallel computing is a type of computation.

There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism.

PARALLEL COMPUTING:

A problem is broken into discrete parts that can be solved concurrently

Each part is further broken down to a series of instructions

Why Use Parallel Computing?:

Main Reasons:

Save Time And/or Money.

Solve Larger / More Complex Problems.

Make Better Use Of Underlying Parallel Hardware.

Parallel Computer Memory Architectures:Shared Memory:

General Characteristics:

Multiple processors can operate independently but share the same memory resources.

Changes in a memory location effected by one processor are visible to all other processors.

Advantages:Global address space provides a user-friendly programming perspective to memory.

Data sharing between tasks is both fast and uniform.

Disadvantages:

Adding more CPUs can geometrically increases traffic on the shared memory-CPU path.

Programmer responsibility for synchronization constructs.

Distributed Memory:

General Characteristics:

Like shared memory systems, distributed memory systems vary widely but share a common characteristic.

Processors have their own local memory.

Advantages:

Memory is scalable with the number of processors

Each processor can rapidly access its own memory.

Disadvantages:

It may be difficult to map existing data structures.

Non-uniform memory access times.

Hybrid Distributed-Shared Memory:

General Characteristics:

The largest and fastest computers in the world today both shared and distributed memory architectures.

The shared memory component can be a shared memory machine.

Advantage :

Increased scalability.

Disadvantage:

Increased programmer complexity.

Flynn's Classical Taxonomy:

One of the more widely used classifications, is called Flynn's Taxonomy.

The matrix below defines the 4 possible classifications according to Flynn:

Types of parallelism:

Bit-level parallelism:

Historically, 4-bit microprocessors were replaced with 8-bit, then 16-bit, then 32-bit microprocessors.

This trend generally came to an end with the introduction of 32-bit processors.

Instruction-level parallelism:

Without instruction-level parallelism, a processor can only issue less than one instruction per clock cycle (IPC < 1).

Applications of Parallel Computing:

Data bases, Data mining.

Networked videos and Multimedia technologies.

Medical imaging and diagnosis.

Advanced graphics and virtual reality.

Collaborative work environments. 

Conclusion:

With increasing demands of human, and more expectation from technology, the importance of processing faster and to a larger scale is growing fast.

REFERENCES

www.google.com www.yahoo.com www.wikipedia.org/history www.askmi.com

THANK YOU!