24-12-2012, 05:53 PM
Parallel Computing
Parallel Computing.ppt (Size: 1.73 MB / Downloads: 57)
Motivating Factor: Human Brain
The human brain consists of a large number (more than a billion) of neural cells that process information. Each cell works like a simple processor and only the massive interaction between all cells and their parallel processing makes the brain's abilities possible.
Aggregated speed with which complex calculations carried out by (billions of) neurons demonstrate feasibility of parallel processing.
Flynn’s taxonomy
Flynn proposed a classification of computer systems based on a number of instruction and data streams that can be processed simultaneously.
They are:
SISD (Single Instruction and Single Data)
SIMD (Single Instruction and Multiple Data)
MISD (Multiple Instruction and Single Data)
MIMD (Multiple Instruction and Multiple Data)
Classification on the basis of computation
Massively Parallel Systems :
It signifies the presence of many independent arithmetic units or entire microprocessors, that run in parallel. Today's most powerful supercomputers are all MP systems such as Earth Simulator, Blue Gene, ASCI White, ASCI Red, ASCI Purple.
Embrassingly Parallel Systems :
A very common usage of an embarrassingly parallel problem lies within graphics processing units (GPUs) for things like 3D projection
Grand Challenge Problems :
A grand challenge is a fundamental problem in science or engineering, with broad applications, whose solution would be enabled by the application of high performance computing resources that could become available in the near future.
Examples of grand challenges are:
the design of hypersonic aircraft, efficient automobile bodies, and extremely quiet submarines.
Electronic structure calculations for the design of new materials such as chemical catalysts, immunological agents, and superconductors.
tools for design, manufacturing, and simulation of complex systems.
Semiconductor design….& more…
Summary/Conclusions
Parallel processing has become a reality:
E.g., SMPs are used as (Web) Servers extensively.
Threads concept utilized everywhere.
Clusters have emerged as popular data centers and processing engines:
E.g., Google search engine.
The emergence of commodity high-performance CPU, networks, and OSs have made parallel computing applicable to enterprise and consumer applications.
E.g., Oracle {9i,10g} database on Clusters/Grids.
E.g. , Facebook and Twitter running on Clouds