Applications of paralleL processing

Applications of Parallel
Processing
A presentation by chinmay terse
vivek ashokan
rahul nair
rahul agarwal

Numeric weather prediction
 NWP uses mathematical models of
atmosphere and oceans
 Taking current observations of weather
and processing these data with
computer models to forecast the
future state of weather.
 Uses data assimilation to produce
outputs

Oceanography and Astrophysics
 Used to study wealth of ocean using
multiprocessors having large computational
power with low power requirements.
 ROMS were used originally but now MPI
programming methods are used.
 Computational astrophysics refers to the methods
and computing tools developed and used in
astrophysics research.
 PIC ,PM and n-body simulations are different
important techniques for computational
astrophysics.

Socio Economics
 Parallel processing is used for modelling of a economy of a
nation/world.
 Programs system which involves cluster computing device to
implement parallel algorithms of scenario calculations ,optimization
are used in such economic models.
 Such program system serves for conducting multi-scenario
calculations to design a suitable development strategy for a region.

Finite element analysis
 FEA is a numeric method commonly used
for multiphysics problem.
 Used in design of huge structures like
ships, dams, supersonic jets etc.
 In FEA extremely large amount of partial
differential equations are to solved
concurrently and hence parallel
processing elements are used.

Artificial Intelligence and Automation
 AI is the intelligence exhibited by machines or software.
 AI systems requires large amount of parallel comptuting for which they are
used.
 Four types
1.Image processing
2.Expert Systems
3.Natural Language Processing(NLP)
4.Pattern Recognition

Seismic Exploration
 It is a method of exploration that uses the principles of seismology to
estimate the properties of the Earth's subsurface from reflected seismic
waves.
 When a seismic wave travelling through the Earth encounters an interface
between two materials, some of the wave energy will reflect off the
interface which are analysed to determine underground strata.
 Such large number of reflected waves are analysed using sensors and
parallel architecture

Genetic Engineering
 It is the direct manipulation of an
organism's genome using biotechnology
for eg. Dna sequence analysis.
 Several of these analysis produce huge
amounts of information which becomes
difficult to hande using single processing units
because of which parallel processing
algorithms are used

Weapon Research and Defense
 Computer clusters are used in simulations that show a nuclear weapon's
performance in precise molecular detail, tools that are used for national
defense.
 Parallel computing is required which are needed to more efficiently certify
nuclear weapons,to accurately show molecular-scale reactions taking
place over milliseconds, or thousandths of a second.
 They are also used in plutonium research to study its behaviour under high
pressure whose alloys are then used for making explosives

Medical Applications
 Parallel computing is used in medical
image processing
 Used for scanning human body and
scanning human brain
 Used in MRI reconstruction
 Used for vertebra detection and
segmentation in X-ray images
 Used for brain fiber tracking

Remote Sensing Applications
 It is a software application that processes remote sensing data.
 Remote sensing applications read specialized file formats that contain
sensor image data, georeferencing information, and sensor metadata.
 Computer analysis of such remotely sensed earth resources data has many
applications in agriculture,forestry etc.
 Explosive amounts of pictorial information needs to be processed in this
area.

Energy Resource Exploration
 Resource Exploration is a method to gather and manage information
about energy resources like oil,natural gas etc.
 Computers here help in the discovery and management of such energy
resources.
 This sector maintains the records of global energy crisis and also helps in
ensuring nuclear reactor safety

Loosely coupled multiprocessors

Loosely coupled multiprocessors
 In loosely coupled multiprocessor each processor has its own memory (i.e.
faster access to its local or own memory).
 processor interact through interconnection structure or by message passing
using standard primitive functions send() & receive().
 The access to remote memory attached to other processors takes longer
time due to added delay through the interconnection network.
 It is characterized by non-uniform memory access time.
 It is easier to organize & write operating system for loosely coupled systems.

Tightly Coupled Multiprocessors

Tightly Coupled Multiprocessors
 Also known as shared memory multiprocessors.
 In this system, there is a single system-wise primary memory that is shared by
all processors.
 Communication between processors takes places through shared memory.
 Every processor has unmapped local memories which is used to store kernel
data.
 High interaction between processors.
 Shared memory modules can communicate through PMIN.

DIFFERNCE BETWEEN TIGHTLY AND
LOOSELY COUPLED MULTIPROCESSOR
Tightly coupled multiprocessor
1)Multiprocessor systems contain multiple CPUs
that are connected at the bus level. These
CPUs may have access to a central shared
memory (SMP or UMA), or may participate in
a memory hierarchy with both local and
shared memory (NUMA).
2) Tightly-coupled systems perform better & are
physically smaller than loosely-coupled
system
3) More expensive.
4) In a tightly-coupled system, the delay
Experienced , when a message is sent from
one computer to another is short and data
rate is high; that is, the number of bits per
second that can be transferred is large.
Loosely-coupled multiprocessor
1)This system(often referred to as clusters)
are based on multiple standalone single or
dual process or commodity computers
interconnected via a high speed
communication system .
2) Loosely coupled system is just Opposite of
tightly coupled system.
3) Less expensive.
4)In a loosely-coupled system, the opposite
is true: The inter-machine message delay is
large and the data rate is low.

DIFFERNCE BETWEEN TIGHTLY AND
LOOSELY COUPLED MULTIPROCESSOR
Tightly coupled multiprocessor
5) Tightly-coupled systems tend to be much
more energy efficient than clusters. This is
because considerable economies can be
realized by designing components to work
together from the beginning in tightly-
coupled systems.
6) For example two computers connected by
a2400 bit/sec modem over the telephone
system are certain to be loosely coupled.
Loosely-coupled multiprocessor
5)loosely-coupled systems use components
that were not necessarily intended
specifically for use in such systems.
6)For example, two CPU chips on the same
printed circuit board and connected by
wire etched onto the board are likely to be
tightly Coupled.

Applications of paralleL processing

Recommended

More Related Content

What's hot (20)

Similar to Applications of paralleL processing (20)

Recently uploaded (20)

Applications of paralleL processing