Distributed
High Perform
High performance computing (HPC) is
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the main motivation for using parallel supercomputers, computer clusters and
other advanced parallel/distributed
High speed
Increasing the
microprocessor
Parallelizing (explicit
computing if we have
Specialized
Increasing clock frequency
Implicit parallelism (Instruction e.g., pipeline, superscalar
sequential
ly) the process of
Level Parallelism)
multiple CPUs/GPUs!
allel Computing
Parallel Computin
refers to a large
(algorithms, arch
tools, etc)
computatio
g (or Processing)
ss of methods
itectures, software
mpt to increas
performing
n concurrently.
The promise of
promise and gat
ocessor computin
parallelism
researchers for at least five decades.
In the past, parallel computing efforts have shown
investment, but in the end,
We argue general-purpose computing is taking an irreversible step toward parallel architectures.
Technology push
Application driven
prevailed.
roughly twice as
much capacity as its predecessor.
Each new chip
was released
within 18-24 months of the previous chip.
By Author: ourworldindata.org – Original text :
Data source: https://en.wikipedia.org/wiki/Transistor_countURL: https://ourworldindata.org/wp-content/uploads/2013/05/Transistor-Count-over-time.pngArticle:
https://ourworldindata.org/technological-progress),
CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=71553709
cessor Perform
rformanc prove by
per year between 1986
Since 2002,
has improved
Technological Limitations
“Frequency wall”: Increasing frequen deeper pipelines has reached diminish
“Power wall”:
(higher clock
“ILP wall”:
ILP (instructi
The chip will
wall”: Load
minishing returns
parallelism).
is fast. Modern microprocessors can take much more clock cycles to access Dynamic Random Access Memory (DRAM) than the clocks for floating-point multiplies.
ing returns o
, but multiply
Intel Announcement (12/2006):
developed the world
processor that delivers supercomputer
like performance (
1+ TFlops, 1+ Tbs/s
from a single, 80
larger than the size of a finger nail while
archers have
s first programmable
chip not muc
using less electricity (~
s home appliances.
) than most of
for networking
The rate of technological progr
fold increase every 4 years (77.8% yearly compound rate).
The emergence of computing (as opposed to
centric) – distributed high performance/throughput computing
astounding
network processor
(Wide Area Netw
Network is the
of a single c
clusters o
omputer, whi
comparable speed or availability. Nowadays, almost all supercomputers
f large sca
A computer cluster is a group of linked computers, working together closely so that in many respects they form a single computer
originally defined as using the
off-the-shelf components, including PCs and fast local area networks, to build a cluster of PCs to improve performance and/or availability over that
than supercompu
e computer
The Internet
Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and
services) that
can be rapidly provisioned
released with minimal management effort or
service provider interaction (NIST’s definition)
Cloud computing describes a new supplement, consumption and delivery model for IT services based on the Internet, and it typically involves the provision of dynamically scalable and often virtualized resources (storage, platform, infrastructure, and software) as a service
the Internet.
When computing cost improve of computers multiply
— storm forecasting and climate prediction
— understanding biochemical processes of living o
Engineering
—earthquake and structural modelling —molecular nanotechnology
—computational —data mining
namics and airplan
Data deluge is commonly seen nowadays in many domains, such as astronomy, particle physics and
smart city and e-health.
The dramatic increase in the volume of data a requires a large amount of computing power necessary to transform the raw data into m
mation, which dema
MapReduce t
nds the use of
strategies.
These demanding requirements have led to the development of high-level programming models such
machines s
Deep learning (DL), or Deep Neural Network (DNN) is a class of machine learning algorithms which are
structure and functio
DNNs are trained by analysing a large amount to enable the classification and prediction
has now be
ssfully applie
applications in practice and play more and more significant roles in our daily lives
powerful computing resources which enable train larger and deeper neural networks
ess is main
ble training data
d for vario
Parallel computing splits a single application into multiple tasks that are executed at the time and is more like a top-down approach
Distributed
application which is executed as a whole but at different locations and is more like a bottom-up approach
howwecanp
concurrently,
omposition:
what happens if many distribu interact with each other
if a global functio
there is no
Parallel computing is about decomposition:
erform a single applicat
how we can divide a computation into smaller parts which may potentially b executed in parallel.
Distributed computing
n can be achiev
ed although
Distributed
entific computing
availability Informatio
Parallel computing considers how maximum degree of concurrency
rce sharing
reliabilit
The differences are now blurr especially after the introducti
computing and cloud computing
related fields
e processors
Networks connecting the processors
Multiple computing activities and processes
Input/output
processors
data distributed
y things in
For the last decade and investment strategy has
Powerful compu
tackling application problems
Need new wa
Parallel algor essential skil must have in
puters 15 to
more, the research been overwhelming
ters are useless without software capable of
The high performance ecosystem needs to be rebalanced Even our PCs are parallel computers and considered
rcomputers are
20 years ago
tomorrow’s ordinary
ys to program contemporary machines
ithms design and programming will become an l every qualified computer scientist/engineer
the near future
Course Theme:
In sequential com performed one at
traightforward to reason abo orrectness and performance
haracteristics
In parallel take place
reason perfor
puting, operations a time, making it
computing, many oper at once, complicating
ing about mance.
the correctness a
ations our
Course Theme:
A sequential a
The parallel on
the input size,
The asymptotic runtime of program is identical on any
the number of processors,
the communication parameters
A parallel algorithm must therefore be analyzed in the context of the underlying platform
Need different
algorithms for dif
luated by its
a sequential serial platform.
of the machine.
ferent HPC computers!
What if pr How do we
Problems to consider: How to divide a task int
e performance
o multiple sm
ocesses need to share partial results? aggregate partial results?
parallel prog
Main Topic
Parallel algorith
Analytical
buted computing
parallel progra
architectures
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