Transcript of 1 2014 Fujitsu December 15 th 2014 High Performance Computing.
- Slide 1
- 1 2014 Fujitsu December 15 th 2014 High Performance
Computing
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- 2 2014 Fujitsu Agenda Introduction Why Parallel Why not
Parallel Speedup How the Code Looks Like Fujitsu Value Proposition
to KAU Benefits to Society
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- 3 2014 Fujitsu Introduction In the field of research, High
Performance Computing (HPC) is the use of hardware, software, tools
and programming techniques to accelerate research computation,
which in turn will enable the execution of large cutting-edge
research simulation that accelerates new discoveries.
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- 4 2014 Fujitsu Sequential Processing Matrix Addition
Example
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- 5 2014 Fujitsu Sequential Processing Matrix Multiplication
Example
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- 6 2014 Fujitsu Sequential Processing What will happen if the
matrix size is 1000,000,000 x 1000,000,000 ? If each addition
operation needs 1 Microsecond then we need more than 3000 Years to
finish the computation
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- 7 2014 Fujitsu Sequential Processing Standalone Computers are
not able to face Big Data Analysis and Processing
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- 8 2014 Fujitsu Parallel Processing Matrix Addition Example
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- 9 2014 Fujitsu Parallel Processing Matrix Multiplication
Example
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- 10 2014 Fujitsu Agenda Introduction Why Parallel Why not
Parallel Speedup How the Code Looks Like Fujitsu Value Proposition
to KAU Benefits to Society
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- 11 2014 Fujitsu Why Parallel It is not always obvious that a
parallel algorithm has benefits, unless we want to do things
faster: doing the same amount of work in less time bigger: doing
more work in the same amount of time Both of these reasons can be
argued to produce better results, which is the only meaningful
outcome of program parallelization
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- 12 2014 Fujitsu Faster, Bigger! There is an ever increasing
demand for computational power to improve the speed or accuracy of
solutions to real-world problems through faster computations and/or
bigger simulations Computations must be completed in acceptable
time (real-time computation), hence must be fast enough
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- 13 2014 Fujitsu Faster, Bigger! An illustrative example: a
weather prediction simulation should not take more time than the
real event Suppose the atmosphere of the earth is divided into 510
8 cubes, each 111 mile and stacked 10 miles high It takes 200
floating point operations per cube to complete one time step 10 4
time steps are needed for a 7 day forecast (time step = 1 min) Then
10 15 floating point operations must be performed (510 8 x 200 x 10
4 ) This takes 10 6 seconds (= 10 days) on a 1 GFLOP machine
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- 14 2014 Fujitsu Grand Challenge Problems Big problems A Grand
Challenge problem is a problem that cannot be solved in a
reasonable amount of time with todays computers Examples of Grand
Challenge problems: Applied Fluid Dynamics Meso- to Macro-Scale
Environmental Modeling Ecosystem Simulations Biomedical Imaging and
Biomechanics Molecular Biology Molecular Design and Process
Optimization Fundamental Computational Sciences Nuclear power and
weapons simulations
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- 15 2014 Fujitsu Physical Limits Which tasks are fundamentally
too big to compute with one CPU? Suppose we have to calculate in
one second for (i = 0; i < ONE_TRILLION; i++) z[i] = x[i] +
y[i]; Then we have to perform 3x10 12 memory moves per second If
data travels at the speed of light (3x10 8 m/s) between the CPU and
memory and r is the average distance between the CPU and memory,
then r must satisfy 310 12 r = 310 8 m/s 1 s which gives r = 10 -4
meters To fit the data into a square so that the average distance
from the CPU in the middle is r, then the length of each memory
cell will be: 210 -4 m / (310 6 ) = 10 -10 m which is the size of a
relatively small atom!
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- 16 2014 Fujitsu Agenda Introduction Why Parallel Why not
Parallel Speedup How the Code Looks Like Fujitsu Value Proposition
to KAU Benefits to Society
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- 17 2014 Fujitsu Why not Parallel Bad parallel programs can be
worse than their sequential counterparts Slower: because of
communication overhead Scalability: some parallel algorithms are
only faster when the problem size is very large Understand the
problem and use common sense! Not all problems are amenable to
parallelism Some algorithms are inherently sequential for (i=1;
i< 1000000; i++) X[i]=X[i-1] + Y[i]; We can find that there is a
dependency that prevents parallelism
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- 18 2014 Fujitsu Agenda Introduction Why Parallel Why not
Parallel Speedup How the Code Looks Like Fujitsu Value Proposition
to KAU Benefits to Society
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- 19 2014 Fujitsu Speedup Definition: the speedup of an algorithm
using P processors is defined as S P = T s / T P Where: T s is the
execution time of the best available sequential algorithm and T P
is the execution time of the parallel algorithm
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- 20 2014 Fujitsu Amdahls Law s (1- ) T s TsTs P S P = T s / T P
+ (1- ) P 1 S P = ( s ) + (1- ) T s P TsTs S P =
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- 21 2014 Fujitsu Parallel Search
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- 22 2014 Fujitsu Agenda Introduction Why Parallel Why not
Parallel Speedup How the Code Looks Like Fujitsu Value Proposition
to KAU Benefits to Society
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- 23 2014 Fujitsu How the Code Looks Like Sequential Matrix
Addition for i = 1 to M for j = 1 to N C[i,j] = A[i,j] + B[i,j]
Parallel Matrix Addition for i = 1 to M for j = 1 to N C[i,j] =
A[i,j] + B[i,j] #pragma omp for Matrix Addition Example
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- 24 2014 Fujitsu Agenda Introduction Why Parallel Why not
Parallel Speedup How the Code Looks Like Fujitsu Value Proposition
to KAU Benefits to Society
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- 25 2014 Fujitsu HPC at KAU Many scientific fields have adopted
in the provisioning and support of research computation. In these
environments, departments and research groups are providing local
resources to support their researchers, whereas the IT team is
focusing on providing central HPC resources and services to support
all staff and student researchers across campus. IT Team Scientists
and Research Students Focus on Solving Scientific Problems Focus on
Providing Sustainable Central HPC Service
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- 26 2014 Fujitsu HPC at KAU Fujitsu is currently working with
KAU in order to provide researchers with impeccable HPC resources
to fulfill their increasing need and meet or even go beyond their
research target. In that sense Fujitsu will collaborate closely and
strongly with KAU in order to ensure that : The use of HPC is
propagated to the whole research communities within KAU KAU
researchers become experienced HPC users KAU IT team become
knowledgeable in HPC technologies and management
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- Fujitsu value proposition to KAU 27 A proven set of services (
support and professional) delivered by Fujitsu HPC experts The
Innovative approach of HPC Campus aligned to the strategy of KAU in
promoting HPC in the University and the Kingdom The involvement of
the whole Fujitsu Corporation with a full commitment and the access
to all HPC worldwide expertise A proven set of services ( support
and professional) delivered by Fujitsu HPC experts The Innovative
approach of HPC Campus aligned to the strategy of KAU in promoting
HPC in the University and the Kingdom The involvement of the whole
Fujitsu Corporation with a full commitment and the access to all
HPC worldwide expertise Fujitsu solution Implement a solid
foundation to support R&D activities and allow scientists to
focus on their research challenges Sound and dedicated service
model End users access and ease of use Enlarge HPC user community
Generate ROI visible to the whole Kingdom Sound and dedicated
service model End users access and ease of use Enlarge HPC user
community Generate ROI visible to the whole Kingdom KAU
requests
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- Solution Building blocks Hardware (servers, network, storage )
OS (RedHat EL, CentOS) HPC middleware (admin, workload mgr, MPI,
Libs ) User interface (Web portal) User Applications Infrastructure
layer (machine room, cooling, electricity )
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED
Services Overview KAU requirementsFujitsus Service delivery A fully
supported and maintained premier HPC systemDedicated Staff to fully
manage and operate the facility Ability to operate and manage the
HPC systems with internal teams Training and Knowledge Transfer
Program for (End Users, Application Developers, System
Administrators, and Operators) Porting/validation of existing
applications on the new service Migration of the existing
implementations to the new HPC facility Optimizing/Extending
existing applicationsSupport in Code optimization Ability to
incorporate remotely located compute islands on campus Migration
and integration Services Positioning KAU as an HPC competence
centre in the Kingdom and the GCC Establishing a collaboration
scheme between KAU and International research organization. HPC
global awareness program Increase institutional collaboration
worldwideWell structured collaboration activities management to
Increase the scope of research project with international
organizations Promote the use of HPC across other areas of science
and research Comprehensive Outreach and marketing Program Link
remote organisations resources to KAUs HPC service Campus cloud
Implementation
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED
Service organization The whole operations are managed by on-site
team The skill-set (on site or mobile) needed to deliver the
services are covering all the areas of expertise needed to deliver
the services : HW engineer (on site and mobile) for HW maintenance
SW engineer (on site and mobile) for SW maintenance Application
specialist (on site and mobile) for application support Technical
experts used for 3 rd level support (mobile), either Fujitsu or 3rd
party experts HPC consultants used in delivering professional
services 30 On-site operation and support Project Manager HW
engineer SW engineer Application expert HW engineer SW engineer
Application expert Intel support Cisco support NetApp support
Altair support Fujitsu product support HPC SW Technical group HPC
HW technical support Mobile HW engineer 3rd party experts Fujitsu
experts
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- Single service interface with worldwide backing 31 Fujitsu HPC
Tokyo Toulouse London Munich KAU Service Desk End-to-End services
are delivered using the Worldwide expertise of Fujitsu in HPC. This
covers the complete scope of HPC components ( HW, SW, Applications)
End-to-End services are delivered using the Worldwide expertise of
Fujitsu in HPC. This covers the complete scope of HPC components (
HW, SW, Applications) San Jose Fujitsu service desk Single point of
contact Fujitsu service desk Single point of contact
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED
Agenda Introduction Why Parallel Why not Parallel Speedup How the
Code Looks Like Fujitsu Value Proposition to KAU Benefits to
Society
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED
Samples of the Benefits to Society There are a whole range of
benefits that could be gained by society through the application of
HPC: HPC could considerably increase oil recovery with more
accurate seismic modeling of oil reservoirs. Currently, the
uncertainties in the seismic models can lead to errors in drilling
that both decrease output and increase environmental impact. HPC is
being used to design efficient wind and wave turbines, helping to
harness renewable energy sources. HPC could be used to model the
spread of epidemics, enabling public health officials to intervene
appropriately to halt the expansion of life-threatening diseases.
HPC could lead to a revolution in medical procedures and devices as
well as product safety for a variety of consumer products by
simulating virtual humans of all shapes and ages. 33
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED Other
Applications of HPC Simulation and Modeling
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- Commercial in confidence - Copyright 2010 FUJITSU LIMITED Other
Applications of HPC Bioinformatics
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- Commercial in confidence - Copyright 2010 FUJITSU LIMITED Oil
and Gas AerodynamicsFluid Mechanics Soil Mechanics GeophysicsRemote
Sensing Climate Research Oceanography Aerospace Other Applications
of HPC Big Data Analysis
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED
Agenda Introduction Why Parallel Why not Parallel Speedup How the
Code Looks Like Fujitsu Value Proposition to KAU Benefits to
Society
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED
Deliverables HPC facility - fully operated and managed by KAU
members. Professional HPC CoE High quality research work (research
projects, scientific papers, etc.) Sustainable HPC facility with an
ambitious research plan in the field of HPC 38 HPC Center of
Excellence Publications ISI SCOPUS ELSEVIER Springer HPC Research
Roadmap Experts Research Projects Funds
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED 39
380 Nodes 9120 Cores 112 Nodes 2688 Cores 2 NVIDIA 48 Core 2 Nodes
48 Core 96 GB 256 GB 96 GB
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED
40
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED How
can we cooperate? Deploying the already existing software systems
on the new platform. Implementing algorithms from scratch.
Optimizing the existing codes. Working on much more larger data
sets. Conducting professional training. Conducting professional
training Initial Training Plan 41
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- Commercial in confidence - Copyright 2012 FUJITSU LIMITED Thank
You 42
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- Commercial in confidence - Copyright 2010 FUJITSU LIMITED We
have a dream Having a new parallel computing paradigm that can be
used by the researchers and the scientific community in the field
of HPC
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- Commercial in confidence - Copyright 2010 FUJITSU LIMITED
44
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- Commercial in confidence - Copyright 2010 FUJITSU LIMITED How
the Code Looks Like Sequential Matrix Addition for i = 1 to M for i
= 1 to N C[i,j] = A[i,j] + B[i,j] Parallel Matrix Addition for i =
1 to M for i = 1 to N C[i,j] = A[i,j] + B[i,j] #pragma omp for
Matrix Addition Example