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HPC & Big Data Convergence: The Cutting Edge & Outlook

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HPC & Big Data Convergence: The Cutting Edge & Outlook

Sardar Usman1, Rashid Mehmood2, Iyad Katib1

1Department of Computer Science, FCIT and 2High Performance Computing Center, King Abdulaziz University, KSA

[email protected], {RMehmood, iakatib}@kau.edu.sa

 

Ø
ØThis poster summarizes the driving forces, challenges, current and future trends associated with the convergence of HPC and Big Data.
ØAn architecture the converged future ofbased on Design Patterns is given.
Ø
 

 

ØData Analysis
ØData storage
ØLocality
ØScalable parallelism
ØFault tolerance
ØSimple execution environment
ØDynamic memory environment
ØSoftware sustainability
ØEnergy efficiency
ØSynchronization
ØMinimizing data movement
ØMemory wall

 

 

Ø
ØBig Data ‘V’ Characteristics
ØData confidentiality
ØHigh dimensionality
ØData reduction
ØAnalytical mechanism
ØComputational complexity
ØReal-time processing
ØDistributed computation
ØEnergy efficiency
ØNon-structured processing

 

ØLack of Predictive Analytics
ØLack of data granularity
ØLack of software flexibility to manipulate data
ØLack of intuitive user interfaces
ØSlow system performance
 
ØEmerging commercial HPC market segments
Ø(affinity marketing, precision medicines etc.)
ØSolution Urgency
ØIoT (Internet of Things)
ØSmart Cities
 
ØData locality
ØEnergy efficiency
ØScalable software infrastructure
ØHeterogeneity
ØReal time data analytics
ØFault tolerance
 
 
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