Adaptive parallel computing over distributed military
computing infrastructures
Rituraj Kumar
Center of Artificial Intelligence and Robotics – DRDO Lab
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Contents
Introduction Adaptive Parallel Computing Approaches for APC
MPI + DDS Hadoop
Conclusions
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Introduction
Net-Centric Paradigm of warfare needs highly compute intensive operations to be performed.
Parallel Computing is the only feasible solution that would guarantee reduced response time.
Tactical deployment would not amenable for – Large Clusters in the field Back-hauling
Intelligent use of the existing spare compute capacity of the computing devices within the cloud is essential.
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Adaptive Parallel Computing
MILCOM
Cloud of Heterogeneous Computing Devices
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Adaptive Parallel Computing
The Amdahl's law is concerned with the speedup achievable from an improvement to a computation that affects a proportion P of that computation where the improvement has a speedup of S.
Amdahls Law
Where,S = SpeedupP = Parallel fraction of ProgramN = Number of Processors
If 95% of the program can be parallelized, the theoretical maximum speedup using parallel computing would be 20×, no matter how many processors are used.
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Cost for parallel Computation = Computation Cost + Serialization Cost
Adaptive Parallel Computing
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APC Approaches
MPI Code:• Parallel implementation of
complex mathematical models
MPI Controller:• Execution of parallel MPI code
over distributed network.
DDS:• Reliable Communication over
challenged network.
DMI:• Identification of computing
nodes in the distributed network.
MPI Controller
DDS
Dynamic Membership
Identifier
MPI Code
MPI + DDS
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APC Approaches
Advantage:Well-known MPI API Framework. DDS provides assurance of reliable
communication between nodes.
Disadvantage:Needs a wrapper for converting MPI calls to DDS
framework.Performance degradation because of the wrapper.
MPI + DDS
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APC Approaches
Map/Reduce can be effectively used for parallelization
Used extensively in varieties of information systems.
Java Based Designed to handle large data sets
HADOOP
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APC Approaches
Advantage:Highly ScalableExcellent fault tolerance capabilitiesGood hardware interoperability
Current challenges:Requirement of slight architectural changesCurrently not suitable for resource constraint
hardware
Hadoop
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Conclusion
Military domain requires reliable parallel computing infrastructure over disadvantaged communication network.
Dynamic topology poses great challenge for computing infrastructure.
MPI framework has few disadvantages Hadoop is a promising candidate in these
conditions.
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Thank You