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HPC MCQ

The document discusses key concepts in parallel computing including sources of overhead, performance metrics, efficiency, speedup, scalability, and communication operations for matrix vector multiplication. It provides definitions and formulas for these concepts and indicates whether statements provided are true or false. Sources of overhead include essential computation, excess computation, inter-process communication, and idling. Performance metrics for parallel systems include execution time, total parallel overhead, speedup, efficiency, cost, and all of these.

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Jayaprabha Kanse
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2K views3 pages

HPC MCQ

The document discusses key concepts in parallel computing including sources of overhead, performance metrics, efficiency, speedup, scalability, and communication operations for matrix vector multiplication. It provides definitions and formulas for these concepts and indicates whether statements provided are true or false. Sources of overhead include essential computation, excess computation, inter-process communication, and idling. Performance metrics for parallel systems include execution time, total parallel overhead, speedup, efficiency, cost, and all of these.

Uploaded by

Jayaprabha Kanse
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as DOCX, PDF, TXT or read online on Scribd
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What are the sources of overhead?

A. Essential /Excess Computation


B. Inter-process Communication
C. Idling
D. All above

Answer : D

Which are the performance metrics for parallel systems?

A. Execution Time
B. Total Parallel Overhead
C. Speedup
D. Efficiency
E. Cost
F. All above

Answer : F

The efficiency of a parallel program can be written as: E = Ts / pTp. True or False?

A. True
B. False

Answer : A

Overhead function or total overhead of a parallel system as the total time collectively
spent by all the processing elements over and above that required by the fastest known
sequential algorithm for solving the same problem on a single processing element.
True or False?
A. True
B. False
Answer : A

What is Speedup?
A. A measure that captures the relative benefit of solving a problem in parallel. It is defined as the
ratio of the time taken to solve a problem on a single processing element to the time required to
solve the same problem on a parallel computer with p identical processing elements.
B. A measure of the fraction of time for which a processing element is usefully
employed.
C. None of the above
Answer : A

In an ideal parallel system, speedup is equal to p and efficiency is equal to one. True or
False?
A. True
B. False
Answer : A
A parallel system is said to be ________________ if the cost of solving a problem on a
parallel computer has the same asymptotic growth (in terms) as a function of the input
size as the fastest-known sequential algorithm on a single processing element.
A. Cost optimal
B. Non Cost optimal
Answer : A

Using fewer than the maximum possible number of processing elements to execute a
parallel algorithm is called ______________ a parallel system in terms of the number of
processing elements.

A. Scaling down
B. Scaling up
Answer : B

The __________________ function determines the ease with which a parallel system can
maintain a constant efficiency and hence achieve speedups increasing in proportion to the
number of processing elements.
A. Isoefficiency
B. Efficiency
C. Scalability
D. Total overhead
Answer : A

Minimum execution time for adding n numbers is Tp = n/p + 2 logp True or False ?
A. True
B. False
Answer : A

The overhead function To = pTP − TS.


A. True
B. False
Answer : A

Performance Metrics for Parallel Systems: Speedup(S) =TS/TP


A. True
B. False
Answer : A

Matrix Vector multiplication 2D Partitions requires some basic communication operations


A. one-to-one communication to align the vector along the main diagonal
B. one-to-all broadcast of each vector element among the n processes of each column
C. all-to-one reduction in each row
D. All Above
Answer : D

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