Computer-Parallel Computing MCQ

Computer-Parallel Computing MCQ
21. Asynchronous communications
  • It involves data sharing between more than two tasks, which are often specified as being members in a common group, or collective
  • It involves two tasks with one task acting as the sender/producer of data, and the other acting as the receiver/consumer.
  • It allows tasks to transfer data independently from one another.
  • None of these
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22. Granularity is
  • In parallel computing, it is a qualitative measure of the ratio of computation to communication
  • Here relatively small amounts of computational work are done between communication events
  • Relatively large amountls of computational work are done between communication / synchronization events
  • None of these
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23. Coarrse-grain Parallelism
  • In parallel computing, it is a qualitative measure of the ratio of computation to communication
  • Here relatively small amounts of computational work are done between communication events
  • Relatively large amountsl of computational work are done between communication / synchronization events
  • None of these
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24. Cache Cherent UMA (CC-UMA) is
  • Here all processors have equal access and access times to memory
  • Here if one processor updates a location in shared memory, all the other processors know about the update
  • Here one SMP can directly access memory of another SMP and not all processors have equal access time to all memories
  • None of these
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25. NOn-Uniform Memory/Access (NUMA) is
  • Here all processors have equal access and access times to memory
  • Here if one processor updates a location in shared memory, all the other processors know about the update
  • Here one SMP can directly access memory of another SMP and not all processors have euqal access time to all memories
  • None of these
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26. It distinguished multi-processor computer architectures according to how they can be classified along the two independent dimentions of instruction and Dat (A) Each of these dimensions can have only one of two possible states: Single or Multiple.
  • Single Program Multiple Data (SPMD)
  • Flynn's taxonomy
  • Von Neumann Architecture
  • None of these
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27. In the threads model of parallel programming
  • A single process can have multiple concurrent execution paths
  • A single proces can have single, concurrent execution paths.
  • A multiple process can have single concurrent execution paths.
  • None of these
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28. These applications typically have multiple executable object files (programs). While the application is being run in parallel. each task can be executing the same or different program as other tasks. All tasks may use different data
  • Single Program Multiple Data(SPMD)
  • Multiple Program Multiple Data (MPMD)
  • Von Neumann Architecture
  • None of these
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29. Here a single program is executed by all tasks simultaneously. At any moment in time, tasks can be executing the same or different instructions within the same program. These programs usually have the necessary logic programmed into them to allow different tasks to branch or conditionally execute only those parts of the program  they are designed to execute.
  • Single Program Multiple Data (SPMD)
  • Multiple Program Multiple Data (MPMD)
  • Von Neumann Architecture
  • None of these
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30. These computers uses the stored-program concept. Memory is used to store both program and data instructions and central processing unit (CPU) gets instructions and /or data from memory. CPU, decodes the instructions and then sequentially performs them.
  • Single, program Multiple Data (SPMD)
  • Flynn's taxonomy
  • Von Neumann Architecture
  • None of these
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