High Performance Computing MCQs with answers Page - 13

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Q. Out-of-order instructions is not possible on GPUs.

  • (A) true
  • (B) false
  • (C) --
  • (D) --

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Q. CUDA supports programming in ....

  • (A) c or c++ only
  • (B) java, python, and more
  • (C) c, c++, third party wrappers for java, python, and more
  • (D) pascal

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Q. FADD, FMAD, FMIN, FMAX are ----- supported by Scalar Processors of NVIDIA GPU.

  • (A) 32-bit ieee floating point instructions
  • (B) 32-bit integer instructions
  • (C) both
  • (D) none of the above

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Q. Each streaming multiprocessor (SM) of CUDA herdware has ------ scalar processors (SP).

  • (A) 1024
  • (B) 128
  • (C) 512
  • (D) 8

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Q. Each NVIDIA GPU has ------ Streaming Multiprocessors

  • (A) 8
  • (B) 1024
  • (C) 512
  • (D) 16

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Q. CUDA provides ------- warp and thread scheduling. Also, the overhead of thread creation is on the order of ----.

  • (A) “programming-overhead”, 2 clock
  • (B) “zero-overhead”, 1 clock
  • (C) 64, 2 clock
  • (D) 32, 1 clock

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Q. Each warp of GPU receives a single instruction and “broadcasts” it to all of its threads. It is a ---- operation.

  • (A) simd (single instruction multiple data)
  • (B) simt (single instruction multiple thread)
  • (C) sisd (single instruction single data)
  • (D) sist (single instruction single thread)

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Q. Limitations of CUDA Kernel

  • (A) recursion, call stack, static variable declaration
  • (B) no recursion, no call stack, no static variable declarations
  • (C) recursion, no call stack, static variable declaration
  • (D) no recursion, call stack, no static variable declarations

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Q. What is Unified Virtual Machine

  • (A) it is a technique that allow both cpu and gpu to read from single virtual machine, simultaneously.
  • (B) it is a technique for managing separate host and device memory spaces.
  • (C) it is a technique for executing device code on host and host code on device.
  • (D) it is a technique for executing general purpose programs on device instead of host.

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Q. _______ became the first language specifically designed by a GPU Company to facilitate general purpose computing on ____.

  • (A) python, gpus.
  • (B) c, cpus.
  • (C) cuda c, gpus.
  • (D) java, cpus.

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