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Welcome to the Pipeline and Vector Processing MCQs Page

Dive deep into the fascinating world of Pipeline and Vector Processing with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Pipeline and Vector Processing, a crucial aspect of Computer Architecture. In this section, you will encounter a diverse range of MCQs that cover various aspects of Pipeline and Vector Processing, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Computer Architecture.

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Check out the MCQs below to embark on an enriching journey through Pipeline and Vector Processing. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Computer Architecture.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Pipeline and Vector Processing. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Pipeline and Vector Processing MCQs | Page 6 of 21

Explore more Topics under Computer Architecture

Q51.
A solution of the problem for representing parallelism in an algorithm is
Discuss
Answer: (c).CUDA
Q52.
The primary and essential mechanism to support the sparse matrices is
Discuss
Answer: (a).Gather-scatter operations
Q53.
In later iterations, data accesses are dependent on the values of data produced in earlier iterations; this dependence is called a
Discuss
Answer: (d).Loop-carried dependence
Q54.
The form of the Loop-carried dependences is,
Discuss
Answer: (b).Recurrence
Q55.
When the vector gets longer than the max length of its, then a technique called
Discuss
Answer: (d).Strip mining
Q56.
The horizontal and diagonal roofs when meeting offers, insight into the computer is known as
Discuss
Answer: (a).Ridge point
Q57.
The on-chip memory which is local to every multithreaded Single Instruction Multiple Data (SIMD) Processor is called
Discuss
Answer: (a).Local Memory
Q58.
A processor, assigned with a thread block, that executes a code, which we usually call a
Discuss
Answer: (b).Multithreaded SIMD Processor
Q59.
A code, known as Grid, which runs on a GPU consisting of a set of
Discuss
Answer: (d).Thread Block
Q60.
The machine object created by the hardware, managing, scheduling, and executing is a thread of
Discuss
Answer: (c).SIMD instructions

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