Question: Computer Science student reads on stack overflow that software algorithms can be made faster by parallelizing their execution- this makes sense, why count to a

 Computer Science student reads on stack overflow that software algorithms can

Computer Science student reads on stack overflow that software algorithms can be made faster by parallelizing their execution- this makes sense, why count to a billion when you can count to 100 million 10 times and add up the results. Student downloads and installs the recommended parallel execution library for the language being used, but notices that the program either slows down or runs at the same speed when using the library in different runs. Which of the following could explain the student's findings? Select all that could apply. Pick the correct choices Programming language of choice does not actually support native parallel execution despite availability of library. The chosen algorithm simply cannot be executed in a parallel fashion, a property of the algorithm. The overhead of parallelism outweighs the benefits of adding parallelism leading to net slow down in algorithm execution The system running the algorithm does not have appropriate resources to execute the algorithm faster in a parallel fashion than it does in a serial fashion. The memory ordering properties of the system caused the calculation to be repeated multiple times instead of just once, with the most accurate answer being selected. Computer Science student reads on stack overflow that software algorithms can be made faster by parallelizing their execution- this makes sense, why count to a billion when you can count to 100 million 10 times and add up the results. Student downloads and installs the recommended parallel execution library for the language being used, but notices that the program either slows down or runs at the same speed when using the library in different runs. Which of the following could explain the student's findings? Select all that could apply. Pick the correct choices Programming language of choice does not actually support native parallel execution despite availability of library. The chosen algorithm simply cannot be executed in a parallel fashion, a property of the algorithm. The overhead of parallelism outweighs the benefits of adding parallelism leading to net slow down in algorithm execution The system running the algorithm does not have appropriate resources to execute the algorithm faster in a parallel fashion than it does in a serial fashion. The memory ordering properties of the system caused the calculation to be repeated multiple times instead of just once, with the most accurate answer being selected

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