12 Questions
Explain how a SISD parallel computer works and provide an example of such a system.
In a SISD system, a single instruction stream is processed by a single processor. An example is a traditional desktop or laptop computer.
Describe the operation of a SIMD parallel computer and give an example of a SIMD system.
In a SIMD system, a single instruction is applied to multiple data streams simultaneously. An example is a GPU (Graphics Processing Unit).
How does a MIMD parallel computer function and provide an instance of a MIMD system?
In a MIMD system, multiple processors execute different instructions on different data. An example is a cluster of networked computers.
Explain the working principle of a SPMD parallel computer and mention a system that follows the SPMD model.
In SPMD architecture, multiple processors execute the same program but on different data. An example is MPI (Message Passing Interface) based systems.
How does a MISD parallel computer operate and provide a real-world example of a MISD system.
MISD systems have multiple processors executing different instructions on the same data. An example is fault-tolerant systems that use multiple error-checking mechanisms.
What is the maximum speedup we can achieve by increasing the number of processing units to 32, then to 64, and then to 128 for a program where 70% of the execution can be parallelized?
The maximum speedup for 32 processing units is 3.33, for 64 processing units is 5.71, and for 128 processing units is 10.
Explain the concept of scaled speedup in parallel computing.
Scaled speedup in parallel computing refers to the ratio of the execution time on a single processor to the execution time on multiple processors. It measures how efficiently an application can utilize additional processors.
What is Gustafson’s Law and how does it relate to achieving a speedup goal?
Gustafson’s Law states that as the number of processors increases, the problem size can be increased to keep the workload balanced, resulting in a speedup that grows linearly with the number of processors. It is used to determine the fraction of inherently sequential operations that can be tolerated to achieve a desired speedup.
Explain the difference between the maximum speedup predicted by Amdahl’s Law and Gustafson’s Law as the number of processors increases.
The maximum speedup predicted by Amdahl’s Law converges to a limit as the number of processors increases, due to the fixed fraction of serial work. In contrast, Gustafson’s Law allows for unbounded speedup as the number of processors increases by scaling the problem size.
Calculate the peak achievable performance of a dot product of two vectors considering the memory system specifications provided.
The peak achievable performance of a dot product of two vectors is 40MFLOPS, assuming 2 multiply-add units and considering memory fetches. If cache read time and CPU cycle are also counted, the rate is 38.64MFLOPS.
What is the effective memory access time of one processor in a distributed shared-address-space SMP system with specified memory access latencies?
The effective memory access time of one processor is 19.7MFLOPS. If the computation is memory-bound, the peak computation rate would be 19.7MFLOPS.
Discuss the importance of load balancing in parallel computing and its impact on overall performance.
Load balancing in parallel computing ensures that work is evenly distributed among processors, avoiding idle processors and maximizing resource utilization. It improves performance by minimizing execution time and preventing bottlenecks.
Learn about Flynn's taxonomy for parallel systems - SISD, SIMD, MIMD, SPMD, and MISD. Understand how each type of parallel computer works with examples. Also, delve into memory access in parallel hardware, calculating maximum execution time for each PE to access data items.
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