### 计算机代写|并行计算作业代写Parallel Computing代考|Nested parfor and for-Loops and Other parfor Requirements

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## 计算机代写|并行计算作业代写Parallel Computing代考|Nested parfor-Loops

You cannot use a parfor-loop inside another par for-loop. As an example, the following nesting of parfor-loops is not allowed:
parfor $i=1: 10$
parfor $j=1: 5$
end
end
Tip You cannot nest parfor directly within another parfor-loop. A parfor-loop can call a function
that contains a parfor-loop, but you do not get any additional parallelism.
Code Analyzer in the MATLAB Editor flags the use of parfor inside another parfor-loop:
PARFOR or SPMD cannot be used inside another PARFOR loop.
You cannot nest parfor-loops because parallelization can be performed at only one level. Therefore, choose which loop to run in parallel, and convert the other loop to a for-loop.
Consider the following performance issues when dealing with nested loops:

• Parallel processing incurs overhead. Generally, you should run the outer loop in parallel, because overhead only occurs once. If you run the inner loop in parallel, then each of the multiple parfor executions incurs an overhead. See “Convert Nested for-Loops to parfor-Loops” on page $2-14$ for an example how to measure parallel overhead.
• Make sure that the number of iterations exceeds the number of workers. Otherwise, you do not use all available workers.
• Try to balance the parfor-loop iteration times. parfor tries to compensate for some load imbalance.

## 计算机代写|并行计算作业代写Parallel Computing代考|Convert Nested for-Loops to parfor-Loops

A typical use of nested loops is to step through an array using a one-loop variable to index one dimension, and a nested-loop variable to index another dimension. The basic form is:
$X=z e \cos (n, m) ;$
for $a=1: n$
for $b=1: m$
$X(a, b)=f u n(a, b)$
end
end
The following code shows a simple example. Use tic and toc to measure the computing time needed.
$\mathrm{A}=100 ;$
tic
for $i=1: 100$
for $j=1: 100$
$a(i, j)=\max (a b s($ eig $($ rand $(A))))$;
end
end
toc
Elapsed time is 49.376732 seconds.
You can parallelize either of the nested loops, but you cannot run both in parallel. The reason is that the workers in a parallel pool cannot start or access further parallel pools.
If the loop counted by $i$ is converted to a parfor-loop, then each worker in the pool executes the nested loops using the j loop counter. The j loops themselves cannot run as a parfor on each worker.
Because parallel processing incurs overhead, you must choose carefully whether you want to convert either the inner or the outer for-loop to a parfor-loop. The following example shows how to measure the parallel overhead.
First convert only the outer for-loop to a parfor-loop. Use tic and toc to measure the computing time needed. Use ticBytes and tocBytes to measure how much data is transferred to and from the workers in the parallel pool.

Run the new code, and run it again. The first run is slower than subsequent runs, because the parallel pool takes some time to start and make the code available to the workers.
$\mathrm{A}=100 ;$
tic

## 计算机代写|并行计算作业代写Parallel Computing代考|Nested for-Loops: Requirements and Limitations

If you want to convert a nested for-loop to a parfor-loop, you must ensure that your loop variables are properly classified, see “Troubleshoot Variables in parfor-Loops” on page 2-29. If your code does not adhere to the guidelines and restrictions labeled as Required, you get an error. MATLAB catches some of these errors at the time it reads the code. These errors are labeled as Required (static).
Required (static): You must define the range of a for-loop nested in a parfor-loop by constant numbers or broadcast variables.
In the following example, the code on the left does not work because you define the upper limit of the for-loop by a function call. The code on the right provides a workaround by first defining a broadcast or constant variable outside the parfor-loop:
$\begin{array}{ll}\text { Invalid } & \text { Valid } \ \begin{array}{ll}A=\text { zeros }(100,200) ; & A=\operatorname{zeros}(100,200) ; \ \text { parfor } i=1: \operatorname{size}(A, 1) & n=\operatorname{size}(A, 2) ; \ \text { for } j=1: \operatorname{size}(A, 2) & \text { parfor } i=1: \operatorname{size}(A, 1) \ \text { fand }(i, j)=i+j ; & \text { for } j=1: n \ \text { end } & \text { end }(i, j)=i+j ; \ \text { end } & \text { end }\end{array}\end{array}$
Required (static): The index variable for the nested for-loop must never be explicitly assigned other than by its for statement.

Following this restriction is required. If the nested for-loop variable is changed anywhere in a parfor-loop other than by its for statement, the region indexed by the for-loop variable is not guaranteed to be available at each worker.
The code on the left is not valid because it tries to modify the value of the nested for-loop variable $j$ in the body of the loop. The code on the right provides a workaround by assigning the nested forloop variable to a temporary variable $t$, and then updating $t$.

## 计算机代写|并行计算作业代写Parallel Computing代考|Nested parfor-Loops

parfor一世=1:10

end
end

MATLAB 编辑器中的代码分析器标记 parfor 在另一个 parfor 循环内的使用：
PARFOR 或 SPMD 不能在另一个 PARFOR 循环内使用。

• 并行处理会产生开销。通常，您应该并行运行外循环，因为开销只发生一次。如果您并行运行内部循环，则每次执行 parfor 都会产生开销。请参阅第 1 页的“将嵌套的 for 循环转换为 parfor 循环”2−14例如如何测量并行开销。
• 确保迭代次数超过工作人员的数量。否则，您不会使用所有可用的工作人员。
• 尝试平衡 parfor 循环的迭代时间。parfor 试图补偿一些负载不平衡。

## 计算机代写|并行计算作业代写Parallel Computing代考|Convert Nested for-Loops to parfor-Loops

X=和和因⁡(n,米);

X(一种,b)=F在n(一种,b)
end
end

_一世=1:100

end
end
toc

## 计算机代写|并行计算作业代写Parallel Computing代考|Nested for-Loops: Requirements and Limitations

无效的  有效的  一种= 零 (100,200);一种=零⁡(100,200);  帕尔福 一世=1:尺寸⁡(一种,1)n=尺寸⁡(一种,2);  为了 j=1:尺寸⁡(一种,2) 帕尔福 一世=1:尺寸⁡(一种,1)  成立 (一世,j)=一世+j; 为了 j=1:n  结尾  结尾 (一世,j)=一世+j;  结尾  结尾

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## MATLAB代写

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