Computer Science计算机科学在互联网大潮中成为热门专业，越来越多的留学生把cs作为首选，除了就业前景好之外，其薪酬也很可观。但是作为大热专业，CS的各种作业，assignment和大大小小的exam、quiz难度都很大，对学生的英语能力和专业技能要求极高。迫于学业压力，选择TopMask的CS代考服务来帮您减轻压力吧！
CS代考价格一般是多少？
随着疫情的持续发展，网络授课仍是主要的授课方式，大部分考试在线上进行，选择代考也是留学生减轻学业压力的方式之一。那么CS代考的价格是多少钱？
时长：要说影响代考价格的首要因素，就是代考时长。在大部分代考服务机构，基本上是按照小时收费的，所以代考时间越长，题量越多价格也越高啦。一般来说，日常的测验、test都是小型考试，在一个小时左右，价格相交与final exam会便宜一些。
难度：第二个会影响价格的因素就是难度，高中、本科、以及硕士研究生等不同学术阶段的难度是不一样的，这很容易理解，代考价格也不同。
个人需求：在TopMask帮助过的客户中，不同的客户有不同的要求。有些同学只需要pass，有些同学则需要保证拿A，那么代考价格就会在基础报价上有所增加。
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下面是一个英国CS代考高分案例，COMP322101
Many parallel algorithms require, at some stage, variables distributed across multiple processing units to be reduced to a single value by a binary operation. This reduced value must then be made accessible to all processing units. For instance, in a series of vector operations, it may happen that the result of the scalar product of two vectors must then be made available to all processing units for the next stage in the calculations.
(a) For shared memory systems, where the processing units are threads, all threads can read the memory location containing the reduced value. However, they should not begin subsequent calculations until the reduction calculation has been completed.
(i) For a GPU, suppose the reduction had been completed by threads within a single work group. Why is it beneficial to use local, rather than global, memory for intermediate calculations in this situation?
(ii) Still for a GPU, how would you ensure the result of the reduction performed by a single work group, in local memory, has been completed, and can be read by all threads for the subsequent calculations? Explain your answer.
(b) For distributed memory systems, where processing units are processes, the issue becomes communicating the result of the reduction to all processes. Suppose that, after the reduction, the reduced value is known only to one process, e.g. rank 0 for MPI.
(i) What form of collective communication should be used to send the reduced value to all processes? You do not need to give the actual MPI function name, but may do so if you like.
(ii) Someone suggests using point-to-point instead of collective communication, and you rightly point out that this will likely be slower than using collective communication. Justify this claim by estimating how the communication time tcomm varies with the total number of processes numProcs for both methods. You should assume that the collective communication uses a binary tree.
(iii) Given barriers are not used in the binary tree, how might the necessary synchronization be achieved?
(iv) In fact, MPI already provides a function MPI Allreduce that both reduces, and distributes the final answer to all processes. One possible implementation is essentially a combination of binary trees. An example is given in Fig. 1 for numProcs=4. Redraw Fig. 1 for the case numProcs=2, for which there will be 2 levels rather than 3, and therefore 4 nodes in total.
(v) How many communications are there in total?
(vi) Returning to Fig. 1, note that in the final row of communications, some processes send two partial sums whereas others send none. How would you alter this final exchange of partial sums to make the communication better balanced, i.e. so processes send at most one partial sum? Use the given rank numbers in your answer.
(c) Notice that Fig. 1 is a task graph. Assume that each task (node) corresponds to the same amount of time, including those on the top and bottom rows.
(i) What is the work and span of the task graph given in Fig. 1? What is the maximum performance as predicted by the work-span model?
(ii) Suppose there are p = 2m processes. What is the work, span, and prediction of the work-span model now, for arbitrary m? (iii) It has been assumed that each task takes the same time to execute. Suppose each task now takes a different, but known, time to execute. Describe in general terms how you would modify the definition of work and span, and the prediction of the work–span model, for this situation. You do not need to derive expressions or perform actual calculations, but should explain your answer.
