并行处理效率是否可以> 1个? [英] Can a Parallel Processing Efficiency become > 1?
问题描述
我了解了并行计算的效率，但从未对此有个清楚的主意，也了解了实现效率的方法 >1 ，并得出结论认为，它可能是超线性的.
I read about efficiency in parallel computing, but never got an clear idea about it, also I read about achieving efficiency >1 and conclude that it's possible when it's a super linear.
那是正确的并且可能吗?
Is that correct and possible?
如果是，那么有人可以告诉我如何做并提供示例吗?
If yes, then can anybody tell me how and provide an example for that?
或者，如果不是，那为什么呢?
Or, if it is not, then why?
推荐答案
让我们首先同意一些条款:
可能会安排一套流程以几种不同的策略执行-
Let's agree on a few terms first:
A set of processes may get scheduled for execution under several different strategies --
-
[SERIAL]-即一次又一次地执行，直到全部完成为止，或者 -
[PARALLEL]-即一次全部开始，一次全部执行，一次全部终止
或
- 以恰好"-
[CONCURRENT]的方式-即，在资源允许的情况下，一些会立即开始，而在空闲或新资源允许的情况下，会安排其他人执行[CONCURRENT].处理过程逐步完成，但没有任何协调，就像资源映射和优先级所允许的那样.
- in a "just"-
[CONCURRENT]fashion - i.e. some start at once, as resources permit, others are scheduled for[CONCURRENT]execution whenever free or new resources permit. The processing gets finished progressively, but without any coordination, just as resources-mapping and priorities permit.
鉴于效率可能与功耗或处理时间有关，让我们关注处理时间，好吗?
Given an efficiency may be related to power-consumption or to processing-time, let's focus on processing-time, ok?
Gene Amdahl阐述了通用处理加速领域，我们将从这里借鉴. HPC/计算机科学教育中的常见问题是，讲师不强调组织并行处理的现实成本.因此，应始终在 overhead-strict 重新制定公式时使用Amdahl定律的开销过高的原始格式(原始)，因为否则，任何朴素的数字都应使用并行计算 只是比较苹果和桔子.
Gene Amdahl has elaborated domain of generic processing speedups, from which we will borrow here. The common issue in HPC / computer science education is that lecturers do not emphasise the real-world costs of organising the parallel-processing. For this reason, the overhead-naive ( original ) formulation of the Amdahl's Law ought be always used in an overhead-strict re-formulation, because otherwise any naive-form figures are in parallel-computing just comparing apples to oranges.
另一方面，一旦将流程增加的制造费用和流程终止的增加的费用两者都记录到方案中，开销限制的提速比较就会开始进行谈论处理时间效率.
On the other hand, once both the process-add-on-setup-overhead costs and process-termination-add-on-overhead costs are recorded into the scheme, the overhead-strict speedup comparison starts to make sense to speak about processing-time efficiency.
话虽如此，在某些情况下，处理时间效率可以提高为 > 1 ，可以说，必须采取专业的应有的谨慎态度，而不是全部处理由于有义务支付和支付NUMA/分布式处理开销的附加成本，因此-类型可以在任何大规模的代码执行资源池上获得显着的加速.
Having said this, there are cases, when processing-time efficiency can become > 1, while it is fair to say, that a professional due care has to be taken and that not all processing-types permit to gain any remarkable speedup on whatever large-scale pool of code-execution resources, right due to the obligation to pay and cover the add-on costs of the NUMA / distributed-processing overheads.
with an overhead-strict Amdahl Law re-formulation
[PARALLEL]-processing speedups GUI-interactive-tool cited here
在瑞典，您必读的书是从Kickstarter到获得DARPA的 [PARALLEL]-硬件的过程中，有很多
Being in Sweden, your must-read is the Andreas Olofsson's personal story about his remarkable effort and experience with piloting parallel-hardware with many first-ever-s on the way from Kickstarter to a DARPA-acquired [PARALLEL]-hardware know-how.
这篇关于并行处理效率是否可以> 1个?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
