转帖| 手机上的超级计算

手机上的超级计算

bbsmrdj 2010-09-02 3055

简介

花费超级计算机几个小时时间的计算任务，在一台普通智能手机上只需要几秒就能模拟出很好的近似结果。研究者们正在全力以赴，打造更加优秀的计算方式。

Supercomputing on a cell phone

手机上的超级计算

For complex problems whose form can be anticipated but whose particulars can’t, new software can offer approximate solutions in seconds.

对于一些复杂的问题来说，模型可能是可以预见的，但是某些具体结果却不能，而新型的软件能在数秒钟之内提供近似的解决方案。

Many engineering disciplines rely on supercomputers to simulate complicated physical phenomena — how cracks form in building materials, for instance, or fluids flow through irregular channels. Now, researchers in MIT’s Department of Mechanical Engineering have developed software that can perform such simulations on an ordinary smart phone. Although the current version of the software is for demonstration purposes, the work could lead to applications that let engineers perform complicated calculations in the field, and even to better control systems for vehicles or robotic systems.

许多工程学科都仰仗于超级计算机来模拟复杂的物理现象 － 比如建筑材质如何发生溃裂，或者液体流过不规则管道等。现在，麻省理工机械工程研究所的研究者们开发了一种软件，可以在普通的智能手机上进行这样的模拟。尽管目前版本的软件只是作为演示用，这样的工作确会产生能让工程师在自己领域进行复杂计算的软件，甚至更好的车辆或机器人控制系统。

[IMG]- New software that runs on a smart phone can approximate in seconds computations that would take a supercomputer hours. The software works for problems whose form is know but whose particulars aren't; slider bars allow users to set the values for which they want the problems solved.

图解 － 运行在一个智能手机上的新软件能在数秒钟内近似出超级计算机要花费数小时才能得出的结果。这个软件可以用来解决那些模型已知，详细结果却未知的问题；滚动条允许用户设置他们希望解决的问题的参数值。

Image courtesy of David Knezevic and Dinh Bao Phuong Huynh.

图片由David Knezevic 和Dinh Bao Phuong Huynh 提供版权。

The new software works in cases where the general form of a problem is known in advance, but not the particulars. For instance, says Phuong Huynh, a postdoc who worked on the project, a computer simulation of fluid flow around an obstacle in a pipe could depend on a single parameter: the radius of the obstacle. But for a given value of the parameter, calculating the fluid flow could take an hour on a supercomputer with 500 processing units. The researchers’ new software can provide a very good approximation of the same calculation in a matter of seconds.

新软件工作在这样的情况下：一个问题的大致模型是可以预先知道的，但是精确的结果却未知。Phuong Huynh，一个工作在这个项目的博士后说道，例如一个计算机对流体流过管道内的一个障碍物的模拟可以依赖于一个单独的参数：障碍物的半径。但是对于给出的一个参数值，要计算流体流动会花费一台拥有500个计算单元的超级计算机一个小时的时间。而对于同样的计算，研究者的新软件可以在几秒内给出一个非常好的近似。

“This is a very relevant situation,” says David Knezevic, another postdoc in the department who helped lead the project. “Often in engineering contexts, you know a priori that your problem is parameterized, but you don’t know until you get into the field what parameters you’re interested in.”

“这是一个非常切题的情况，”David Knezevic，部门另外一个帮助领导这个项目的博士后说道，“通常在工程领域，你已经预先知道你的问题是参数化的，但是除非你进入到相关领域里去，否则你不会知道哪些参数是你感兴趣的。”

Each new problem the researchers’ software is called upon to solve requires its own mathematical model. The models, however, take up very little space in memory: A cell phone could hold thousands of them. The software, which is available for download, comes preloaded with models for nine problems, including heat propagation in objects of several different shapes, fluid flow around a spherical obstacle, and the effects of forces applied to a cracked pillar. As the researchers develop models for new classes of problems, they post them on a server, from which they can be downloaded.

研究者的软件被调用来解决的每一个新的问题都需要它们自己的数学模型。然而，模型只在内存中占用了非常小的一块地方：一个手机可以加载成千上万个模型。这个已经可以下载的软件，预先加载了9个问题的模型，包括不同形状物体的热传播，流体留过一个球形障碍物，以及对破裂的支柱施力的各种效果。在研究者开发出新的问题种类的模型时，他们会把它们发布到一台服务器上供大家下载。

Advance work

前期工作

But while the models are small, creating them is a complicated process that does in fact require a supercomputer. “We’re not trying to replace a supercomputer,” Knezevic says. “This is a model of computation that works in conjunction with supercomputing. And the supercomputer is indispensable.”

虽然模型很小，创建它们却是一个复杂的，切实需要超级计算机的过程。“我们并没有尝试去替代一台超级计算机，”Knezevic 说，“这是一个和超级计算协同工作的计算模型。而且超级计算机是不可或缺的。

Knezevic, his fellow postdoc Phuong Huynh, Ford Professor of Engineering Anthony T. Patera, and John Peterson of the Texas Advanced Computer Center describe their approach in a forthcoming issue of the journal Computers and Fluids. Once they have identified a parameterized problem, they use a supercomputer to solve it for somewhere between 10 and 50 different sets of values. Those values, however, are carefully chosen to map out a large space of possible solutions to the problem. The model downloaded to a smart phone finds an approximate solution for a new set of parameters by reference to the precomputed solutions.

Knezevic，以及他的博士后同事Phuong Huynh，福特工程教授Anthony T. Patera，和得克萨斯高级计算机中心的John Peterson，描述了他们处理即将到来的日志（journal）计算机和流体问题的方式。一旦他们鉴定出了可参数化的问题，就会用超级计算机去解决大约10 到50 组数据。不过，这些数据是经过仔细挑选的，必须覆盖这个问题可能的结局方案的大多数值空间。这个模型会被下载到智能手机上，通过引用预先计算好的结果来找到一个对应新的参数组的近似结果。

The key to the system, Knezevic says, is the ability to quantify the degree of error in an approximation of a supercomputing calculation, a subject that Patera has been researching for almost a decade. As the researchers build a problem model, they select parameters that will successively minimize error, according to analytic techniques Patera helped developed. The calculation of error bounds is also a feature of the phone application itself. For each approximate solution of a parameterized problem, the app also displays the margin of error. The user can opt to trade speed of computation for a higher margin of error, but the app can generally get the error under 1 percent in less than a second.

Knezevic 说，这个系统的关键是定量在近似超级计算机计算结果时的错误程度的能力，这个课题Patera 已经研究了将近10年。在研究者建立完一个问题的模型之后，他们根据Patera 帮助开发的分析技术，选择能够成功最小化错误的参数。计算错误边界也是这个手机程序的一个特性。对于每一个参数化问题的近似结果，这个程序也会显示误差的边界。用户可以用更高的误差来换取更快的计算速度，不过这个程序已经能在不到1秒的时间获得小于百分之一的误差。

Turning the tables

反客为主

While the researchers’ software can calculate the behavior of a physical system on the basis of its parameters, it could prove even more useful by doing the opposite: calculating the parameters of a physical system on the basis of its behavior. Instead of, say, calculating fluid flow around an obstacle based on the obstacle’s size, the software could calculate the size of the obstacle based on measurements of the fluid flow at the end of a pipe. Ordinarily, that would require several different computations on a supercomputer, trying out several different sets of parameters. But if testing, say, 30 options on a supercomputer would take 30 hours, it might take 30 seconds on a phone. Indeed, the researchers have already developed a second application that calculates such “inverse problems.”

虽然研究者们的软件可以根据参数计算一个物理系统的行为，但是把它反过来用被证明更加有用：根据一个物理系统的行为计算它的参数。这个软件可以根据测量管道重点的流体流动来计算障碍物的大小，而非仅仅根据障碍物大小来测量周围的流体流动。通常，这会需要一台超级计算机的几个不同计算结果，测试出几组不同的参数。但是如果是测试的话，30 组可能会花上超级计算机30个小时，而手机上则要30秒。当然，研究者已经开发出了另外一个程序来计算这些“反向问题”。

In the same way that a simulation of a physical system describes its behavior on the basis of parametric measurements, control systems, of the type that govern, say, automotive brake systems or autonomous robots, determine devices’ behavior on the basis of sensor measurements. Control-systems researchers spend a great deal of energy trying to come up with practical approximations of complex physics in order to make their systems responsive enough to work in real time. But Knezevic, Huynh and Patera’s approach could make those approximations both more accurate and easier to calculate.

和物理模拟系统基于参数测量描述它们的行为一样，像控制系统这样的管理类型系统，比如汽车的刹车系统或者独立行动的机器人，通过感应器的测量数据来决定设备的行为。控制系统研究者们花了很大的精力尝试计算出复杂物理系统的实用性近似，来使得他们的系统能足够快地反应和工作在实时状态下。但是Knezevic，Huynh 和Patera 的方法可以使得这些近似更准确，更容易计算。

Max Gunzberger, Frances Eppes Eminent Professor of Scientific Computing at Florida State University says that the MIT researchers’ work has a “cuteness aspect” that has already won it some attention. But “once you get over the cuteness factor,” he says, “if you talk about serious science or serious engineering, there’s a potential there.” Gunzberger points out that while the researchers’ demo concentrates on fluid mechanics, “there’s lots of other problems that their approach can be applied to. They built the structure that they themselves or others can start using to solve problems in different application areas.”

Max Gunzberger，法国埃普杰出的科学计算学教授，先任职于佛罗里达州立大学，说麻省理工研究者的工作有一个“可爱的方面”已经引起了一些注视。但是，“一旦你忘记这些可爱的因素，”他说，“如果你开始讨论严肃的科学和科学工程，它们确实有潜力。”Gunzberger 在研究者们的演示尚集中在流体力学时指出，“他们的方法可以应用在很多其它问题上。他们建立的结构可以被他们自己或者其他人用来开始解决不同应用领域的实际问题。”