Friday format: IaaS and science - how it works
/ photo Guilherme Yagui CC The
amount of data collected in various fields of science is constantly growing, which allows researchers to build realistic models and conduct accurate simulations based on them. However, every year this requires ever greater computing power.
Cloud technologies and IaaS provide users with resources that meet the requirements of the task: the required amount of memory and storage, the right number of processors. Thanks to this, research teams of all sizes are able to solve problems without investing huge amounts of money in computer infrastructure.
All this greatly helps in conducting research. An example is the University of São Paulo - the largest university in Brazil, which was already discussed in one of our previous posts . In 2012, university management decided to implement the USP Cloud project. In the course of the work, it was planned to form 6 out of 150 disparate university data centers, and collect corporate, research and educational environments into a massive private cloud.
When the project was implemented, the USP acquired the opportunity to conduct research, being at a great distance from the studied object, and students - the opportunity to study online. More than 150 thousand people got access to lectures, mail, a digital library, as well as museum collections.
“The cloud allows researchers to achieve results much faster, which contributes to the rapid penetration of information technology at the university,” explains Antonio Roque Dechen, Executive Vice President of Management and Professor at the College of Agriculture at Luis de Keyruos University of São Paulo. “It speeds up research and development by providing safe and mobile access to critical educational tools.”
Mankind is gradually realizing the full potential of cloud computing, therefore seeks to apply this technology to solve major scientific and industrial problems. Therefore, later in the article we will consider several areas in which IaaS are effectively used-technology.
One of the common problems when conducting large-scale research in physics is the management of data sets. To solve this problem, cloud computing is suitable, with which users gain remote access to arrays of information and distributed computing resources. For example, IaaS clouds can be effectively used to process experimental data from high-energy physics.
A group of scientists from Canada has developeddistributed cloud system using IaaS clusters in Canada and the USA. The user of such a system can write batch jobs for the analytical virtual machine and transfer them to the central scheduler. The system will automatically prepare one of the virtual machines in the cloud and run the user application on it, which, in turn, will have free access to the central database with calibration data.
The virtual machine has installed BaBar software that simulates collisions of charged particles: it measures their motion paths and energy. Tests have shown that the system is able to efficiently perform hundreds of batch tasks at the same time, and its potential is not limited.
Astronomy is a science adjacent to physics, and it also generates terabytes of data. Their processing each time brings us closer to understanding the structure of the universe. The use of cloud computing is also very common in this area.
For example, in the “clouds”, the collisions of galaxies are simulated using the GADGET application. It is specially designed for simulations on parallel computing systems and uses tree-based algorithms to evaluate the effect of gravitational forces on nearby particles.
/ NASA's Earth Observatory CC photo
Also worth noting the missionKepler Space Telescope, launched by NASA in 2009. Equipped with an ultra-sensitive photometer, it was created with the goal of finding planets like the Earth outside the solar system. By the beginning of 2014, they had discovered 3,500 candidates for the planet, of which more than 1,000 were confirmed by various scientific groups of researchers.
“Kepler” with great accuracy measures the intensity of light coming from distant stars and detects its change when the planet passes through the star’s disk. The analysis of such signals requires the calculation of periodograms and an assessment of their significance, and this is impossible without serious computing resources.
Cloud computing allows you to parallelize computing, and speed up data processing. For example, executing a task on a cluster of 128 Dell PowerEdge 1950 machines increased the performance of algorithms hundreds of times.
Another example is the system developed by Canadian scientists. They combined the Canadian Advanced Network for Astronomical Research (CANFAR) cloud computing system with Skytree's advanced machine learning software, thereby creating the first cloud-based data mining system used in astronomy.
Now more than 500 processor cores and several hundred terabytes of reliable storage are available. Virtual machines can perform large-scale computing and operate with millions of objects, but this is far from the limit of the CANFAR + Skytree system.
In 2015, the Gartner analytic company published its study of the “maturity cycle” of developing technologies. On the graph, technologies are distributed according to how large their adoption by the majority is.
The new document says that at the peak of high expectations are unmanned vehicles and the Internet of things. However, one of the main technological and advanced areas remains robotics.
The full potential of the robots is not fully disclosed, but clouds will soon help with this. History is rooted in the early 1990s. With the advent of the first Mosaic browser, a professor and students from the University of Southern California began to develop the idea of webcasts from cameras.
At the same time, the team decided to move away from the concept of passive monitoring of what is happening and create a robot that looks after a garden with living plants. For these purposes, an industrial manipulator has been adapted, equipped with a camera, an irrigation system and a nozzle for collecting seeds. Roboruk was installed in the center of a three-meter flowerbed, and users could control it using a specially designed graphical interface. "Telesad", the project received this name, became the first active device working on the network.
Since then, robotics has advanced far enough. At the moment, there are hundreds of research laboratories that have developed more than 5 million service robots that are cleaned in homes and offices, and more than 3 thousand robots that help surgeons in operating rooms around the world.
But so far it is impossible to create a robot that would arrange things in the house in its place. Such work is difficult for them. This problem was addressed by Andrew Eun (Andrew Ng) during his speech at Stanford University.
The problem lies in the fact that he is not able to remember all household items - there is always something that he is not familiar with. A new remote control from the TV, a new baby toy, new slippers.
However, a possible solution already exists: you need to connect the electronic assistant to the wireless network, so that it will have access to an extensive information store on the Internet. A "cloud" robot will be able to receive data directly from data centers. Moreover, this will simplify the hardware stuffing of the electronic assistant, since all important algorithmic operations will be processed in the data center. Several research groups are already working in this direction.
Cloud computing is the key to a new generation of robots. Take, for example, the Google car, which, when driving, accesses a huge database of the company with maps and images from space, comparing the information received with the data of sensors and video surveillance cameras.
Until recently, robots were considered autonomous systems with limited amounts of computing power and memory. Cloud robotics offers an alternative when robots exchange data and code over wireless networks.
That's all for today. Cloud technologies penetrate many other scientific fields, for example, chemistry, biology, genetics, geography. We plan to talk about this in the second part of this post. Subscribe to our Hubrablog so you don’t miss our new publications, friends.