Sly Media Networks LLC

What is a Cluster

sly — Sun, 08 Jan 2012 02:41:27 +0000

It seems these days more and more research environments are taking advantage of using a cluster of computers for running parallel programs on them. So what is a cluster? In the computing world there are two types of clustering. One type is for high redundancy and fail-over for usually one high profile computer. In this scenario, let’s say it’s a web server, there would be multiple computers all synchronized together into a cluster so that if any one of the computers died another one would take it’s place. This is what I thought clustering was when I was in the private sector. When I got into academics is when I realized the other cluster use. The second type of cluster is where you just put lots of computers together and use them all at the same time (in parallel) to compute some type of large data set or algorithm. It’s what I focus on mostly these days and the topic of this discussion.

The main idea here is let’s say for example, you run a program that takes one month to run on one processor. This could be your own personal desktop even. Many times, the program computes some calculation over and over again while changing a variable each iteration. A good example is “over time”. So the same calculation, but time changes in it.

Let’s say that if we wrote the program so that it could send one calculation to one cpu and another calculation (with time incremented) to another cpu we theoretically could cut our time in half to solve the same problem. So running it on 1 cpu takes a month, 2 cpu’s takes 15 days, 4 cpu’s takes a week, and so on. You can see that for certain problems you can vastly increase the turn around time to analyze results.

Now, mind you, this is just the basic idea and there are a lot of issues related to this and in many cases there is a limit to how much performance you can get. Meaning that at some point the time to calculate the problem slows down when you have too many resources. The overhead to manage the communication between hosts takes over and essentially takes longer to process and collect all the output data.

If this is a little technical don’t worry… the main idea is that there are many benefits for using lots of computing resources to solve problems.

Two Types of Compute Clusters

sly — Sun, 08 Jan 2012 02:39:02 +0000

Traditionally in the computational world there were two types of compute cluster configurations. One type is called “Shared Memory” and the other is called a “Beowulf”. With the Shared Memory systems it was boxes of computers plugged together with a very high speed interconnect. The connect made it so that all the pieces connected together appears as just one computer. Just like your computer at home. The advantage of a shared memory system is that usually you could have a lot of memory (RAM) installed in the machine. Load these systems up with a large disk for temporary space and it could really crunch some data sets. With the advent of “cores” lately and the ability to buy memory relatively cheaply (compared to just a few short years ago) many home computers now coming with multiple “cores” are essentially a type of “Shared memory” system. Shared memory systems are great for problems that have large GB sized data sets that need to all be loaded into memory at once to analyze it.

The other type of cluster is a Beowulf cluster. This is where you take multiple computers and hook them together so that they can perform parts of the parallel applications. Each computer generally doesn’t have a lot of resources compared to a single shared memory system but collectively a Beowulf can compete with these numbers. Beowulf’s are best suited for problems where they need lots of CPU time but not a lot of memory or disk storage. So in this scenario just having lots of computers available to run some part of a program is the benefit. A good example of a beowulf cluster is the Seti @ Home or Folding @ Home Projects. Here you can download a screensaver that allows them to use your idle computer to run parts of their very large sets of data that they need to crunch.

Welcome

sly — Sat, 16 Jul 2011 02:48:43 +0000

Welcome to my Blog and Website. I plan to write up some posts on different technical topics. Mostly related to my experiences with Computational Computing and Unix System Administration.

You won’t find anything related to Windows or Microsoft related products here. I only utilize open source (usually free) software solutions. Besides the hardware costs there is not software maintenance agreements to manage with any solutions we develop. Yearly software maintenance contracts for commercial products can be expensive. With so many free and very well developed software applications out there it doesn’t make any sense to look at commercial (paid) products unless there isn’t anything besides that that can meet your needs.

Stay tuned for my next post …….