Case Study: Clusters and Image Processing, Part I
The Savings: Money and Time
Dee-Ann LeBlanc
Sunday, March 17, 2002 06:47:40 PM
People typically do not move to another operating system and architecture
once their application is already in place unless there are some large
benefits to doing so. ImageLinks made the change because of anticipated
monetary and time gains. Of course, in the corporate world, time is money!
So, these two different types of savings are interrelated.
The Money
The easiest savings to quantify is money. The major thing to consider
here is the move from SGI hardware to commodity hardware (PCs). The
trickle-down effect brought about savings in almost every aspect of
the operation.
As I mentioned earlier, ImageLinks initially used SGI Indigo 2s for its
image processing. This choice required that all hardware and peripherals be
purchased through SGI to avoid warranty problems. Unfortunately, when you
cannot comparison shop for components, more often than not these components
end up being more expensive than they would for similar power and
capabilities under other computer architectures. Specifically, ImageLinks
went from spending $15,000 a month on leases for its SGI and Unix machines,
to a one-time purchase of $25,000 for all the hardware components for
its Linux setup.
When the hardware and operating system are expensive, typically the
software is too. This problem occurs for a number of reasons, including
the reality of a vertical market with few customers supporting the research
and development efforts of the software manufacturer. Such high-end software
tends to be modular, where you purchase a base package and then buy modules
for different functionality. Software, modules, and licenses were running
ImageLinks over $75,000 per year. Though the company created its own tools,
it still required the development environment, compilers, and other
components in order to build and maintain the code.
Moving to Linux allowed ImageLinks to take advantage of freely available
Open Source tools for its development environment. Its software budget for
2000 was around $10,000, with no sacrifice in functionality or quality.
The Time
Just as significant as the upfront costs saved by the change is the
savings in time. I already detailed that the application's compilation
was reduced from 12 hours to 2 hours. There is also the issue of
image-processing jobs. These were reduced sometimes from several days of
computing time to just a few hours, in some cases.
All of ImageLinks's software development has also moved to the Linux
platform. This change has increased programming efficiency immensely. If
the development team needs the latest compiler, linker, debugger, editor,
or configuration tool, it can just turn to the Internet and download the
needed tool. The compile times, as I mentioned before, are also faster and
produce binaries approximately half the size of the SGI compilers. Smaller
programs run faster because they require less RAM, which in turn speeds up
image-processing times.
To give you a feel for the kinds of time savings the folks at ImageLinks
have experienced, they kindly provided me with the results of one of their
test runs. In this run, they perform the following tasks for a collection of
satellite images:
- Utilize the fusing component of their software to merge all the
images correctly into a single image, correcting for rotation, time of day,
and properly assembling overlaps.
- Take the resulting image and project it onto a three-dimensional
model of the earth, finding its proper resting place.
- Utilize the results of the first two stages to create a map of the
area represented by the sum of the satellite images.
The total resulting output from this operation is 1GB of data. Table 1.1
details the speeds documented under three different hardware options.
NOTE: See the section "Implementing the Beowulf Cluster" in Part 2 next week for details on the cluster mentioned in Table 1.
Table 1 Image-processing job speed comparisons.
