GPUs are becoming common
GPU chips may be common in the video cards on your desktop, but cloud machines aren’t desktops. They don’t have USB ports, CD/DVD drives, or video cards because they only communicate to the world via the network. They don’t need to run games or even display streaming video.
This isn’t an issue for anyone who’s running a standard Web server that only concatenates strings, but it is a problem if you want to do the heavy-duty parallel computation for which GPUs are ideal. Now that more and more scientists and others are discovering the power of running parallel algorithms on GPUs, more and more are asking for GPUs in their cloud machines.
You won’t find them as an option with a standard instance, but IBM’s SoftLayer will install one in its bare-metal servers. It’s not as simple as spinning up an instance in seconds, but you can have the power of a GPU in the same box as a CPU. Amazon also has two types of machine that come with GPUs ready to run.
The early cloud machines came with a meter, and at the end of the month you got a bill. If you wanted more details, you had to log into your machine and install your own analytics package. Today, it’s easier to get data about how your machine is running.
Google’s dashboard offers live graphics that plot the load on your machines. Microsoft's dashboard includes maps and graphs for monitoring the performance of your systems. Then there are enhanced services from a handful of companies such as LogicMonitor or NewRelic. They offer even data and graphs because they specialize in analytics. The major clouds now have a number of satellite companies orbiting around them for you to get a better sense of what your cloud machines are weathering, to mix a few celestial metaphors.
So many choices
One of the biggest challenges is choosing a machine. You might think it would be easy because they all run Linux or Windows, but it’s getting harder than ever. Amazon has about nine different types of machines, each of which can have different configurations of RAM. And that’s only the current generation. If you want to stick with older machines, Amazon has at least nine of those too.
The same is true for the other companies. Rackspace has newer machines that are optimized for intense computation, fast I/O, or large memory. You’ll want to stick your databases on the I/O-optimized instances because they keep reading and writing from the disk. Large data sets like search indices need as much memory as you can afford. There are many decisions to make, and there promise to be more.
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