The need for speed
Now that we've covered all of the developments in supercomputing over the last five decades, it's probably time to mention why we even needed to build supercomputers in the first place. Put simply, we need them to perform calculations that are beyond our capabilities. The first computers were developed during World War II to execute complex code-breaking calculations that would have taken any human being an incredibly long time to perform.
This has remained the core function of supercomputers: performing complex and usually repetitive algorithms on huge data sets. Supercomputers have found a home in weather centres worldwide, and although their predictions might not always be as accurate as we might like, they do a far better job than we would be able to do without them!
They're also key in more general climate research: without supercomputers, we would probably not have known about global warming. NEC's Earth Simulator was created for precisely this purpose. The amount of data that needs to be processed when considering this global phenomenon is enormous.
Likewise, military problems also often require supercomputers. The current fastest supercomputer in the world – an IBM BlueGene/L, nicknamed Roadrunner, and installed at the Lawrence Livermore National Laboratory in California – works for the US military. Most of its workload is classified, but it is known that much of it involves work on nuclear weapons.
Physics simulation in general is another important application. The ASCI Red was primarily created to provide the level of processing power required for 'full physics' numerical modelling, where all of the data and physical equations of a system can be used in full.
Other scientific applications include chemical and biological molecular analysis, with the latter the particular focus of the Folding@Home project, which turns everyday Internet-connected computers into a supercomputer distributed around the globe. Semiconductor design now also requires the use of supercomputers, so the systems are in effect designing their own future.
In order to benefit from supercomputing, problems must contain a considerable amount of parallelism. If a problem can't be split up in this way, it will be a waste to run it on this kind of exotic hardware.
Fortunately, some tasks lend themselves naturally to parallelism. These tasks are nicknamed 'embarrassingly parallel', and examples include graphics rendering where each pixel can be calculated separately and brute-force code cracking.
Speed limits
Big computers have big problems, however. Thanks to the laws of physics, there is a limit on how fast data can travel: nothing can go faster than light.
For a spread-out system, data will take a fairly large amount of time to move from one processing subsystem to another, placing a ceiling over how fast calculations can occur. The continuing reduction in the size of transistors helps to pack more of them into the same space, so the distances between them will become smaller.
But since supercomputers are now made up of clusters of multiprocessor computers, the communications paths between all the different elements have become the most significant bottleneck. Although the processors in today's supercomputers aren't far off what you find in a desktop, the networking fabric connecting them together remains highly specialised.
A key difference between AMD's Opteron processors, which are aimed at high-performance computing (HPC) usage, and its Athlon 64s (which are aimed at the desktop) is the number of HyperTransport buses available. These buses allow the processors in a node to collaborate more quickly. Intel's Quick Path Interconnect will perform a similar function when Core i7's higher-end Xeon siblings appear in early 2009.
Then there's the need to network nodes together as fast as possible to make the cluster. This requirement has led to the development of HPC-specific networking technologies. Sun used the Scalable Coherent Interface – which is capable of 20Gbps – for many of its supercomputers in the late 1990s, and saw its share of the TOP500 list grow rapidly as a consequence.
