From ALICE Documentation
Using the HPC or “supercomputer” is a little different from running programs on your desktop. When you login you’ll be connected to one of the system’s “login nodes”. These nodes serve as a staging area for you to marshal your data and submit jobs to the batch scheduler. Your job will then wait in a queue along with other researchers' jobs. Once the resources it requires become available, the batch scheduler will then run your job on a subset of our hundreds of “compute nodes”. You can see the overall structure in the diagram below.
An important point about the diagram above is that ALICE clusters are a collection of shared, finite resources. When you connect to the login nodes, you are sharing their resources (CPU cycles, memory, disk space, network bandwidth, etc.) with a few dozen other researchers. The same is true of the file servers when you access your home or project directories, and can even be true of the compute nodes.
For most day-to-day activities you should not have to worry about this, and we take precautions to limit the impact that others might have on your experience. That said, there are a few use cases that are worth watching out for:
- The login nodes should only be used for light computation; any CPU- or memory-intensive operations should be done using the batch system. A good rule of thumb is that if you wouldn't want to run a task on your desktop because it would slow down other applications, you shouldn't run it on the login nodes. (See also: Interactive Jobs.)
- I/O-intensive jobs should copy their files to fast, temporary storage, such as the local storage allocated to jobs or the Scratch parallel file system.
In general, we just encourage our users to remember that what you do may affect other researchers on the system. If you think something you want to do or try might interfere with the work of others, we highly recommend that you contact us at email@example.com (mail request).
Supercomputers become history quickly!
|Supercomputer - 1989||Smartphone - 2015||ALICE - 2019|
|Memory||128 MB||4 GB||14.4 TB|
|Storage||30 GB||64 GB||545 TB|
|Speed||2 GFLOPS||302 GFLOPS||604 TFlops|
HPC terminology glossary
A comment was made: “One of the problems we have as HPC pro's is discussing the technologies that exist or that we support in a way that's accessible to our clients and customers who may not be as well versed in those technologies as we are." We hope this glossary is helpful.
|K||kilo, 103, thousand||1KB||very small|
|M||mega, 106, million||1MB||L2 cache per core|
|G||giga, 109, million||384GB||memory per node|
|T||tera, 1012, trillion||10 TB||disk space for scratch data|
|P||peta, 1015, quadrillion||4 PB||aggregate storage|
|E||exa, 1018, quintillion||Exascale systems||current research area|