Slashdot Mirror
High-Performance Linux Clustering
An anonymous reader writes "High Performance Computing (HPC) has become easier, and two reasons are the adoption of open source software concepts and the introduction and refinement of clustering technology. This first of two articles discusses the types of clusters available, uses for those clusters, reasons clusters have become popular for HPC, some fundamentals of HPC, and the role of Linux in HPC."
We spent $849,000 on an Itanium cluster and have recently found ourselves SOL since it's a dying architecture.
You can't even run Java on them.
If you "get" pointers add me as a friend (116)!
For some very good information on F/OSS based clustering, check out aggregate.org. They have really neat ideas, that are reasonably well doccumented and freely implementable/usable. I built a little cluster (AFAPI on a WAPERS switch) with them for my highschool senior project, and it was a great experence.
Though mpp's are kind of like clusters, and the boundary between the two is vague, I think there's definately a distinction. In many MPPs, nodes share access to memory, just at a performance penalty. Often the scientific binary is written using a message-passing tool like MPI, but the OS is often run with direct memory access. Definately from a systems-administration point of view, an mpp is different from a cluster. In an MPP you don't have 4000 root hard drives and 4000 power supplies to replace when they break. An mpp may be like a (fast) cluster from the programmer's point of view, but they are a lot simpler to deploy and manage. (Blue Gene, xt3, altix)
I also contest some of the distinctions drawn about vector processor systems. The two vector systems currently on the market, the cray X1 and the NEC SX-8 are clusters. Each node just happens to be a vector-smp. The earth simulator is a 640 node cluster of 8-way SMP boxes, where each of the processors in the smp is a vector cpu. However, the predominant programming method even on these boxes is with explicite message passing like MPI. Co-array fortran and Unified Parallel C are faster, but slow to catch on.
Good summary of the common case though.