这个问题有点模糊,与多个方面,但我会尽力而为。计算资源- - -一些大学有自己的集群或超级计算机。但许多国家也有地区或国家设施。例如,[ARCHER2][1]是最新的迭代的英国国家超级计算机服务。少量的计算时间是英国学者免费,但对于大型项目,他们必须竞标。这是罕见的模拟要求的阿切尔的规模或ARCHER2;通常取决于正在运行的模型,一个部门或机构系统的几个节点可能是足够的,特别是如果一个并不匆忙。建筑规范对不同系统- - - - - -只要精心编写的代码,这并不像听起来那么难。FORTRAN标准化相当不错(尽管有些代码需要使用一个特定的编译器),和MPI——太——尽管其不同的实现。和大多数现代超级计算机是大规模并行机器的实际计算节点标准x64服务器,使用cpu(如英特尔工作站。 So you can do a lot of development on a desktop PC before you try to build it somewhere big and expensive. The biggest differences between different systems tend to lie in the interconnectors (the high-speed, low-latency networking between nodes), but usually the system admins will have optimised an MPI installation for that system and made it available to users, so all the details of inter-process and inter-node communications are abstracted. Making changes or improvements ---- As you've identified, for most people the key is to improve one small aspect at a time, such as a particular parametrisation. Once somebody has the standard code working, then if it is well written in a maintainable manner (not a given in the scientific world) then it is relatively straightforward for them to modify one aspect and test it. The hardest thing often is obtaining measurements or other data against which to validate the new version. [1]: https://www.archer2.ac.uk/