Large memory HPC infrastructure to underpin world-class biological research

现代生物学研究几乎在每个阶段都使用计算机。随着我们用来生成数据的工具的改进，要分析的数据量也大大增加，因此我们需要越来越大、越来越强大的计算机，以便能够理解我们现有的数据。对于一些项目，数据的增加只是大小的问题，这个问题可以通过将数据分解成块并在单独的处理器上分析每个块来解决。然而，对于其他项目，我们需要执行的分析要求我们在所有数据点之间进行比较，这意味着我们不能很容易地将问题分开。虽然有一些聪明的（但复杂的）方法可以在不同的处理器之间移动数据，以尝试解决这些特定的问题，但它们不能很好地扩展，这可能意味着使用“标准的”高性能计算设备根本无法进行某些分析。这些项目需要访问专门的计算机系统，这些系统允许大量处理器同时共享同一大块内存。我们的目标是提供对这些专门计算机系统之一的访问。拥有这样的系统将允许bbsrc资助的爱丁堡研究人员(a)更有效、更深入地分析现有数据集，(b)设计实验并分析数据集，否则这些数据集是不实际的，甚至是不可能的，(c)获得使用灵活配置的超级计算机系统的实际经验，从而使他们能够理解和测试他们的分析的哪些部分可能从运行这个系统中受益。或者另一种配置的超级计算机系统，例如，每单位可用内存具有更多数量的处理器。

Modern biological research uses computers at nearly every stage. As the instruments that we use to generate the data improve, the amount of data to be analysed has increased greatly, such that we need increasingly bigger and more powerful computers in order to be able to make sense of the data that we have available.For some projects, the increase in the data is simply a question of size and the problem can be addressed by breaking the data up into blocks and analysing each block on a separate processor. However, for other projects, the analyses that we need to perform require us to do comparisons across and between all the data points meaning that we can't split the problem up quite so easily. Whilst there are clever (but complicated) ways of moving data around between different processors to try to address these particular problems, they do not scale well, and this can mean that some analyses are simply not possible using "standard" high-performance computing equipment. These projects need access to specialised computer systems that allow large numbers of processors to share the same large block of memory at the same time. Our aim is to provide access to one of these specialised computer systems.Having access to such a system will allow BBSRC-funded researchers at Edinburgh to (a) analyse existing data sets more efficiently and to a greater depth, (b) design experiments and analyse data sets that would not otherwise be practical or even possible and (c) get hands-on experience of using a flexibly configured super-computer system and therefore allow them to understand and test which parts of their analyses might benefit from running on this, or an alternatively configured super-computer system e.g. one with a greater number of processors per unit of available memory.