Staged Performance Optimisation Components (SPOCS)

为了从各种科学和工程软件应用中获得良好的性能，软件优化是必要的。这一点最近变得越来越重要，因为长期以来快速提高原始处理器速度的趋势已经结束。未来的高性能计算机将以多样性和多核并行性为特征，这意味着芯片在一个封装中包含多个处理器。让软件有效地利用这些架构将需要越来越复杂的优化技术。本提案旨在解决优化高性能软件中的一个特定问题：给定N段代码（组件）和M个可能适用的优化，我们能否以一种更智能的方式管理最终的优化决策，而不是为N个组件中的每一个组件配备信息（元数据），以确定M个优化中的每一个是否可以应用以及可能获得多少。这很重要，因为只有当我们能够解开组件和优化的交叉乘积时，我们才能希望有效地优化。我们面临的挑战是在不重写现有优化的情况下添加新组件，以及在不添加所有现有组件元数据的情况下添加新优化。

Software optimisation is necessary in order to achieve good performance from various science and engineering software applications. This has recently become increasingly important because the long-standing trend for rapid advances in raw processor speed has come to an end. Future high-performance computers will be characterised by diversity and multi-core parallelism, meaning chips that contain in one package multiple processors. Getting software to make effective use of such architectures will require increasingly sophisticated optimisation techniques. This proposal seeks to address a specific problem in optimising high-performance software: Given N pieces of code (components) and M possible optimisations that might be applicable, can we manage the resulting optimisation decisions in a smarter way than equipping every one of the N components with information (metadata) that determines whether each of the M optimisations can be applied and how much it is likely to gain. This is important because it is only if we can unweave this cross-product of components and optimisations that we can hope to optimise effectively. The challenge is to make it possible to add new components without having to re-write our existing optimisations, and to add new optimisations without having to add to the metadata for all exsiting components.