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    • 7. 发明授权
    • Migrating program objects in a multi-node computer system
    • 在多节点计算机系统中迁移程序对象
    • US08364908B2
    • 2013-01-29
    • US12110409
    • 2008-04-28
    • Eric L. BarsnessDavid L. DarringtonAmanda PetersJohn M. Santosuosso
    • Eric L. BarsnessDavid L. DarringtonAmanda PetersJohn M. Santosuosso
    • G06F12/16
    • G06F9/5022
    • Embodiments of the invention enable application programs running across multiple compute nodes of a highly-parallel system to selectively migrate objects from one node to another. For example, when an object becomes too large, a node containing the object may migrate the object to another node, thereby freeing memory space. Whether a large object is migrated can be dependent on how frequently the object is used by the application. Because the memory used by such an object is freed for other uses by the application, overall application performance may be improved. On large parallel systems with thousands of compute nodes, even relatively small improvements in application performance an individual compute node may be magnified many times, resulting in dramatic improvements in overall application performance.
    • 本发明的实施例使得能够跨高度并行系统的多个计算节点运行的应用程序选择性地将对象从一个节点迁移到另一个节点。 例如,当对象变得太大时,包含对象的节点可能会将对象迁移到另一个节点,从而释放内存空间。 是否迁移大对象可以取决于应用程序使用对象的频率。 因为这样一个对象使用的内存被应用程序的其他用途所释放,所以整体应用程序的性能可能会得到改善。 在具有数千个计算节点的大型并行系统上,即使相对较小的应用程序性能改进,单个计算节点可能会被放大多次,从而在整体应用程序性能方面有显着改进。
    • 9. 发明授权
    • Sharing compiler optimizations in a multi-node system
    • 在多节点系统中共享编译器优化
    • US08214814B2
    • 2012-07-03
    • US12144763
    • 2008-06-24
    • Eric L. BarsnessDavid L. DarringtonAmanda PetersJohn Matthew Santosuosso
    • Eric L. BarsnessDavid L. DarringtonAmanda PetersJohn Matthew Santosuosso
    • G06F9/45
    • G06F8/443
    • Embodiments of the invention enable application programs running across multiple compute nodes of a highly-parallel system to compile source code into native instructions, and subsequently share the optimizations used to compile the source code with other nodes. For example, determining what optimizations to use may consume significant processing power and memory on a node. In cases where multiple nodes exhibit similar characteristics, it is possible that these nodes may use the same set of optimizations when compiling similar pieces of code. Therefore, when one node compiles source code into native instructions, it may share the optimizations used with other similar nodes, thereby removing the burden for the other nodes to figure out which optimizations to use. Thus, while one node may suffer a performance hit for determining the necessary optimizations, other nodes may be saved from this burden by simply using the optimizations provided to them.
    • 本发明的实施例使得能够跨高度并行系统的多个计算节点运行的应用程序将源代码编译成本机指令,并且随后共享用于与其他节点编译源代码的优化。 例如,确定要使用哪些优化可能会消耗节点上显着的处理能力和内存。 在多个节点呈现类似特征的情况下,编译相似的代码段时,这些节点可能会使用相同的优化集合。 因此,当一个节点将源代码编译为本地指令时,它可以共享与其他类似节点一起使用的优化,从而消除其他节点的负担,以确定要使用的优化。 因此,虽然一个节点可能遭受用于确定必要的优化的性能命中,但是可以通过简单地使用提供给它们的优化来从其负担中节省其他节点。