links for 2010-10-06

  • Copy as RTF TextMate bundle
    Need to copy + paste some text and keep the syntax highlighting?

    Yes you do. All the time. For Keynote presentations. And probably other reasons.

    Install this bundle, and after selecting some pretty syntax highlighted text, use Ctrl+Alt+Cmd+R to copy it as RTF (rich text format) Now you can paste it directly into Keynote presentations. And other places where RTF is supported.

  • We have built Percolator, a system for incrementally processing updates to a large data set, and deployed it to create the Google web search index. By replacing a batch-based indexing system with an indexing system based on incremental processing using Percolator, we process the same number of documents per day, while reducing the average age of documents in Google search results by 50%.
  • Future many-core microprocessors are likely to be heterogeneous, by design or due to variability and defects. The latter type of heterogeneity is especially challenging due to its unpredictability. To minimize the performance and power impact of these hardware imperfections, the runtime thread scheduler and global power manager must be nimble enough to handle such random heterogeneity. With hundreds of cores expected on a single die in the future, these algorithms must provide high power-performance efficiency, yet remain scalable with low runtime overhead. This paper presents a range of scheduling and power management algorithms and performs a detailed evaluation of their effectiveness and scalability on heterogeneous many-core architectures with up to 256 cores.
  • Highly available cloud storage is often implemented with complex, multi-tiered distributed systems built on top of clusters of commodity servers and disk drives. Sophisticated management, load balancing and recovery techniques are needed to achieve high performance and availability amidst an abundance of failure sources that include software, hardware, network connectivity, and power issues. While there is a relative wealth of failure studies of individual components of storage systems, such as disk drives, relatively little has been reported so far on the overall availability behavior of large cloud-based storage services. We characterize the availability properties of cloud storage systems based on an extensive one year study of Google's main storage infrastructure and present statistical models that enable further insight into the impact of multiple design choices, such as data placement and replication strategies.

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