We collected file system content data from 857 desktop computers at Microsoft over a span of 4 weeks. We analyzed the data to determine the relative efficacy of data deduplication, particularly considering whole-file versus block-level elimination of redundancy. We found that whole-file deduplication achieves about three quarters of the space savings of the most aggressive block-level deduplication for storage of live file systems, and 87% of the savings for backup images. We also studied file fragmentation finding that it is not prevalent, and updated prior file system metadata studies, finding that the distribution of file sizes continues to skew toward very large unstructured files.

As hardware parallelism continues to increase, CPU caches can no longer be considered as a transparent, hardware-level performance optimization. Cache impact on performance, in particular in the face of false sharing, is completely dependent on the software that is executing. To effectively support parallel workloads on cache coherent hardware, the operating system must begin to treat the CPU cache like other shared hardware resources, and manage it appropriately.We demonstrate a prototype example of such support by describing Plastic 1 , a software-based system that detects, diagnoses, and transparently repairs false sharing as it occurs in running applications. Plastic solves two challenging problems. First, it is capable of rapid, low-overhead detection and diagnosis of false sharing in unmodified, running applications. Second, it resolves identified instances of false sharing by providing a sub-page granularity memory remapping facility within the system. Our implementation is capable of identifying and repairing pathological false sharing in under one second of execution and achieves speedups of 3-6x on known examples of false sharing in parallel benchmarks.

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