Whose Cache Line Is It Anyway?

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, 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.