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Memory requirements can be a limiting factor for programs dealing with large data structures. Especially interpreted programming languages that are used to deal with large vectors like R suffer from memory overhead when copying such data structures. Avoiding data duplication directly in the application can reduce the memory requirements. Alternatively, generic kernel-level memory reduction functionality like deduplication and compression can lower the amount of memory required, but they need to compensate for missing application knowledge by utilizing more CPU time, leading to excessive overhead. To allow new optimizations based on the application's knowledge about its own memory utilization, we propose to introduce a new system call. This system call uses the existing copy-on-write functionality of the Linux kernel to avoid duplicating memory when data is copied. Our experiments using real-world …