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Initially, zram had only the latter function, hence the original name "compcache" ("compressed cache"). Unlike swap, zram only uses 0.1% of the maximum size of the disk when not in use. [1] After four years in the Linux kernel's driver staging area, zram was introduced into the mainline Linux kernel in version 3.14, released on March 30, 2014. [2]
Cache hierarchy, or multi-level cache, is a memory architecture that uses a hierarchy of memory stores based on varying access speeds to cache data. Highly requested data is cached in high-speed access memory stores, allowing swifter access by central processing unit (CPU) cores.
Pages in the page cache modified after being brought in are called dirty pages. [5] Since non-dirty pages in the page cache have identical copies in secondary storage (e.g. hard disk drive or solid-state drive), discarding and reusing their space is much quicker than paging out application memory, and is often preferred over flushing the dirty pages into secondary storage and reusing their space.
The page cache in main memory, which is an example of disk cache, is managed by the operating system kernel. While the disk buffer , which is an integrated part of the hard disk drive or solid state drive, is sometimes misleadingly referred to as "disk cache", its main functions are write sequencing and read prefetching.
A system with a smaller page size uses more pages, requiring a page table that occupies more space. For example, if a 2 32 virtual address space is mapped to 4 KiB (2 12 bytes) pages, the number of virtual pages is 2 20 = (2 32 / 2 12). However, if the page size is increased to 32 KiB (2 15 bytes), only 2 17 pages are required. A multi-level ...
The memory mapping process is handled by the virtual memory manager, which is the same subsystem responsible for dealing with the page file. Memory mapped files are loaded into memory one entire page at a time. The page size is selected by the operating system for maximum performance. Since page file management is one of the most critical ...
A cache has two primary figures of merit: latency and hit ratio. A number of secondary factors also affect cache performance. [1] The hit ratio of a cache describes how often a searched-for item is found. More efficient replacement policies track more usage information to improve the hit rate for a given cache size.
Unlike the case of exclusive cache, where the unique memory capacity is the combined capacity of all caches in the hierarchy. [4] If the size of lower level cache is small and comparable with the size of higher level cache, there is more wasted cache capacity in inclusive caches.