Virtual memory compression: Difference between revisions

Revision as of 17:36, 16 November 2023

Revision as of 16:48, 29 December 2023

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Virtual memory compression is distinct from [[garbage collection (computer science)|garbage collection]] (GC) systems, which remove unused memory blocks and in some cases consolidate used memory regions, reducing fragmentation and improving efficiency. Virtual memory compression is also distinct from [[context switching]] systems, such as [[Connectix]]'s [[RAM Doubler]] (though it also did online compression) and Apple OS 7.1, in which inactive processes are suspended and then compressed as a whole.<ref name="CWORLD-RD2"/>

==Types==

There are two general types of virtual memory compression : (1) sending compressed pages to a swap file in main memory, possibly with a backing store in auxiliary storage<ref name ="CaseForCompressedCaching"/><ref name="zram_kernel_org">{{cite web |url="https://www.kernel.org/doc/html/next/admin-guide/blockdev/zram.html" |title="zram: Compressed RAM-based block devices" |last="Gupta" |first="Nitin" |website="docs.kernel.org" |publisher="The kernel development community" |access-date=2023-12-29 }}</ref><ref name="zswap_kernel_org">{{cite web |url="https://www.kernel.org/doc/html/v4.18/vm/zswap.html" |title="zswap" |website="https://www.kernel.org/doc/html/v4.18/vm/zswap.html" |publisher="The kernel development community" |access-date=2023-12-29 }}</ref>, and (2) storing compressed pages side-by-side with uncompressed pages.<ref name="CaseForCompressedCaching"/>

The first type (1) usually uses some sort of [[LZ77_and_LZ78|LZ]] class dictionary compression algorithm combined with [[Entropy_coding|entropy coding]], such as [[Lempel–Ziv–Oberhumer|LZO]] or [[LZ4_(compression_algorithm)|LZ4]] <ref name="zswap_kernel_org /><ref name="zram_kernel_org" />, to compress the pages being swapped out. Once compressed, they are either stored in a swap file in main memory, or written to auxiliary storage, such as a hard disk.<ref name="zswap_kernel_org" /><ref name="zram_kernel_org" /> A two stage process can be used instead wherein there exists both a backing store in auxiliary storage and a swap file in main memory and pages that are evicted from the in-memory swap file are written to the backing store with a greatly decreased bandwidth need due to the compression. This last scheme leverages the benefits of both previous methods : fast in-memory data access with a great increase in the total amount of data that can be swapped out.<ref name="zswap_kernel_org" /><ref name="zram_kernel_org" /><ref name ="CaseForCompressedCaching"/>

One of the most used class of algorithms for the second type (2), the WK class of compression algorithms, takes advantage of in-memory data regularities present in pointers and integers.<ref name ="CaseForCompressedCaching"/> Specifically, in target code generated by most high-level programming languages, both integers and pointers are often present in records whose elements are word-aligned. Furthermore, the values stored in integers are usually small. Also pointers tend to point to nearby locations. Additionally, common data patterns such as a word of all zeroes can be encoded in the compressed output by a very small code. Using these data regularities, the WK class of algorithms use a very small dictionary ( 16 entries in the case of [[WKdm]] ) to achieve up to a 50% compression ratio while achieving much greater speeds and having less overhead than LZ class dictionary compression schemes.<ref name ="CaseForCompressedCaching"/>

==Benefits==