SSD-based (Solid State Disk) cache management method and system

Abstract

The invention discloses an SSD-based (Solid State Disk) cache management method and system. The SSD-based cache management method comprises the following steps: step 1, sending a read-write request, checking whether a cached DRAM (Dynamic Random Access Memory) hits data, searching a hash list, judging whether the data is existent, reading the data from the cached DRAM and returning the request if the data is existent, and reading data to the cached DRAM from a HDD (Hard Disk Drive) and carrying out step 2 if the data is nonexistent in the cached DRAM; step 2, carrying out data screening by using a two-level LRU (least recently used) linked list and a Ghost buffer, and identifying data heat; and step 3, carrying out self-adaptive change calculation on the length of the two-level LRU linked list, acquiring the granularity of a page cluster when the second-level LRU linked list of the cached DRAM is full, taking C pages behind the second-level LRU end as a whole body to replace the cached DRAM, and writing the C pages into an SSD in a large granularity, wherein the page cluster size is C pages, and C is an integral multiple of Block page number in the SSD.

Description

technical field [0001] The present invention relates to a cache storage structure and strategy, in particular to an SSD-based cache management method and system. Background technique [0002] With the progress of contemporary society, more and more data information needs to be processed, and the amount of data is growing explosively. This brings many problems to traditional storage systems. Traditional storage systems generally consist of memory (DRAM) and hard disks (HDD). DRAM acts as a cache for HDD. Such a system faces the following challenges: [0003] First, the total amount of data is increasing rapidly. The joint report of IDC and EMC pointed out that the data in today's society is growing explosively. From their report, it can be seen that the amount of data before and after 2005 was only tens of exabytes (1EB=10 18 Bytes), thousands of EB in 2010, is expected to reach nearly 8000EB by 2015, which is 8ZB (1ZB=10 21 Byte) data volume. Faced with such a data scale...

AI Technical Summary

Problems solved by technology

[0016] In order to solve the above-mentioned problems, aiming at the performance characteristics of SSD, the purpose of the present invention is to solve the problem of excessive small-grained random writing and serious cache pollution in the SSD of the prior art, and proposes a new cache architecture, which is composed of DRAM and SSD. A system in which DRAM is the first-level cache and SSD is the second-level cache

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