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Performance Q & A by Adrian Cockcroft

Increase system performance by maximizing your cache

You can't get the best results if you use the wrong cache. We explain how each works and when to do it

SunWorld
February  1997
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Abstract
Accessing a file on disk or over a network is hundreds of times slower than reading a cached copy from memory. Many types of cache exist to speed up file accesses. Changing your workload to make it more "cache friendly" can result in very significant performance benefits. (3,100 words)


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Q: I know that files are cached in memory and there is also a cache filesystem option. How can I tell if the caches are working well and how big they should be? Also, how can I tune applications together with the caches?
--Tasha in Cashmere (again)

A: Computer system hardware and software are built by using many types of cache. The system designers optimize these caches to work well with typical workload mixes and tune them using in-house and industry standard benchmarks. If you are writing an application or deciding how to deploy an existing suite of applications on a network of systems, you need to know what caches exist and how to work with them to get good performance.

Cache principles revisited
Here's a recap to the principles of caching we covered in last month's article. Caches work on two basic principles that should be quite familiar to you from everyday life experiences. The first is that if you spend a long time getting something that you think you may need again soon, you keep it nearby. The contents of your cache make up your working set. The second principle is that when you get something, you can save time by also getting the extra items you suspect you'll need in the near future.

The first principle is called "temporal locality" and involves reusing the same things over time. The second principle is called "spacial locality" and depends on the simultaneous use of things that are located near each other. Caches only work well if there is good locality in what you are doing. Some sequences of behavior work very efficiently with a cache, and others make little or no use of the cache. In some cases, cache-busting behavior can be fixed by changing the system to provide support for special operations. In most cases, avoiding cache-busting behavior in the workload's access pattern will lead to a dramatic improvement in performance.

A cache works well if there are a lot more reads than writes, and if the reads or writes of the same or nearby data occur close together in time. An efficient cache has a low reference rate (it doesn't make unnecessary lookups), a very short cache hit time, a high hit ratio, the minimum possible cache miss time, and an efficient way of handling writes and purges.


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File access caching with local disks
We'll start by looking at the simplest configuration, the open, fstat, read, write, and mmap operations on a local disk with the default Unix File System (UFS).

chart gif

There are a lot of interrelated caches. They are system-wide caches shared by all users and all processes. The activity of one cache-busting process can mess up the caching of other well-behaved processes. Conversely, a group of cache-friendly processes working on similar data at similar times help each other by pre-filling the caches for each other. The diagram shows the main data flows and relationships.

That's all for this month. I've gone on too long, and I've only covered the basic operations involved in caching UFS to local disk. I'll continue this topic next month and show how NFS and CacheFS fit into the overall scheme of things from a caching point of view.


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About the author
Adrian Cockcroft joined Sun in 1988, and currently works as a performance specialist for the Server Division of SMCC. He wrote Sun Performance and Tuning: SPARC and Solaris, published by SunSoft Press PTR Prentice Hall. Reach Adrian at adrian.cockcroft@sunworld.com.

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