替代嵌套数组（6维）与内存的差距保持O（1）访问 [英] Alternative to nested array (6 dimensions) with memory gaps retaining O(1) access

问题描述

我的统计数据，从运行不同配置的程序读取。比方说，有6个配置（ A ， B ... ˚F）。该配置可能不是线性变化，所以如果你想测量值作为一个表的，有可能是在表中的空白。现在的问题是关于构建这些统计数据在内存中。

I am reading in statistical data from running a program with different configurations. Let's say there are 6 configurations (a, b, ..., f). The configurations may not change linearly, so if you think of the measurements as a table, there could be gaps in the table. The question is regarding structuring these statistical data in memory.

，想到的第一件事就是阅读这些配置动态分配的6深数组或数组：

The first thing that comes to mind is to read these configurations to a dynamically allocated 6-deep array or arrays:

struct data ******measurements;

现在这工作正常。你有很少的内存开销（只有那些将数据实际分配的配置）和访问时间 O（1）。

Now this works fine. You have very little memory overhead (only the configurations that have data will actually be allocated) and the access time is O(1).

除了这个事实，大多数人不喜欢 ****** 三分球，这有添加配置意味着添加尺寸阵列的下跌，这可能除非读取/写入到阵列封装在一个函数变得丑陋。 （写入已封装照顾分配必要的时候，所以这实际上也是没有这么大的交易）。

Besides the fact that most people don't like ****** pointers, this has the downside that adding configurations means adding dimensions to the array, which could get ugly unless read/write to the array is encapsulated in a function. (Write is already encapsulated to take care of allocation when necessary, so this in fact is not such a big deal).

我想到的另一个想法是使用地图结构配置到结构数据使用AVL树什么（我已经，以便有没有实现间接费用） 。这解决了扩展配置参数的问题，但会降低访问时间 O（日志（N））。

Another idea that comes to mind is to use a map of struct config to struct data using an AVL tree or something (which I already have so has no implementation overheads). This solves the problem of extending the configuration parameters, but decreases access time to O(log(n)).

测试的数量可以得到 0相当大（日志（N））有所作为。

The number of tests could get considerably large for the O(log(n)) to make a difference.

我的问题是：用6深嵌套数组这里是否合理？或者是有这样做的更好的办法？

推荐答案

真正的性能瓶颈（除了浪费内存）都没有计算，但间接性和高速缓存缺失的数量，你会遇到。这些可以通过百因素占主导地位，以一千指数之类的东西的计算。所以，你最好的选择是减少迂回的数量和投入进位计算。至于我可以看到这个最好由你的散列索引6来完成。这会降低你的间接为两个，第一查找存储在哈希表中的值（可能是一个指针），然后获取您的感兴趣的直接的数据。

The real performance bottleneck (besides wasting memory) are not computations but the number of indirections and cache misses that you will encounter. These can dominate by a factor of hundred to thousand the computation of indices and stuff like that. So your best choice is to reduce the number of indirections and invest a bit into computation. As far as I can see this would best be done by hashing your 6 indices. This would reduce your indirections to two, first looking up the value (probably a pointer) that is stored in the hash table, and then fetching the data that your are interested in directly.

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