大小为2^24的Hashtable抛出内存不足异常,尝试用Shanks BSGS解决离散日志

发布于 2024-12-05 14:19:39 字数 936 浏览 0 评论 0原文

我正在尝试求解离散 log 2^x = r (mod m)。 其中米,2^47

所以我创建了一个大小为 2^24 的哈希表,并用它来存储整数键和 BigInteger 值。

这是我的代码:

using System;
    using System.Collections.Generic;
    using System.Collections;
    using System.Linq;
    using System.Text;
    using System.Numerics;

    namespace Shanks_BSGS_Algorithm
    {
        class Program
        {
            static int Main()
            {
                BigInteger g = 2,temp = 2,n = (Math.Sqrt(281474976710656));
                Hashtable b = new Hashtable(n);
                int i=0;
                b.Add(0, 1);
                i++;
                for (i = 1; (BigInteger)i < n ; i++)
                {
                    temp *= g;
                    b.Add(i,temp);
                }

                return 0;
            }
        }
    }

如果它有所作为的话。我正在一台拥有 1.5 GB RAM 和 32 位 Windows 7 的 6 年旧笔记本电脑上的 Visual C# 2010 Express 上运行此程序。 提前致谢。

I am trying to solve a discrete log 2^x = r (mod m).
where m, 2^47

So i created a hashtable of size 2^24 and using it to store an integer key and a BigInteger value.

Here is my code:

using System;
    using System.Collections.Generic;
    using System.Collections;
    using System.Linq;
    using System.Text;
    using System.Numerics;

    namespace Shanks_BSGS_Algorithm
    {
        class Program
        {
            static int Main()
            {
                BigInteger g = 2,temp = 2,n = (Math.Sqrt(281474976710656));
                Hashtable b = new Hashtable(n);
                int i=0;
                b.Add(0, 1);
                i++;
                for (i = 1; (BigInteger)i < n ; i++)
                {
                    temp *= g;
                    b.Add(i,temp);
                }

                return 0;
            }
        }
    }

Also if it makes a difference. I am running this on Visual C# 2010 Express on a 6yr old laptop with 1.5 gb RAM and 32-bit Windows 7.
Thanks in advance.

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评论(2

奶气 2024-12-12 14:19:39

temp 变得非常大(高达 16777216 位)。所以你的哈希集包含 1600 万个非常长的 BigIntegers。也许你想减少 temp mod m,但是当 g = 2 并且 m 是 2 的幂时,当然这最终会变成 0。所以目前还不清楚你想要做什么。

temp becomes very big (up to 16777216 bit). So your hashset contains 16 million very long BigIntegers. Maybe you want to reduce temp mod m, but of course this will eventually become 0 when g = 2 and m is a power of 2. So it's not really clear what you want to do.

依 靠 2024-12-12 14:19:39

首先,我认为您需要使用 temp 值作为数据的关键:

// this makes more sense, otherwise you
// could simply have an array of BigIntegers
b.Add(temp,i);

关于内存问题,.NET 不允许任何进程使用超过 2Gb 的内存,并且允许如果您需要连续的块,则更少。由于您在处理过程中要处理非常大的数字,因此内存不足是不可避免的。

一种解决方案(如果您只需要最终结果,则首选)是使用不同的算法(Pollard's rho算法),其空间效率更高,并且具有相似的运行时间。

如果您确实想测试 BSGS 算法,您可能需要使用基于磁盘的哈希表。我不知道 .NET 的任何实现,但您可能会发现几个 C++ 项目,看看是否可以轻松移植它们 (例如,胸径)。

如果您找不到这样的哈希表,比移植更简单的解决方案(好吧,取决于您的数据库技能)可能是使用您熟悉的关系数据库,使用可以允许足够大的整数的模式。您可以尝试使用 SQLite,随着它的增长,它变慢,但我相信速度对您来说并不那么重要。具有适当索引的 SQL Server 可能会工作得很好。

First of all, I think you need to use the temp value as the key to your data:

// this makes more sense, otherwise you
// could simply have an array of BigIntegers
b.Add(temp,i);

Regarding the memory issue, .NET doesn't allow any process to use more than 2Gb of memory, and allows even less if you need a contiguous block. Since you are dealing with very large numbers as you go along, running out of memory is inevitable.

One solution (preferred, if you only need the end result) would be to use a different algorithm (Pollard's rho algorithm), which is much more space efficient, and has a similar running time.

If you really want to test the BSGS algorithm, you will probably need to go for a disk-based hashtable. I am not aware of any implementations for .NET, but you might find several C++ projects around and see if you can port them easily (DBH, for instance).

If you cannot find such a hashtable, a simpler solution than porting (well, depending on your DB skills) might be to use a relational database you are comfortable with, using a schema that can allow sufficiently large integers. You could try with SQLite, it will get slower as it grows, but I believe speed is not that important to you. SQL Server with some proper indexing might work well.

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