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c++ - 这个自定义的 md5 哈希算法是如何实现的?

转载 作者:行者123 更新时间:2023-11-28 03:05:14 27 4
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首先,我的最终目标是在支持 cuda 的显卡上实现 md5 哈希算法。是的,我知道它已经完成了。

由于有问题的代码相当冗长,这里是一个链接(这不是我的代码): http://majuric.org/software/cudamd5/source/cudamd5-v1.2.1/cuda_md5_gpu.cu

大部分代码遵循维基百科的原型(prototype)。但是,此时开始有所不同:

static const uint rconst_cpu[16] = {
7, 12, 17, 22, 5, 9, 14, 20, 4, 11, 16, 23, 6, 10, 15, 21
};

显然,每个“分组”只需重复四次即可。继续代码,它到达了这一点:

__device__ inline uint r(const uint i) {
return rconst[(i / 16) * 4 + i % 4];
}

__device__ inline uint &getw(uint *w, const int i)
{
return w[(i+threadIdx.x) % 16];
}

__device__ inline uint getw(const uint *w, const int i) // const- version
{
return w[(i+threadIdx.x) % 16];
}


__device__ inline uint getk(const int i)
{
return k[i]; // Note: this is as fast as possible (measured)
}

__device__ void step(const uint i, const uint f, const uint g, uint &a, uint &b, uint &c, uint &d, const uint *w)
{
uint temp = d;
d = c;
c = b;
b = b + leftrotate((a + f + getk(i) + getw(w, g)), r(i));
a = temp;
}

我不确定这些函数在做什么 - 特别是 r()。 此外,w[(i+threadIdx.x) % 16]; 意思是?我知道 threadIdx.x 是 cuda 独有的,但我昨天才开始使用这种语言。

欢迎任何建设性的意见。

编辑:这是代码:

// CUDA MD5 hash calculation implementation (A: mjuric@ias.edu).
//
// A very useful link: http://people.eku.edu/styere/Encrypt/JS-MD5.html
//

#define RSA_KERNEL md5_v2

#include <stdio.h>
#include "cutil.h"

typedef unsigned int uint;

//
// On-device variable declarations
//

extern __shared__ uint memory[]; // on-chip shared memory
__constant__ uint k[64], rconst[16]; // constants (in fast on-chip constant cache)
__constant__ uint target[4]; // target hash, if searching for hash matches

//
// MD5 magic numbers. These will be loaded into on-device "constant" memory
//
static const uint k_cpu[64] = {

0xd76aa478, 0xe8c7b756, 0x242070db, 0xc1bdceee,
0xf57c0faf, 0x4787c62a, 0xa8304613, 0xfd469501,
0x698098d8, 0x8b44f7af, 0xffff5bb1, 0x895cd7be,
0x6b901122, 0xfd987193, 0xa679438e, 0x49b40821,

0xf61e2562, 0xc040b340, 0x265e5a51, 0xe9b6c7aa,
0xd62f105d, 0x2441453, 0xd8a1e681, 0xe7d3fbc8,
0x21e1cde6, 0xc33707d6, 0xf4d50d87, 0x455a14ed,
0xa9e3e905, 0xfcefa3f8, 0x676f02d9, 0x8d2a4c8a,

0xfffa3942, 0x8771f681, 0x6d9d6122, 0xfde5380c,
0xa4beea44, 0x4bdecfa9, 0xf6bb4b60, 0xbebfbc70,
0x289b7ec6, 0xeaa127fa, 0xd4ef3085, 0x4881d05,
0xd9d4d039, 0xe6db99e5, 0x1fa27cf8, 0xc4ac5665,

0xf4292244, 0x432aff97, 0xab9423a7, 0xfc93a039,
0x655b59c3, 0x8f0ccc92, 0xffeff47d, 0x85845dd1,
0x6fa87e4f, 0xfe2ce6e0, 0xa3014314, 0x4e0811a1,
0xf7537e82, 0xbd3af235, 0x2ad7d2bb, 0xeb86d391,
};

static const uint rconst_cpu[16] =
{
7, 12, 17, 22, 5, 9, 14, 20, 4, 11, 16, 23, 6, 10, 15, 21
};

void init_constants(uint *target_cpu)
{
cudaMemcpyToSymbol(k, k_cpu, sizeof(k));
cudaMemcpyToSymbol(rconst, rconst_cpu, sizeof(rconst));
if(target_cpu) { cudaMemcpyToSymbol(target, target_cpu, 4*4); };
}

//
// MD5 routines (straight from Wikipedia's MD5 pseudocode description)
//

__device__ inline uint leftrotate (uint x, uint c)
{
return (x << c) | (x >> (32-c));
}

__device__ inline uint r(const uint i)
{
return rconst[(i / 16) * 4 + i % 4];
}

// Accessor for w[16] array. Naively, this would just be w[i]; however, this
// choice leads to worst-case-scenario access pattern wrt. shared memory
// bank conflicts, as the same indices in different threads fall into the
// same bank (as the words are 16 uints long). The packing below causes the
// same indices in different threads of a warp to map to different banks. In
// testing this gave a ~40% speedup.
//
// PS: An alternative solution would be to make the w array 17 uints long
// (thus wasting a little shared memory)
//
__device__ inline uint &getw(uint *w, const int i)
{
return w[(i+threadIdx.x) % 16];
}

__device__ inline uint getw(const uint *w, const int i) // const- version
{
return w[(i+threadIdx.x) % 16];
}


__device__ inline uint getk(const int i)
{
return k[i]; // Note: this is as fast as possible (measured)
}

__device__ void step(const uint i, const uint f, const uint g, uint &a, uint &b, uint &c, uint &d, const uint *w)
{
uint temp = d;
d = c;
c = b;
b = b + leftrotate((a + f + getk(i) + getw(w, g)), r(i));
a = temp;
}

__device__ void inline md5(const uint *w, uint &a, uint &b, uint &c, uint &d)
{
const uint a0 = 0x67452301;
const uint b0 = 0xEFCDAB89;
const uint c0 = 0x98BADCFE;
const uint d0 = 0x10325476;

//Initialize hash value for this chunk:
a = a0;
b = b0;
c = c0;
d = d0;

uint f, g, i = 0;
for(; i != 16; i++)
{
f = (b & c) | ((~b) & d);
g = i;
step(i, f, g, a, b, c, d, w);
}

for(; i != 32; i++)
{
f = (d & b) | ((~d) & c);
g = (5*i + 1) % 16;
step(i, f, g, a, b, c, d, w);
}

for(; i != 48; i++)
{
f = b ^ c ^ d;
g = (3*i + 5) % 16;
step(i, f, g, a, b, c, d, w);
}

for(; i != 64; i++)
{
f = c ^ (b | (~d));
g = (7*i) % 16;
step(i, f, g, a, b, c, d, w);
}

a += a0;
b += b0;
c += c0;
d += d0;
}

//////////////////////////////////////////////////////////////////////////////
///////////// Ron Rivest's MD5 C Implementation //////////////////
//////////////////////////////////////////////////////////////////////////////

/***********************************************************************
** Copyright (C) 1990, RSA Data Security, Inc. All rights reserved. **
** **
** License to copy and use this software is granted provided that **
** it is identified as the "RSA Data Security, Inc. MD5 Message **
** Digest Algorithm" in all material mentioning or referencing this **
** software or this function. **
** **
** License is also granted to make and use derivative works **
** provided that such works are identified as "derived from the RSA **
** Data Security, Inc. MD5 Message Digest Algorithm" in all **
** material mentioning or referencing the derived work. **
** **
** RSA Data Security, Inc. makes no representations concerning **
** either the merchantability of this software or the suitability **
** of this software for any particular purpose. It is provided "as **
** is" without express or implied warranty of any kind. **
** **
** These notices must be retained in any copies of any part of this **
** documentation and/or software. **
***********************************************************************/


/* F, G and H are basic MD5 functions: selection, majority, parity */
#define F(x, y, z) (((x) & (y)) | ((~x) & (z)))
#define G(x, y, z) (((x) & (z)) | ((y) & (~z)))
#define H(x, y, z) ((x) ^ (y) ^ (z))
#define I(x, y, z) ((y) ^ ((x) | (~z)))

/* ROTATE_LEFT rotates x left n bits */
#define ROTATE_LEFT(x, n) (((x) << (n)) | ((x) >> (32-(n))))

/* FF, GG, HH, and II transformations for rounds 1, 2, 3, and 4 */
/* Rotation is separate from addition to prevent recomputation */
#define FF(a, b, c, d, x, s, ac) \
{(a) += F ((b), (c), (d)) + (x) + (uint)(ac); \
(a) = ROTATE_LEFT ((a), (s)); \
(a) += (b); \
}
#define GG(a, b, c, d, x, s, ac) \
{(a) += G ((b), (c), (d)) + (x) + (uint)(ac); \
(a) = ROTATE_LEFT ((a), (s)); \
(a) += (b); \
}
#define HH(a, b, c, d, x, s, ac) \
{(a) += H ((b), (c), (d)) + (x) + (uint)(ac); \
(a) = ROTATE_LEFT ((a), (s)); \
(a) += (b); \
}
#define II(a, b, c, d, x, s, ac) \
{(a) += I ((b), (c), (d)) + (x) + (uint)(ac); \
(a) = ROTATE_LEFT ((a), (s)); \
(a) += (b); \
}


/* Basic MD5 step. Transform buf based on in.*/
void inline __device__ md5_v2(const uint *in, uint &a, uint &b, uint &c, uint &d)
{
const uint a0 = 0x67452301;
const uint b0 = 0xEFCDAB89;
const uint c0 = 0x98BADCFE;
const uint d0 = 0x10325476;

//Initialize hash value for this chunk:
a = a0;
b = b0;
c = c0;
d = d0;

/* Round 1 */
#define S11 7
#define S12 12
#define S13 17
#define S14 22
FF ( a, b, c, d, getw(in, 0), S11, 3614090360); /* 1 */
FF ( d, a, b, c, getw(in, 1), S12, 3905402710); /* 2 */
FF ( c, d, a, b, getw(in, 2), S13, 606105819); /* 3 */
FF ( b, c, d, a, getw(in, 3), S14, 3250441966); /* 4 */
FF ( a, b, c, d, getw(in, 4), S11, 4118548399); /* 5 */
FF ( d, a, b, c, getw(in, 5), S12, 1200080426); /* 6 */
FF ( c, d, a, b, getw(in, 6), S13, 2821735955); /* 7 */
FF ( b, c, d, a, getw(in, 7), S14, 4249261313); /* 8 */
FF ( a, b, c, d, getw(in, 8), S11, 1770035416); /* 9 */
FF ( d, a, b, c, getw(in, 9), S12, 2336552879); /* 10 */
FF ( c, d, a, b, getw(in, 10), S13, 4294925233); /* 11 */
FF ( b, c, d, a, getw(in, 11), S14, 2304563134); /* 12 */
FF ( a, b, c, d, getw(in, 12), S11, 1804603682); /* 13 */
FF ( d, a, b, c, getw(in, 13), S12, 4254626195); /* 14 */
FF ( c, d, a, b, getw(in, 14), S13, 2792965006); /* 15 */
FF ( b, c, d, a, getw(in, 15), S14, 1236535329); /* 16 */

/* Round 2 */
#define S21 5
#define S22 9
#define S23 14
#define S24 20
GG ( a, b, c, d, getw(in, 1), S21, 4129170786); /* 17 */
GG ( d, a, b, c, getw(in, 6), S22, 3225465664); /* 18 */
GG ( c, d, a, b, getw(in, 11), S23, 643717713); /* 19 */
GG ( b, c, d, a, getw(in, 0), S24, 3921069994); /* 20 */
GG ( a, b, c, d, getw(in, 5), S21, 3593408605); /* 21 */
GG ( d, a, b, c, getw(in, 10), S22, 38016083); /* 22 */
GG ( c, d, a, b, getw(in, 15), S23, 3634488961); /* 23 */
GG ( b, c, d, a, getw(in, 4), S24, 3889429448); /* 24 */
GG ( a, b, c, d, getw(in, 9), S21, 568446438); /* 25 */
GG ( d, a, b, c, getw(in, 14), S22, 3275163606); /* 26 */
GG ( c, d, a, b, getw(in, 3), S23, 4107603335); /* 27 */
GG ( b, c, d, a, getw(in, 8), S24, 1163531501); /* 28 */
GG ( a, b, c, d, getw(in, 13), S21, 2850285829); /* 29 */
GG ( d, a, b, c, getw(in, 2), S22, 4243563512); /* 30 */
GG ( c, d, a, b, getw(in, 7), S23, 1735328473); /* 31 */
GG ( b, c, d, a, getw(in, 12), S24, 2368359562); /* 32 */

/* Round 3 */
#define S31 4
#define S32 11
#define S33 16
#define S34 23
HH ( a, b, c, d, getw(in, 5), S31, 4294588738); /* 33 */
HH ( d, a, b, c, getw(in, 8), S32, 2272392833); /* 34 */
HH ( c, d, a, b, getw(in, 11), S33, 1839030562); /* 35 */
HH ( b, c, d, a, getw(in, 14), S34, 4259657740); /* 36 */
HH ( a, b, c, d, getw(in, 1), S31, 2763975236); /* 37 */
HH ( d, a, b, c, getw(in, 4), S32, 1272893353); /* 38 */
HH ( c, d, a, b, getw(in, 7), S33, 4139469664); /* 39 */
HH ( b, c, d, a, getw(in, 10), S34, 3200236656); /* 40 */
HH ( a, b, c, d, getw(in, 13), S31, 681279174); /* 41 */
HH ( d, a, b, c, getw(in, 0), S32, 3936430074); /* 42 */
HH ( c, d, a, b, getw(in, 3), S33, 3572445317); /* 43 */
HH ( b, c, d, a, getw(in, 6), S34, 76029189); /* 44 */
HH ( a, b, c, d, getw(in, 9), S31, 3654602809); /* 45 */
HH ( d, a, b, c, getw(in, 12), S32, 3873151461); /* 46 */
HH ( c, d, a, b, getw(in, 15), S33, 530742520); /* 47 */
HH ( b, c, d, a, getw(in, 2), S34, 3299628645); /* 48 */

/* Round 4 */
#define S41 6
#define S42 10
#define S43 15
#define S44 21
II ( a, b, c, d, getw(in, 0), S41, 4096336452); /* 49 */
II ( d, a, b, c, getw(in, 7), S42, 1126891415); /* 50 */
II ( c, d, a, b, getw(in, 14), S43, 2878612391); /* 51 */
II ( b, c, d, a, getw(in, 5), S44, 4237533241); /* 52 */
II ( a, b, c, d, getw(in, 12), S41, 1700485571); /* 53 */
II ( d, a, b, c, getw(in, 3), S42, 2399980690); /* 54 */
II ( c, d, a, b, getw(in, 10), S43, 4293915773); /* 55 */
II ( b, c, d, a, getw(in, 1), S44, 2240044497); /* 56 */
II ( a, b, c, d, getw(in, 8), S41, 1873313359); /* 57 */
II ( d, a, b, c, getw(in, 15), S42, 4264355552); /* 58 */
II ( c, d, a, b, getw(in, 6), S43, 2734768916); /* 59 */
II ( b, c, d, a, getw(in, 13), S44, 1309151649); /* 60 */
II ( a, b, c, d, getw(in, 4), S41, 4149444226); /* 61 */
II ( d, a, b, c, getw(in, 11), S42, 3174756917); /* 62 */
II ( c, d, a, b, getw(in, 2), S43, 718787259); /* 63 */
II ( b, c, d, a, getw(in, 9), S44, 3951481745); /* 64 */

a += a0;
b += b0;
c += c0;
d += d0;

}

//////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////

// The kernel (this is the entrypoint of GPU code)
// Loads the 64-byte word to be hashed from global to shared memory
// and calls the calculation routine
__global__ void md5_calc(uint *gwords, uint *hash, int realthreads)
{
int linidx = (gridDim.x*blockIdx.y + blockIdx.x)*blockDim.x + threadIdx; //assuming blockDim.y = 1 and threadIdx.y = 0, always
if(linidx >= realthreads) { return; } // this check slows down the code by ~0.4% (measured)

// load the dictionary word for this thread
uint *word = &memory[0] + threadIdx.x*16;
for(int i=0; i != 16; i++)
{
getw(word, i) = gwords[(linidx)*16+i];
}

// compute MD5 hash
uint a, b, c, d;

RSA_KERNEL(word, a, b, c, d);

// return the hash
hash[(linidx)*4+0] = a;
hash[(linidx)*4+1] = b;
hash[(linidx)*4+2] = c;
hash[(linidx)*4+3] = d;
}

// The kernel (this is the entrypoint of GPU code)
// Loads the 64-byte word to be hashed from global to shared memory,
// calls the calculation routine, compares to target and flags if a match is found
__global__ void md5_search(uint *gwords, uint *succ, int realthreads)
{
int linidx = (gridDim.x*blockIdx.y + blockIdx.x)*blockDim.x + threadIdx.x; // assuming blockDim.y = 1 and threadIdx.y = 0, always
if(linidx >= realthreads) { return; } // this check slows down the code by ~0.4% (measured)

// load the dictionary word for this thread
uint *word = &memory[0] + threadIdx.x*16;
for(int i=0; i != 16; i++)
{
getw(word, i) = gwords[linidx*16+i];
}

// compute MD5 hash
uint a, b, c, d;

RSA_KERNEL(word, a, b, c, d);

if(a == target[0] && b == target[1] && c == target[2] && d == target[3])
{
succ[0] = linidx;
succ[3] = 1;
}
}

// A helper to export the kernel call to C++ code not compiled with nvcc
double execute_kernel(int blocks_x, int blocks_y, int threads_per_block, int shared_mem_required, int realthreads, uint *gpuWords, uint *gpuHashes, bool search)
{
dim3 grid;
grid.x = blocks_x; grid.y = blocks_y;

unsigned int hTimer;
CUT_SAFE_CALL( cutCreateTimer(&hTimer) );
CUDA_SAFE_CALL( cudaThreadSynchronize() );
CUT_SAFE_CALL( cutResetTimer(hTimer) );
CUT_SAFE_CALL( cutStartTimer(hTimer) );

if(search)
{
md5_search<<<grid, threads_per_block, shared_mem_required>>>(gpuWords, gpuHashes, realthreads);
}
else
{
md5_calc<<<grid, threads_per_block, shared_mem_required>>>(gpuWords, gpuHashes, realthreads);
}

CUT_CHECK_ERROR("md5_calc() execution failed\n");
CUDA_SAFE_CALL( cudaThreadSynchronize() );
CUT_SAFE_CALL( cutStopTimer(hTimer) );
double gpuTime = cutGetTimerValue(hTimer);
CUT_SAFE_CALL( cutDeleteTimer( hTimer) );

return gpuTime;
}

最佳答案

CUDA GPU 有一种特殊的逻辑存储,由 __constant__ 表示它基本上使用一种特殊的硬件缓存机制来改善对 CUDA 内核使用的频繁访问的常量值的访问时间。

rconst_cpu array 只是数据的 CPU 拷贝(要复制到 GPU rconst 数组,它位于常量内存中,如 __constant__ 所示)将位于 GPU 上的这个常量内存区域。

r函数(在 GPU 上运行)采用索引 i传递给它,并使用位 4-5(i)索引到 rconst 中的 4 个组之一。数组,并使用位 0-1(属于 i)从所选组中选择一个值。

关于这个语法:

w[(i+threadIdx.x) % 16];

如您所述,threadIdxpart of the CUDA extensions to C/C++ .它是一个内置变量,仅在设备代码中可用。它有 3 个维度:.x , .y , 和 .z , 它在设备代码中用于区分线程行为。 CUDA 体系结构本质上提供了一组由所有线程执行的代码。这些内置变量是允许线程执行彼此不同的事情的主要机制。

在此特定示例中,假设多个线程将执行生成此特定数组引用的代码。然后每个线程将访问 w 中的一个元素。等于 i 的数组传递给函数的索引,加上唯一的 threadIdx.x每个线程都有的索引。因此每个线程将访问 w 的不同元素。基于此引用。

这些问题似乎反射(reflect)了 C 和 CUDA 的基本方面。我不建议你尝试通过这种方式学习CUDA,我相信这样的问题很容易关闭,因为它清楚地表明你对CUDA缺乏了解,也许还有C。关闭问题的原因之一如下:

“要求代码的问题必须表现出对正在解决的问题的最低限度的理解。包括尝试过的解决方案,为什么它们不起作用,以及预期的结果。另请参阅:Stack Overflow 问题 list ”

因此我的建议是获得 few hours of basic exposure to CUDA programming首先,而不是仅仅拿起对你来说看起来很陌生的代码并要求其他人一点一点地破译它。

关于c++ - 这个自定义的 md5 哈希算法是如何实现的?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/19887261/

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