加入 Gitee
与超过 1200万 开发者一起发现、参与优秀开源项目,私有仓库也完全免费 :)
免费加入
文件
该仓库未声明开源许可证文件(LICENSE),使用请关注具体项目描述及其代码上游依赖。
克隆/下载
xf86drmRandom.c 4.75 KB
一键复制 编辑 原始数据 按行查看 历史
luoyaoming 提交于 2022-08-22 15:56 . Import Upstream version 2.4.101
/* xf86drmRandom.c -- "Minimal Standard" PRNG Implementation
* Created: Mon Apr 19 08:28:13 1999 by faith@precisioninsight.com
*
* Copyright 1999 Precision Insight, Inc., Cedar Park, Texas.
* All Rights Reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and associated documentation files (the "Software"),
* to deal in the Software without restriction, including without limitation
* the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice (including the next
* paragraph) shall be included in all copies or substantial portions of the
* Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
* PRECISION INSIGHT AND/OR ITS SUPPLIERS BE LIABLE FOR ANY CLAIM, DAMAGES OR
* OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
* ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
* DEALINGS IN THE SOFTWARE.
*
* Authors: Rickard E. (Rik) Faith <faith@valinux.com>
*
* DESCRIPTION
*
* This file contains a simple, straightforward implementation of the Park
* & Miller "Minimal Standard" PRNG [PM88, PMS93], which is a Lehmer
* multiplicative linear congruential generator (MLCG) with a period of
* 2^31-1.
*
* This implementation is intended to provide a reliable, portable PRNG
* that is suitable for testing a hash table implementation and for
* implementing skip lists.
*
* FUTURE ENHANCEMENTS
*
* If initial seeds are not selected randomly, two instances of the PRNG
* can be correlated. [Knuth81, pp. 32-33] describes a shuffling technique
* that can eliminate this problem.
*
* If PRNGs are used for simulation, the period of the current
* implementation may be too short. [LE88] discusses methods of combining
* MLCGs to produce much longer periods, and suggests some alternative
* values for A and M. [LE90 and Sch92] also provide information on
* long-period PRNGs.
*
* REFERENCES
*
* [Knuth81] Donald E. Knuth. The Art of Computer Programming. Volume 2:
* Seminumerical Algorithms. Reading, Massachusetts: Addison-Wesley, 1981.
*
* [LE88] Pierre L'Ecuyer. "Efficient and Portable Combined Random Number
* Generators". CACM 31(6), June 1988, pp. 742-774.
*
* [LE90] Pierre L'Ecuyer. "Random Numbers for Simulation". CACM 33(10,
* October 1990, pp. 85-97.
*
* [PM88] Stephen K. Park and Keith W. Miller. "Random Number Generators:
* Good Ones are Hard to Find". CACM 31(10), October 1988, pp. 1192-1201.
*
* [Sch92] Bruce Schneier. "Pseudo-Ransom Sequence Generator for 32-Bit
* CPUs". Dr. Dobb's Journal 17(2), February 1992, pp. 34, 37-38, 40.
*
* [PMS93] Stephen K. Park, Keith W. Miller, and Paul K. Stockmeyer. In
* "Technical Correspondence: Remarks on Choosing and Implementing Random
* Number Generators". CACM 36(7), July 1993, pp. 105-110.
*
*/
#include <stdio.h>
#include <stdlib.h>
#include "libdrm_macros.h"
#include "xf86drm.h"
#include "xf86drmRandom.h"
#define RANDOM_MAGIC 0xfeedbeef
drm_public void *drmRandomCreate(unsigned long seed)
{
RandomState *state;
state = drmMalloc(sizeof(*state));
if (!state) return NULL;
state->magic = RANDOM_MAGIC;
#if 0
/* Park & Miller, October 1988 */
state->a = 16807;
state->m = 2147483647;
state->check = 1043618065; /* After 10000 iterations */
#else
/* Park, Miller, and Stockmeyer, July 1993 */
state->a = 48271;
state->m = 2147483647;
state->check = 399268537; /* After 10000 iterations */
#endif
state->q = state->m / state->a;
state->r = state->m % state->a;
state->seed = seed;
/* Check for illegal boundary conditions,
and choose closest legal value. */
if (state->seed <= 0) state->seed = 1;
if (state->seed >= state->m) state->seed = state->m - 1;
return state;
}
drm_public int drmRandomDestroy(void *state)
{
drmFree(state);
return 0;
}
drm_public unsigned long drmRandom(void *state)
{
RandomState *s = (RandomState *)state;
unsigned long hi;
unsigned long lo;
hi = s->seed / s->q;
lo = s->seed % s->q;
s->seed = s->a * lo - s->r * hi;
if ((s->a * lo) <= (s->r * hi)) s->seed += s->m;
return s->seed;
}
drm_public double drmRandomDouble(void *state)
{
RandomState *s = (RandomState *)state;
return (double)drmRandom(state)/(double)s->m;
}
马建仓 AI 助手
尝试更多
代码解读
代码找茬
代码优化