Lih-Yuan Deng , Bryan R. Winter , Jyh-Jen Horng Shiau , Henry Horng-Shing Lu , Nirman Kumar , Ching-Chi Yang
{"title":"并行化高效大阶多重递归生成器","authors":"Lih-Yuan Deng , Bryan R. Winter , Jyh-Jen Horng Shiau , Henry Horng-Shing Lu , Nirman Kumar , Ching-Chi Yang","doi":"10.1016/j.parco.2023.103036","DOIUrl":null,"url":null,"abstract":"<div><p>The general multiple recursive generator (MRG) of maximum period has been thought of as an excellent source of pseudo random numbers. Based on a <span><math><mi>k</mi></math></span>th order linear recurrence modulo <span><math><mi>p</mi></math></span><span>, this generator produces the next pseudo random number based on a linear combination of the previous </span><span><math><mi>k</mi></math></span> numbers. General maximum period MRGs of order <span><math><mi>k</mi></math></span> have excellent empirical performance, and their strong mathematical foundations have been studied extensively.</p><p><span>For computing efficiency, it is common to consider special MRGs with some simple structure with few non-zero terms which requires fewer costly multiplications. However, such MRGs will not have a good “spectral test” property when compared with general MRGs with many non-zero terms. On the other hand, there are two potential problems of using general MRGs with many non-zero terms: (1) its efficient implementation (2) its efficient scheme for its parallelization. Efficient implementation of general MRGs of larger order </span><span><math><mi>k</mi></math></span> can be difficult because the <span><math><mi>k</mi></math></span>th order linear recurrence requires many costly multiplications to produce the next number. For its parallelization scheme, for a large <span><math><mi>k</mi></math></span>, the traditional scheme like “jump-ahead parallelization method” for general MRGs becomes highly computationally inefficient. We proposed implementing maximum period MRGs with many nonzero terms efficiently and in parallel by using a MCG constructed from the MRG. In particular, we propose a special class of large order MRGs with many nonzero terms that also have an efficient and parallel implementation.</p></div>","PeriodicalId":54642,"journal":{"name":"Parallel Computing","volume":"117 ","pages":"Article 103036"},"PeriodicalIF":2.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Parallelizable efficient large order multiple recursive generators\",\"authors\":\"Lih-Yuan Deng , Bryan R. Winter , Jyh-Jen Horng Shiau , Henry Horng-Shing Lu , Nirman Kumar , Ching-Chi Yang\",\"doi\":\"10.1016/j.parco.2023.103036\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The general multiple recursive generator (MRG) of maximum period has been thought of as an excellent source of pseudo random numbers. Based on a <span><math><mi>k</mi></math></span>th order linear recurrence modulo <span><math><mi>p</mi></math></span><span>, this generator produces the next pseudo random number based on a linear combination of the previous </span><span><math><mi>k</mi></math></span> numbers. General maximum period MRGs of order <span><math><mi>k</mi></math></span> have excellent empirical performance, and their strong mathematical foundations have been studied extensively.</p><p><span>For computing efficiency, it is common to consider special MRGs with some simple structure with few non-zero terms which requires fewer costly multiplications. However, such MRGs will not have a good “spectral test” property when compared with general MRGs with many non-zero terms. On the other hand, there are two potential problems of using general MRGs with many non-zero terms: (1) its efficient implementation (2) its efficient scheme for its parallelization. Efficient implementation of general MRGs of larger order </span><span><math><mi>k</mi></math></span> can be difficult because the <span><math><mi>k</mi></math></span>th order linear recurrence requires many costly multiplications to produce the next number. For its parallelization scheme, for a large <span><math><mi>k</mi></math></span>, the traditional scheme like “jump-ahead parallelization method” for general MRGs becomes highly computationally inefficient. We proposed implementing maximum period MRGs with many nonzero terms efficiently and in parallel by using a MCG constructed from the MRG. In particular, we propose a special class of large order MRGs with many nonzero terms that also have an efficient and parallel implementation.</p></div>\",\"PeriodicalId\":54642,\"journal\":{\"name\":\"Parallel Computing\",\"volume\":\"117 \",\"pages\":\"Article 103036\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Parallel Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S016781912300042X\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Parallel Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S016781912300042X","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Parallelizable efficient large order multiple recursive generators
The general multiple recursive generator (MRG) of maximum period has been thought of as an excellent source of pseudo random numbers. Based on a th order linear recurrence modulo , this generator produces the next pseudo random number based on a linear combination of the previous numbers. General maximum period MRGs of order have excellent empirical performance, and their strong mathematical foundations have been studied extensively.
For computing efficiency, it is common to consider special MRGs with some simple structure with few non-zero terms which requires fewer costly multiplications. However, such MRGs will not have a good “spectral test” property when compared with general MRGs with many non-zero terms. On the other hand, there are two potential problems of using general MRGs with many non-zero terms: (1) its efficient implementation (2) its efficient scheme for its parallelization. Efficient implementation of general MRGs of larger order can be difficult because the th order linear recurrence requires many costly multiplications to produce the next number. For its parallelization scheme, for a large , the traditional scheme like “jump-ahead parallelization method” for general MRGs becomes highly computationally inefficient. We proposed implementing maximum period MRGs with many nonzero terms efficiently and in parallel by using a MCG constructed from the MRG. In particular, we propose a special class of large order MRGs with many nonzero terms that also have an efficient and parallel implementation.
期刊介绍:
Parallel Computing is an international journal presenting the practical use of parallel computer systems, including high performance architecture, system software, programming systems and tools, and applications. Within this context the journal covers all aspects of high-end parallel computing from single homogeneous or heterogenous computing nodes to large-scale multi-node systems.
Parallel Computing features original research work and review articles as well as novel or illustrative accounts of application experience with (and techniques for) the use of parallel computers. We also welcome studies reproducing prior publications that either confirm or disprove prior published results.
Particular technical areas of interest include, but are not limited to:
-System software for parallel computer systems including programming languages (new languages as well as compilation techniques), operating systems (including middleware), and resource management (scheduling and load-balancing).
-Enabling software including debuggers, performance tools, and system and numeric libraries.
-General hardware (architecture) concepts, new technologies enabling the realization of such new concepts, and details of commercially available systems
-Software engineering and productivity as it relates to parallel computing
-Applications (including scientific computing, deep learning, machine learning) or tool case studies demonstrating novel ways to achieve parallelism
-Performance measurement results on state-of-the-art systems
-Approaches to effectively utilize large-scale parallel computing including new algorithms or algorithm analysis with demonstrated relevance to real applications using existing or next generation parallel computer architectures.
-Parallel I/O systems both hardware and software
-Networking technology for support of high-speed computing demonstrating the impact of high-speed computation on parallel applications