逻辑内置自测系统测试数据生成的有效并行处理技术

Paul Chang, B. Keller, S. Paliwal
{"title":"逻辑内置自测系统测试数据生成的有效并行处理技术","authors":"Paul Chang, B. Keller, S. Paliwal","doi":"10.1109/ATS.2000.893652","DOIUrl":null,"url":null,"abstract":"Logic Built-in Self rest (LBIST) is a test methodology adopted by some companies to test their complex processor designs. It can involve a very high volume of simulation, perhaps up to one to two million patterns. For large designs, the simulation time (which includes logic simulation, random stimulus generation and signature computations) can be enormous. Parallel processing provides a relief for this long simulation time. This paper describes a technique to efficiently partition patterns among different processors. These patterns are derived from on-product Pseudo-Random Pattern Generators (PRPGs) and the signature is a serial compression of the response data from all of the patterns. Both the PRPG and signature calculation have a serial pattern dependency, which normally would prohibit parallel simulation of the patterns. We show how to quickly advance a PRPG state to jump ahead to any specific pattern's starting state and an innovative post processing technique to compute correct signatures from initially incorrect ones computed in parallel among different processes. The results demonstrate that the overhead to correct the signatures is small and the parallel speed up is very effective.","PeriodicalId":403864,"journal":{"name":"Proceedings of the Ninth Asian Test Symposium","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Effective parallel processing techniques for the generation of test data for a logic built-in self test system\",\"authors\":\"Paul Chang, B. Keller, S. Paliwal\",\"doi\":\"10.1109/ATS.2000.893652\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Logic Built-in Self rest (LBIST) is a test methodology adopted by some companies to test their complex processor designs. It can involve a very high volume of simulation, perhaps up to one to two million patterns. For large designs, the simulation time (which includes logic simulation, random stimulus generation and signature computations) can be enormous. Parallel processing provides a relief for this long simulation time. This paper describes a technique to efficiently partition patterns among different processors. These patterns are derived from on-product Pseudo-Random Pattern Generators (PRPGs) and the signature is a serial compression of the response data from all of the patterns. Both the PRPG and signature calculation have a serial pattern dependency, which normally would prohibit parallel simulation of the patterns. We show how to quickly advance a PRPG state to jump ahead to any specific pattern's starting state and an innovative post processing technique to compute correct signatures from initially incorrect ones computed in parallel among different processes. The results demonstrate that the overhead to correct the signatures is small and the parallel speed up is very effective.\",\"PeriodicalId\":403864,\"journal\":{\"name\":\"Proceedings of the Ninth Asian Test Symposium\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Ninth Asian Test Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATS.2000.893652\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Ninth Asian Test Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATS.2000.893652","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

逻辑内置自休息(LBIST)是一些公司用来测试其复杂处理器设计的一种测试方法。它可能涉及非常大的模拟量,可能多达1到2百万个模式。对于大型设计,仿真时间(包括逻辑仿真、随机刺激生成和签名计算)可能是巨大的。并行处理缩短了模拟时间。本文描述了一种在不同处理器之间高效划分模式的技术。这些模式来源于产品上的伪随机模式生成器(prpg),签名是对来自所有模式的响应数据的串行压缩。PRPG和签名计算都具有串行模式依赖关系,这通常会禁止模式的并行模拟。我们展示了如何快速推进PRPG状态以跳转到任何特定模式的启动状态,以及一种创新的后处理技术,以从不同进程之间并行计算的最初不正确的签名中计算正确的签名。结果表明,校正签名的开销很小,并行加速效果显著。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective parallel processing techniques for the generation of test data for a logic built-in self test system
Logic Built-in Self rest (LBIST) is a test methodology adopted by some companies to test their complex processor designs. It can involve a very high volume of simulation, perhaps up to one to two million patterns. For large designs, the simulation time (which includes logic simulation, random stimulus generation and signature computations) can be enormous. Parallel processing provides a relief for this long simulation time. This paper describes a technique to efficiently partition patterns among different processors. These patterns are derived from on-product Pseudo-Random Pattern Generators (PRPGs) and the signature is a serial compression of the response data from all of the patterns. Both the PRPG and signature calculation have a serial pattern dependency, which normally would prohibit parallel simulation of the patterns. We show how to quickly advance a PRPG state to jump ahead to any specific pattern's starting state and an innovative post processing technique to compute correct signatures from initially incorrect ones computed in parallel among different processes. The results demonstrate that the overhead to correct the signatures is small and the parallel speed up is very effective.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信