Abstraction Levels in SoC Modeling - OCP-IP在SOC的抽象层次建模-国际合作共29页文档

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软件测试术语中英文对照

data corruption：数据污染
data definition C-use pair：数据定义C-use使用对
data definition P-use coverage：数据定义P-use覆盖
data definition P-use pair：数据定义P-use使用对
data definition：数据定义
data definition-use coverage：数据定义使用覆盖
data definition-use pair ：数据定义使用对
data definition-use testing：数据定义使用测试
Check In :检入
Check Out :检出
Closeout : 收尾
code audit ：代码审计
Code coverage : 代码覆盖
Code Inspection：代码检视
Core team : 核心小组
corrective maintenance：故障检修
correctness ：正确性
coverage ：覆盖率
coverage item：覆盖项
crash：崩溃
Beta testing : β测试
Black Box Testing：黑盒测试
Blocking bug : 阻碍性错误
Bottom-up testing : 自底向上测试
boundary value coverage：边界值覆盖
boundary value testing：边界值测试
Bug bash : 错误大扫除
bug fix : 错误修正
Bug report : 错误报告

半监督拉普拉斯特征映射算法

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０引．言
信息化时代的到来，伴随着大量高维数据的产生。现实生活中许多数据，如文本数据、图形数据、视频数据、语言数据等，在计算机当中都是以高维向量的形式进行存
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关键词：拉普拉斯特征映射算法；半监督机器学习；流形学习；低维信息；模式识别
中图法分类号：ＴＰ０．文献标识号：Ａ文章编号：１０ —０４（０２０ —６１０３１６００７２２１）２００—６

项目管理专业英语词汇

Abstract Resource抽象资源Abstraction抽象Acceleration加速Acceptability Criteria验收标准Acceptable Quality Level("AQL")可接受质量水平Acceptance验收Acceptance Criteria验收标准Acceptance Letters验收函Acceptance Number接受数目Acceptance Review验收评审Acceptance Test验收测试Acquisition Methods采购方式Acquisition Negotiations采购谈判Acquisition Plan采购计划Acquisition Plan Review("APR")采购计划评审Acquisition Planning采购计划编制Acquisition Process采购过程Acquisition Strategy采购策略Action行动Action Item行动项Action Item Flags行动项标记Action Plan行动计划Activation激活Active Listening积极倾听Activity Arrow Net活动箭线网络Activity Based Costing("ABC")基于活动的成本核算Activity Based Management("ABM")基于活动的管理Activity Calendar活动日历Activity Code活动代码Activity Definition活动定义Activity Description活动描述Activity Duration活动工期活动持续时间Activity Duration Estimating活动工期估算Activity Elaboration活动详述Activity File活动档案Activity ID活动识别码Activity List活动清单Activity Node Net活动节点网络双代号网络Activity on Arc("AOA")弧线表示活动双代号网络Activity on Arrow("AOA")箭线表示活动双代号网络参见Arrow Diagramming Method.Activity on Node节点表示活动单代号网络参见Activity on Arc和Precedence Diagram Method.Activity Oriented面向活动Activity Oriented Schedule面向活动的进度计划Activity Properties活动属性Activity Quantities活动量值Activity Status活动状态Activity Timing活动定时Actor执行者角色Actual实际的Actual and Scheduled Progress实际进展的与计划进度Actual Cost实际成本Actual Cost Data Collection实际成本汇总Actual Costs实际费用Actual Dates实际日期Actual Direct Costs实际直接成本Actual Expenditures实际的支出参见Actual Costs.Actual Finish实际完成Actual Finish Date实际完成日期Actual Start实际开始Actual Start Date实际开始日期ACWP已完成工作实际成本See Actual Cost of Work Performed Adaptation适应Added Value附加价值Addendum附录参见procurement addendum.Adequacy适当Adjourning解散Adjustment调节ADM参见Arrow Diagram MethodADM Project ADM项目Administration管理部门Administrative行政的参见Administrative Management Administrative Change行政变更Administrative Management行政管理ADP参见Automated Data ProcessingADR参见Alternative Dispute Resolution Advanced Material Release("AMR")材料提前发布AF参见Actual Finish DateAFE参见Application for Expenditure参见Authority for ExpenditureAffect影响Affected Parties受影响方Agency代理Agenda议程Aggregation汇总Agreement协议Agreement,legal协议合同ALAP参见As-Late-As-PossibleAlgorithm算法Alignment排列成行Alliance联合Allocated Baseline分配的基线Allocated Requirements分配需求Allocation分配Allowable Cost允许成本Allowance预留Alternate Resource替代资源Alternative Analysis替代分析Alternative Dispute Resolution("ADR")替代争议解决方案Alternatives可选方案Ambiguity含糊不清Amendment修订Amount at Stake损失量AMR材料提前公布Analysis分析Analysis and Design分析与设计Analysis Time分析期Analyst分析员AND Relationship与关系Anecdotal轶事Anticipated Award Cost预期中标价AOA参见Activity on Arrow参见Activity on ArcAON参见Activity on NodeAOQ参见Average Outgoing QualityAOQL参见Average Outgoing Quality Limit APMA参见Area of Project Management ApplicationApparent Low Bidder最低投标人Application应用Application Area应用领域Application for Expenditure("AFE")支出申请Application for Expenditure Justification支出申请的论证Application Programs应用程序Applied Direct Costs实际直接成本Apportioned Effort分摊努力Apportioned Task分摊任务Appraisal评估Approach方法Appropriation拨款Approval批准Approval to Proceed批准继续Approve同意Approved Bidders List批准的投标人清单Approved Changes批准的变更Approved Project Requirements批准的项目需求APR参见Acquisition Plan ReviewAQL参见Acceptable Quality LevelArbitrary随意的Arbitration仲裁Arc弧线Architectural Baseline构架基线Architectural View构架视图Architecture构架Architecture,executable构架可执行参见Executable Architecture.Archive档案文件Archive Plan存档计划Area of Project Application参见Area of Project Management ApplicationArea of Project Management Application ("APMA")项目管理的应用领域Arrow箭线Arrow Diagram参见Activity Arrow NetArrow Diagram Method("ADM")箭线图方法Arrow Diagramming箭线图方法Arrow Diagramming Method箭线图方法双代号网络图Artifact制品Artificial人工的AS参见Actual Start DateASAP参见As-Soon-As-PossibleAs-built Design实际建造设计As-built Documentation实际建造文档As-Built Records参见As-Built DocumentationAs-Built Schedule实际建造进度计划As-Late-As-Possible("ALAP")尽可能晚As-Needed恰如所需As-of Date见Data Date.As-Performed Schedule实际进度计划Assembly组装件Assembly Sequence组装顺序Assessment评估Assets资产Assignment分配委派任务Associated Revenue关联收益Association关联关系As-Soon-As-Possible("ASAP")尽快Assumption假设Assumptions假设Assumptions List假设清单Assurance保证Assurance Program见Quality Assurance Program.ATP见Acceptance Test ProcedureAttitude态度Attribute属性Attrition损耗Audit审核审计Authoritarian独裁的Authoritative权威的Authority权威权力Authority for Expenditure("AFE")开支权Authorization授权见ApprovalAuthorize批准Authorized Unpriced Work批准的未定价工作Authorized Work批准的工作Authorized Works批准的工作Automated Data Processing("ADP")自动化数据处理Automatic Decision Event自动决策事件Automatic Generation自动生成Automatic Test Equipment自动测试设备AUW见Authorized Unpriced WorkAuxiliary Ground Equipment辅助场地设备Availability可用性Average Outgoing Quality("AOQ")平均出厂质量Average Outgoing Quality Limit("AOQL")平均出厂质量限度Average Sample Size Curve平均样本规模曲线Avoidance避免Award授予Award Fee奖金Award Letter中标函BAC完工预算参见Budget at Completion参见Baseline at CompletionBack Charge逆向计费参见BackchargeBackcharge逆向收费Backward Pass倒推法/反向计算Bad Debts坏帐Balance余额权衡Balanced Matrix平衡矩阵Balanced Scorecard平衡记分卡参见Scoring a Project's Contribution Balanced Scorecard Approach("BSA")平衡记分卡方法Bank储备Banking储备Bar Chart横道图Bargaining讨价还价交涉Bargaining Power讨价还价权力交涉权力Barriers障碍Base基础基数Baseline基线基准Baseline at Completion("BAC")完成/完工基线Baseline Concept基线概念Baseline Control基线控制参见Configuration ControlBaseline Cost基线成本Baseline Dates基线日期Baseline Finish Date基线完成日期参见Scheduled Finish DateBaseline Management基线管理Baseline Plan基线计划基准计划Baseline Review基线评审Baseline Schedule基线进度计划Baseline Start Date基线开始日期参见Scheduled Start Date.Baseline,budget基线预算Baseline,business基线商业Baseline,cost estimate基线费用估算Baseline,technical基线技术Basis of Estimate估算根据Batch批量参见LotBatch Operation批运行/批处理BATNA参见Best Alternative to Negotiated AgreementBCM参见Business Change ManagerBCWP参见Budgeted Cost of Work Performed BCWS参见Budgeted Cost of Work Scheduled BEC参见Elapsed CostBehavior行为/反应Behavior Analysis行为分析参见Functional AnalysisBenchmark基准Benchmarking标竿管理Beneficial Occupancy/Use有益的占用/使用Benefits效益Benefits Framework效益框架Benefits Management效益管理Benefits Management Plan效益管理计划Benefits Management Regime效益管理制度Benefits Profiles效益简述Benefits Realization Phase效益实现阶段Best Alternative to Negotiated Agreement("BATNA")协议外最佳方案BATNABest and Final Contract Offer最佳及最终合同报价Best and Final Offer最佳及最终报价Best Efforts Contract最大努力合同Best Practices最佳实践Best Value最佳值Beta Distribution贝塔发布Beta Test贝塔测试Beta testing贝塔测试Bid投标Bid Analysis投标分析Bid Bond投标保证金Bid Cost Considerations投标成本补偿费Bid Document Preparation招标文件准备Bid Documents招标文件Bid Evaluation评标Bid List投标人清单Bid Package标段标块Bid Protests投标抗议/拒付Bid Qualifications投标资质Bid Response投标响应Bid Technical Consideration投标技术因素Bid Time Consideration投标中的时间因素Bid/No Bid Decision投标/不投标决策Bidder投标人Bidders Conference投标人会议Bidders List投标人名单Bidders Source Selection投标人来源选择Bidding投标Bidding Strategy投标策略Bill帐单Bill of Materials材料清单Bills of Materials材料清单Blanket Purchase Agreement("BPA")一揽子采购协议BPABlueprint蓝图/计划设计图Board委员会Boiler Plate样板文件Bona Fide真诚真实Bond担保Bonus奖金Bonus Schemes奖励计划Booking Rates预提费率BOOT参见Build,Own,Operate,Transfer Bottom Up Cost Estimate自下而上成本估算Bottom Up Cost Estimating自下而上成本估算Bottom Up Estimating自下而上估算Boundary边界BPA参见Blanket Purchase Agreement BPR参见Business Process Reengineering Brainstorming头脑风暴法Branching Logic分支逻辑关系Breach of Contract违约Breadboarding实验模型Break Even盈亏平衡Breakdown分解Breakdown Structure分解结构Break-Even Chart盈亏平衡图Break-Even Charts盈亏平衡图Break-Even Point盈亏平衡点Bribe贿赂BSA参见Balanced Scorecard ApproachBuck Passing完全通过/推卸责任Budget预算Budget at Completion("BAC")完工预算BACBudget Cost预算成本Budget Costs预算成本预算费用Budget Decrement预算消耗Budget Element预算要素Budget Estimate预算估算参见EstimateBudget Presentation预算介绍Budget Revision预算修订Budget Unit预算单位Budgetary Control预算性控制Budgeted已安排预算的Budgeted Cost of Work Performed("BCWP")已完工作预算成本BCWPBudgeted Cost of Work Scheduled("BCWS")计划工作的预算成本Budgeting制定预算Budgeting&Cost Management预算制定与成本管理Build建设构造Build,Own,Operate,Transfer("BOOT")建造拥有经营转让Buildability建造能力Building建筑物Building Professionalism建设专业化Build-to Documentation建成文档Built-in Test Equipment内置测试设备Bulk Material大宗材料Burden间接费用负担参见Indirect Cost.Burden of Proof举证费Bureaucracy官僚制度Burn Rate消耗速度Burst Node分支点Business Actor业务参与者/角色Business Appraisal商业评估Business Area业务领域Business Assurance商业保证Business Assurance Coordinator商业保证协调人Business Case商业案例Business Change Manager("BCM")商业变更经理BCMBusiness Creation商业创新Business Engineering商业工程Business Imperative商业需要Business Improvement业务改进Business Manager商务经理商业经理Business Modeling业务建模Business Needs商业需求Business Objectives商业目标Business Operations业务运作Business Process业务流程Business Process Engineering业务流程工程参见business engineeringBusiness Process Reengineering("BPR")业务流程重组Business Processes业务流程Business Risk商业风险Business Rule商业规则Business Transition Plan业务转换计划参见Transition PlanBusiness Unit业务单位Buyer买方Buyer's Market买方市场Buy-In支持认同买进Bypassing回避C/SCSC参见Cost/Schedule Control System CriteriaC/SSR参见Cost/Schedule Status ReportCA参见Control AccountCAD参见Computer Aided Drafting参见Computer Aided DesignCalculate Schedule估算进度安排Calculation计算Calendar日历参见Project Calendar.Calendar File日历文件Calendar Range日历范围Calendar Start Date日历开始日期Calendar Unit日历单位Calendar,Software日历软件Calendars日历集Calibration校准CAM参见Cost Account Manager参见Computer Aided Manufacturing参见Control Account ManagerCAP参见Cost Account Plan参见Control Account PlanCapability能力Capability Survey能力调查Capital资本Capital Appropriation资本划拨Capital Asset资本资产Capital Cost资本成本Capital Employed占用的资本Capital Expansion Projects资本扩展项目Capital Goods Project资本货物项目Capital Property资本财产CAR参见Capital Appropriation Request Cards-on-the-wall Planning墙卡规划法Career职业Career Path Planning职业路线规划Career Planning职业规划参见Career Path Planning.Carryover Type1结转类型1Carryover Type2结转类型2Cascade Chart层叠图CASE(1)参见Computer Aided Software EngineeringCASE(2)参见Computer Aided System Engineering Cash现金Cash Flow现金流Cash Flow Analysis现金流分析Cash Flow Management现金流管理Cash Flow,Net现金流净值Cash In现金流入Cash Out现金支出Catalyst催化者Catch-up Alternatives赶上计划的备选方案Causation起因Cause动因CBD参见Component-Based DevelopmentCBS参见Cost Breakdown StructureCCB参见Change Control BoardCCDR参见Contractor Cost Data ReportCDR参见Critical Design ReviewCentral Processing Unit("CPU")中央处理单元Centralized集中的Certain确定的参见Certainty.Certainty确定性Certificate of Conformance一致性认证Certification认证Chain链Challenge挑战Champion推动者支持者Change变更变化变革Change Control变更控制Change Control Board("CCB")变更管理委员会Change Documentation变更文档Change in Scope工作范围变化参见Scope Change.Change Log变更日志Change Management变更管理Change Management Plan变更管理计划Change Notice变更通知Change Order变更通知单参见Variation OrderChanged Conditions变更的条款Characteristic特性Chart图表Chart of Accounts会计科目表Chart Room图表室Charter章程参见Project CharterChecking检查Checklist检查清单Checkpoint检查点Checkpoints检查点集Chief Executive Officer首席执行官Child子项Child Activity子活动CI参见Configuration ItemClaim索赔Clarification澄清Class类Classes类Classification分类Classification of Defects缺陷的分类Clearance Number净空数Client客户Client Environment客户环境Client Quality Services客户质量服务Closed Projects已收尾的项目Closeout收尾Closeout Report收尾报告Closeout,phase收尾阶段参见Project Closeout.Closing终止Closure收尾CM参见Configuration Management参见Construction ManagementCoaching教练Code代码参见Source Code.Code and Unit Test编码和单元测试Code of Accounts帐目编码Coding编码Collaboration协作Collapsing折叠Collective集体的Combative好战的Commercial商务的Commercial Item Description商务描述Commission and Handover委托和移交Commissioning试运行Commissions and Bonuses酬金和奖金Commit提交Commitment承诺义务Commitment Document承诺文件Commitment Estimate参见Estimate Class ACommitment Package承诺包Commitment to Objectives对目标的承诺Committed Cost已承担成本已承付成本Committed Costs已承诺费用Common Carrier公众运营商Communicating With Groups与团队的沟通Communicating With Individuals与个人的沟通Communication沟通参见Effective Communication. Communication Channels沟通渠道Communication Plan,Strategic沟通计划策略性的Communication Plan,Tactical沟通计划--战术性的Communication Room交流室Communications Management沟通管理Communications Plan沟通计划Communications Planning沟通规划编制Community社团Company公司Comparison对比Compatibility兼容性Compensation补偿Compensation and Evaluation补偿和评价Competence能力Competency能力Competition竞争Competitive:竞争的Compile编译Compile Time编译时Complete完成Completed Activity已完成的活动Completed Units完工单元Completion完工Completion Date完成日期Complex复杂的参见Project Complexity.Component构件组件Component Integration and Test组件集成和测试Component-Based Development("CBD")基于构件的开发Components组件Compound Risk复合风险Compromise折衷Compromising,in negotiating折衷谈判Computer计算机Computer Aided Design("CAD")计算机辅助设计Computer Aided Drafting("CAD")计算机辅助制图Computer Aided Manufacturing("CAM")计算机辅助制造Computer Cost Applications计算机化的成本管理应用Computer Hardware计算机硬件Computer Modeling计算机建模Computer Program Configuration Item计算机程序配置项参见Computer Software Configuration Item.Computer Software计算机软件Computer Software Component计算机软件组件Computer Software Configuration Item("CSCI")计算机软件配置项Computer Software Documentation计算机软件文档Computer Software Unit计算机软件单元Computer-Aided计算机辅助的Computerized Information Storage, Reference and Retrieval计算机化的信息存储定位和检索Concept概念Concept Definition Document概念定义文档Concept Phase概念阶段Concept Study概念研究Conception Phase概念形成阶段Conceptual概念性的参见Concept.Conceptual Budgeting概念性预算Conceptual Design概念性设计Conceptual Development概念性开发Conceptual Project Planning概念性项目计划Concession让步Concession Making,in negotiating谈判中的让步Conciliatory调和的Concluding终决的Conclusions结论Concurrency并发性Concurrent并发事件Concurrent Delays并行延迟Concurrent Engineering并行工程Concurrent Tasks并行任务Conditional Risk条件风险Conditions条件条款Conducting执行Confidence Level信心等级Configuration配置Configuration Audit配置审核Configuration Breakdown配置分解Configuration Control配置控制Configuration Control Board配置控制委员会Configuration Identification配置识别Configuration Item Acceptance Review配置项验收评审Configuration Item Verification配置项验证Configuration Item Verification Procedures配置项验证程序Configuration Management配置管理Configuration Management Board配置管理委员会Configuration Relationships配置关系Configuration Status Accounting配置状态统计Conflict冲突Conflict Management冲突管理Conflict Resolution冲突解决方案Conformance to Requirements与需求的一致性Confrontation积极面对Consensus一致同意Consensus Decision Process集体决策过程Consent同意Consequences后果Consideration对价Considerations对价需要考虑的事项Consolidate合并Consortium联盟Constituents涉众Constraint约束条件Constraint,project constraint约束条件对项目的约束Constraints约束条件Constructability施工能力Construction施工构造建造建筑Construction Contractor施工承包商Construction Cost施工成本Construction Management("CM")施工管理Construction Manager施工经理Construction Stage施工阶段Construction Work施工工作Construction-Oriented以施工为导向的Constructive Challenge建设性质询Constructive Change建设性变更Consultant咨询顾问Consulting咨询Consumable Resource可消耗资源Consumables消费性物资Contemplated Change Notice预期变更通知Contending,in negotiating争论在谈判中Content内容Content Type内容类型Context背景Contingencies不可预见费应急费用参见Reserve and Contingency Planning. Contingency不可预见费应急费用Contingency Allowance应急补助参见Reserve.Contingency Budget Procedure不可预见费用预算程序Contingency Plan意外事件计划Contract Package合同包参见Contract Breakdown.Contract Performance Control合同履行控制Contract Plan合同计划Contract Pre-award Meetings合同预授予会议Contract Quality Requirements合同质量要求Contract Requirements合同要求Contract Risk合同风险Contract Risk Analysis合同风险分析Contract Signing合同签署Contract Strategy合同战略Contract Target Cost("CTC")合同目标成本Contract Target Price("CTP")合同目标价格Contract Type合同分类Contract Types合同类型Contract Work Breakdown Structure ("CWBS")合同工作分解结构Contract/Procurement Management合同/采购管理Contracting签订合同Contractor承包商Contractor Claims Release承包商索赔豁免Contractor Cost Data Report("CCDR")承包商成本数据报告Contractor Evaluation承包商评估Contractor Furnished Equipment承包商供应的设备Contractor Project Office承包商项目办公室Contractor Short Listing承包商短列表Contractor's Performance Evaluation承包商的绩效评价Contractual合同的参见Contractual Conditions. Contractual Conditions合同条款Contractual/Legal Requirements合同的/法律上的要求Contributed Value贡献价值参见Added Value.Contribution Analysis贡献分析Control控制参见Project Control和Control Cycle. Control Account("CA")控制帐目Control Account Manager("CAM")控制帐目经理Control Account Plan("CAP"):控制帐目计划Control and Coordination控制和协调Control Chart控制表Control Cycle控制周期Control Gate控制关口控制关卡参见Management Control Point.Control Loop控制回路Control Point控制点Control Requirements控制必要条件要求Control System控制系统Control Theory控制论Controllable Risks可控风险Controlling控制参看Project ControlControlling Relationship控制关系Coordinated Matrix协调型的矩阵Coordination协调Coordinator协调员Corporate公司Corporate Administration and Finance公司行政和财务Corporate Budget.公司预算Corporate Business Life Cycle公司商务生命周期Corporate Constraints公司限制因素Corporate Data Bank公司数据库Corporate Management公司管理Corporate Memory公司记忆库Corporate Philosophy公司价值体系,公司哲学Corporate Planning公司计划编制Corporate Project Management公司项目管理Corporate Project Strategy公司项目战略Corporate Quality Standards公司质量标准Corporate Resources公司资源Corporate Responsibility Matrix公司责任矩阵Corporate Standards公司标准Corporate Supervision公司监管Corporation公司Correction纠正Corrective Action纠正措施Correlation相关性Cost成本参见Project Cost.Cost Account成本帐目Cost Account Breakdown成本帐目分解Cost Account Manager("CAM")成本帐目经理Cost Account Plan("CAP")成本帐目计划Cost Accumulation Methods成本累加方法Cost Analysis成本分析Cost Applications成本应用Cost Avoidance成本规避Cost Baseline成本基线Cost Benefit成本效益Cost Benefit Analysis成本效益分析Cost Breakdown Structure成本分解结构Cost Budgeting成本预算Cost Ceiling封顶成本成本上限Cost Ceiling Bracket成本上限范围Cost Center成本中心Cost Check成本检查Cost Classes成本类别Cost Code成本代码Cost Codes成本代码Cost Control成本控制Cost Control Point成本控制点Cost Control System成本控制系统Cost Curve成本曲线Cost Distribution成本分摊Cost Effective成本效率成本有效的Cost Element成本元素Cost Engineering成本工程Cost Envelope成本区域Cost Estimate成本估算Cost Estimate Classification System成本估算分类系统Cost Estimating成本估算Cost Estimating Relationship成本估算关系Cost Forecast成本预测Cost Forecasting成本预测Cost Growth成本增长Cost Incurred已发生成本Cost Index成本指数Cost Indices成本指数表Cost Input成本投入Cost Management成本管理Cost Model成本模型Cost of Money资金成本Cost of Quality质量成本Cost Overrun成本超支Cost Performance Baseline成本绩效基线请参见"Cost Baseline".Cost Performance Index("CPI")成本绩效指数Cost Performance Indicator("CPI")成本绩效指数Cost Performance Measurement Baseline 成本绩效度量基线Cost Performance Ratio("CPR")成本绩效比率参见Cost Performance IndicatorCost Performance Report("CPR")成本绩效报告Cost Plan成本计划Cost Plus成本补偿Cost Plus Fixed Fee Contract("CPFF")成本加固定费用合同Cost Plus Incentive Fee Contract ("CPIFC")成本加奖励费用合同Cost Plus Percentage of Cost Contract ("CPPC")成本加成本百分比合同Cost Reimbursable Contract成本补偿合同费用可偿还合同Cost Reimbursement成本补偿Cost Reimbursement Type Contracts成本补偿型合同Cost Reviews成本评审Cost Savings成本节约Cost Sharing Contract成本共享合同Cost Status成本状态Cost to Complete竣工尚需成本Cost to Complete Forecast竣工所需成本预测Cost Types成本类型Cost Variance("CV")成本偏差Cost/Schedule Status Report("C/SSR")成本/进度状态报告Cost-Benefit Analysis成本效益分析Costed Work Breakdown Structure带成本信息的工作分解结构Cost-Effectiveness成本效果分析法Costing成本核算Costing Systems成本核算系统Cost-Time Resource Sheet("CTR")成本时间资源表Counseling指导Countermeasures对策CPFFC参见"Cost Plus Fixed Fee Contract" CPI参见"Cost Performance Index".参见"Cost Performance Indicator". CPIF成本加奖励费用合同参见"Cost Plus Incentive Fee Contract"CPIFC参见"Cost Plus Incentive Fee Contract" CPM参见"Critical Path Method"CPN参见"Critical Path Network"CPPC参见"Cost Plus Percentage of Cost Contract"CPR参见"Cost Performance Ratio"参见Cost Performance Report"CPU参见"Central Processing Unit"CR参见"Change Request"Craft技艺Crash Costs赶工成本Crash Duration赶工工期Crashing赶工Creativity创造力Credit赊欠信誉Credited Resource已授予的资源Crisis危机Criteria标准指标Criterion标准指标Critical关键的Critical Activity关键活动Critical Chain关键链Critical Defect关键性缺陷Critical Defective有关键缺陷的产品Critical Design Review关键设计评审Critical Event关键事件Critical Factors关键因素Critical Path关键路径Critical Path Analysis关键路径分析Critical Path Method("CPM")关键路径法Critical Path Network("CPN")关键路径网络图Critical Performance Indicator关键绩效指标Critical Ratio临界比关键比率Critical Sequence关键工序Critical Sequence Analysis关键工序分析Critical Subcontractor关键分包商Critical Success Factors("CSF")关键的成功因素Critical Task关键任务Critical Work Item关键工作项Criticality Index关键指数Cross Organizational交叉型组织跨组织的Cross References交叉参照Cross-Stage Plan交叉阶段计划CSCI参见"Computer Software Configuration Item".CSF参见"Critical Success Factors"CTC参见"Contract Target Cost"CTP参见"Contract Target Price"CTR参见"Cost-Time Resource Sheet" Culture文化Culture,organizational文化组织文化Cumulative Cost-to-Date到目前为止的累计成本参见Total Expenditure to Date" Cumulative S Curve累计S曲线参见"S Curve"Currency Conversion货币兑换Current Budget当前预算Current Date Line当前日期线Current Finish Date当前完成日期Current FY Budget Allocation当前财政年的预算分配Current Start Date当前开始日期Current Status当前状态Current Year当年Custom Duty and Tax海关关税Customer客户Customer Acceptance Criteria客户验收标准Customer Furnished Equipment客户提供的设备Customer Perspective客户观点Customer/Client Personnel客户方的职员Cutoff Date移交日期Cutover移交CV参见Cost Variance"CWBS参见"Contract Work Breakdown Structure"Cybernetics控制论Cycle周期Cycle Time周期Damages损害赔偿金Dangle悬空活动Data数据Data Application数据应用Data Bank参见"Corporate Memory"Data Collection数据收集Data Date("DD")数据日期Data Entry Clerk数据录入员Data Item Description("DID")工作项描述Data Processing数据处理Data Refinements数据改进Data Type数据类型Data Structure Organization数据结构组织Database数据库Database Administrator("DBA")数据库管理员Database Management System("DBMS")数据库管理系统Date of Acceptance验收日期Day Work Account日常工作帐户DBA参见"Database Administrator"DBM见"Dynamic Baseline Model"DBMS参见"Database Management System" DCE参见"Distributed ComputingEnvironment"DCF参见"Discounted Cash Flow"DD参见"Data Date"Deactivation Plan惰性化计划Deactivation Procedures惰性化流程Debriefing投标反馈听取情况汇报情况Decentralized分散的Decision决策Decision Documentation决策文档Decision Event决策事件Decision Making制定决策Decision Making Process决策过程Decision Support System决策支持系统Decision Theory决策论Decision Tree决策树Decision Trees决策树组Decomposing分解Decomposition分解Default违约Default Values默认值Defect缺陷Defective缺陷产品Defects-Per-Hundred-Units每百个单元有缺陷的数量Deficiency缺陷Deficiency List缺陷清单Definition定义Definition Phase定义阶段Definitive确定性的Definitive Estimate确定性估算参见"Estimate"Deflection风险转移Degradation降级Delay延期Delay,compensable补偿性延期Delaying Resource资源延期Delegating授权Delegation授权Deliberate Decision Event预先准备的决策事件Deliverable可交付成果,可交付物参见"Product".Deliverable Breakdown Structure可交付物分解结构参见"Work Breakdown Structure" Deliverable Deadline可交付物的终止期限Deliverables可交付成果可交付物Deliverables Management交付物管理Delivery交付Delphi Technique德尔菲法Demonstrate演示证明Demonstrated已证明的Demonstrated Past Experience已证明的过去经验Demonstration演示Demonstration Review演示评审Department部门Departmental Budget部门预算Dependability可靠性Dependencies依赖关系Dependency活动之间的依赖关系参见Logical Relationship" Dependency Arrow关系箭线Dependency Diagram网络图前导网络图Dependency Links依赖关系Dependency Management依赖关系管理Deployment部署Deployment Lessons Learned Document部署的经验教训文档Deployment Plan部署计划Deployment Procedures部署流程Deployment Readiness Review部署准备评审Deployment View部署视图Depreciation折旧Descriptive描述性的Design设计Design&Development Phase设计和开发阶段Design Alternatives设计备选方案Design Appraisal设计评估Design Authority设计权威Design Baseline基准设计Design Bid Build设计阶段投标的建立Design Brief设计大纲Design Build设计的建立包括设计和构造Design Concept设计概念Design Contingency设计应急费用Design Contract设计合同Design Control设计控制Design Development设计开发Design Management设计管理Design Management Plan设计管理计划Design Model设计模型Design of Experiment试验设计Design Package设计包Design Review设计评审Design Subsystem设计子系统Design Time设计时间Design to Budget按预算设计Design to Cost按成本设计Design-to Specifications按规范设计Desirable Logic合意逻辑Detail Documentation详细的文档Detail Schedule详细的进度安排Detailed Design详细设计Detailed Design Stage详细设计阶段Detailed Engineering详细工程Detailed Planning详细计划Detailed Plans详细的计划参见Detailed Resource Plan和Detailed Technical PlanDetailed Resource Plan详细的资源计划Detailed Schedule详细的进度安排Detailed Technical Plan详细的技术计划Determination决定决心Determine Least Cost for Maximum Results 确定可以获得最大收获的最小成本参见Cost Benefit"Deterministic确定性的Deterministic Network确定的网络图Developed Country发达国家Developer开发人员Developing Country发展中国家Development开发参见"Development Phase"Development case开发案例Development Phase开发阶段Development Plan开发计划Development process开发过程Deviation偏差Deviation Permit允许偏差参见"Production Permit"Diagram图Diagramming参见"Scheduling"DID参见"Data Item Description" Differences偏差差异Differentials差值Differing Site Conditions不同的现场环境Direct Cost直接成本Direct Cost Contingency直接成本应急费用参见"Project Direct Cost Contingency" Direct Costs直接成本Direct Labor直接人工Direct Project Costs直接项目成本费用Directing指挥Direction指导Directive指示Director主管总监Discipline学科Discipline Maintenance规矩的维护Discontinuous Activity非连续的活动Discontinuous Processing非连续的过程Discount Rate贴现率折现率Discounted Cash Flow("DCF")折现现金流Discounting折现Discrete Effort离散工作Discrete Milestone离散里程碑Discrete Task离散任务Discrimination歧视Discussion讨论Display显示Disposal of Materials材料处置Dispute辩论Disruption破坏Disruptive破坏性的Dissemination分发。

Soc设计

Focus shifted from individual products to product "platforms" Many IPs: hardware and software Application or architecture related platform Short develop time
System on Programmable Chip -SoPC
•
Many IPs + FPGA/CPLD on a chip Customizable: Chip was fabricated most of the way Only last few metal layers waiting for your custom part Field-programmable: Chip bought as it, customized by customer like FPGA Allowed to change the functionality of the chip according to the application
Motivation of SoC
• Application perspective

• Engineering design perspective

More complicated system Low cost of computation Higher reliability
What is SoC?
• SoC: System-on-Chip

• SoC Design: system architecture+ IC
Complex integrated circuit (IC) that integrates the major functional elements of a complete end-product into a single chip using silicon intellectual property (IP) blocks. Dataquest 1995: Contains at lest one of MPU or DSP core and memory and more than 100k gates

Sequence Diagram

Problem Statement:Implement Sequence diagram for capturing and representation, requirements of a system. Theory:A sequence diagram is a kind of interaction diagram that shows how processes operate with one another and in what order. It is a construct of a Message Sequence Chart.A sequence diagram shows object interactions arranged in time sequence.Purpose:The sequence diagram is used primarily to show the interactions between objects in the sequential order that those interactions occur. Much like the class diagram, developers typically think sequence diagrams were meant exclusively for them. However, an organization's business staff can find sequence diagrams useful to communicate how the business currently works by showing how various business objects interact.Besides documenting an organization's current affairs, a business-level sequence diagram can be used as a requirements document to communicate requirements for a future system implementation. During the requirements phase of a project, analysts can take use cases to the next level by providing a more formal level of refinement. When that occurs, use cases are often refined into one or more sequence diagrams.Elements of Sequence diagram:Sequence diagrams are constructed from the following:LifelinesWhen drawing a sequence diagram, lifeline notation elements are placed across the top of the diagram. Lifelines represent either roles or object instances that participate in the sequence being modeled. [Note: In fully modeled systems the objects (instances of classes) will also be modeled on a system's class diagram.] Lifelines are drawn as a box with a dashed line descending from the center of the bottom edge (Figure 3). The lifeline's name is placed inside the box.Figure 3: An example of the Student class used in a lifeline whose instance name is freshmanThe UML standard for naming a lifeline follows the format of:Instance Name : Class NameIn the example shown in Figure 3, the lifeline represents an instance of the class Student, whose instance name is freshman. Note that, here, the lifeline name is underlined. When an underline is used, it means that the lifeline represents a specific instance of a class in a sequence diagram, and not a particular kind of instance (i.e., a role).Our example lifeline in Figure 3 is a named object, but not all lifelines represent named objects. Instead a lifeline can be used to represent an anonymous or unnamed instance. When modeling an unnamed instance on a sequence diagram, the lifeline's name follows the same pattern as a named instance; but instead of providing an instance name, that portion of the lifeline's name is left blank.MessagesThe first message of a sequence diagram always starts at the top and is typically located on the left side of the diagram for readability. Subsequent messages are then added to the diagram slightly lower then the previous message.To show an object (i.e., lifeline) sending a message to another object, you draw a line to the receiving object with a solid arrowhead (if a synchronous call operation) or with a stick arrowhead (if an asynchronous signal). The message/method name is placed above the arrowed line. The message that is being sent to the receiving object represents an operation/method that the receiving object's class implements.Besides just showing message calls on the sequence diagram, the Figure 4 diagram includes return messages. These return messages are optional; a return message is drawn as a dotted line with an open arrowhead back to the originating lifeline, and above this dotted line you place the return value from the operation. In Figure 4 the secSystem object returns userClearance to the system object when the getSecurityClearance method is called. The system object returns availableReports when the getAvailableReports method is called.Again, the return messages are an optional part of a sequence diagram. The use of returnmessages depends on the level of detail/abstraction that is being modeled.GuardsWhen modeling object interactions, there will be times when a condition must be met for a message to be sent to the object. Guards are used throughout UML diagrams to control flow. Here, I will discuss guards in both UML 1.x as well as UML 2.0. In UML 1.x, a guard could only be assigned to a single message. To draw a guard on a sequence diagram in UML 1.x, you placed the guard element above the message line being guarded and in front of the message name.How to Draw?To create a sequence diagram:1.On the Architecture menu, click New Diagram.2.Under Templates, click UML Sequence Diagram. the diagram.4.In Add to Modeling Project, select an existing modeling project in your solution, orCreate a new modeling project, and then click OK.A new sequence diagram appears with the Sequence Diagram toolbox. Thetoolbox contains the required elements and connectors.To draw a sequence diagram:1.Drag Lifelines from the Toolbox onto the diagram to represent instances of classes,components, actors, or devices.You can also create a lifeline by dragging an existing class, interface, actor or component from UML Model Explorer onto the diagram. This creates a lifeline representing an instance of the chosen type.2.Draw messages to show how the lifelines collaborate to achieve a specific goal.To create a message, click a message tool. Then click the sending lifeline at the point where you want the message to start, and then click the receiving lifeline.An execution occurrence appears at the receiving lifeline. The execution occurrence represents a period of time during which the instance is executing a method.You can create other messages that start from an execution occurrence.3.To show a message that comes from an unknown event source, or broadcasts to unknownrecipients, draw an asynchronous message from or to blank space on the diagram. Thesemessages are called found messages and lost messages.4.Draw sequence diagrams for each major message to the same component or system. Example:Applications of Sequence Diagrams:·We should use sequence diagrams when we want to look at the behavior of several objects within a single use case.· Sequence diagrams are good at showing collaborations among the objects.· They are not so good at precise definition of behavior.In short,Sequence Diagrams - capture some elements of the dynamics of systems, support a number of different activities, describe interaction in some detail, including timing Conclusion:Thus we have successfully studied and implemented sequence diagram of a system。

中英文地理信息系统(GIS)英语词汇表

accreditation 委派accuracy 准确度acquisition 获取activity patterns 活动模式added value 附加值adjacency邻接Aeolian 伊奥利亚人的, 风的, 风蚀的Age of Discovery 发现的年代aggregation聚合algorithm, definition算法,定义ambiguity 不明确analytical cartography 分析制图application programming interfaces(APIs) 应用编程接口ARCGis 美国ESRI公司开发的世界先进的地理信息系统软件ArcIMS 它是个强大的，基于标准的工具，让你快速设计和管理Internet地图服务ArcInfo 在ArcGIS软件家族中，ArcInfo是GIS软件中功能最全面的。

它包含ArcView和ArcEditor 所有功能，并加上高级空间处理和数据转换ArcNews 美国ESRI向用户终生免费赠送的ArcNews报刊ArcSDE ArcSDE在ESRI GIS软件和DBMS之间提供通道，是一个空间数据引擎ArcUser Magazine 为ESRI用户创建的报刊ArcView 桌面GIS和制图软件，提供数据可视化，查询，分析和集成功能，以及创建和编辑地理数据的能力ARPANET ARPA 计算机网（美国国防部高级研究计划局建立的计算机网）aspatial data 非空间数据？Association of Geographic Information (AGI) 地理信息协会attribute data 属性数据attributes, types 属性，类型attributive geographic data 属性地理数据autocorrelation 自相关Autodesk MapGuide 美国Autodesk公司生产的Web GIS软件Automated mapping/facility management(AM/FM) systems 自动绘图/设备管理系统facilities 设备avatars 化身A VIRIS 机载可见光/红外成像光谱仪azimuthal projections 方位投影batch vectorization 批量矢量化beer consumption 啤酒消费benchmarking 基准Berry, Brianbest fit line 最优线binary counting system 二进制计算系统binomial distribution 二项式分布bivariate Gaussian distribution 二元高斯分布block encoding 块编码Bosnia, repartitioning 波斯尼亚，再分离成两个国家buffering 缓冲区分析Borrough, PeterBusiness and service planning(retailing) application in petroleum and convenience shopping 石油和便利购物的业务和服务规划（零售）应用business drivers 业务驱动business, GIS as 业务，地理信息系统作为Buttenfield, Barbaracadasters 土地清册Callingham, Martincannibalizing 调拨Cartesian coordinate system笛卡尔坐标系Cartograms 统计地图cartographic generalization 制图综合cartographic modeling 地图建模cartometric transformations 量图变换catalog view of database 数据库目录视图census data人口普查数据Census of Population 人口普查central Place Theory 中心区位论central point rule 中点规则central tendency 中心倾向centroid 质心choropleth mapping分区制图choosing a GIS 选择一个地理信息系统class 类别classification generalization 分类综合client 客户端client-server C/S结构客户端-服务器cluster analysis 聚类分析clutter 混乱coastline weave 海岸线codified knowledge 编码知识COGO data 坐标几何数据COGO editing tools 坐标几何编辑工具Collaboration 协作Local level 地方级National level 国家级Collection-level metadata 获取级元数据Commercial-off-the-shelf (COTS) systems 成熟的商业化系统chemas-microsoft-comfficeffice" />>> Commom object request broker architecture (CORBA) 公共对象请求代理体系结构Community, GIS 社区，地理信息系统Competition 竞争Component GIS 组件地理信息系统Component object model (COM) 组件对象模型Computer assisted mass appraisal (CAMA) 辅助大量估价，>>Computer-aided design (CAD)-based GIS 基于计算机辅助制图的地理信息系统Models 数据模型Computer-aided software engineering (CASE) tool 计算机辅助软件工程工具Concatenation 串联Confidence limits 置信界限Conflation 异文合并Conformal property 等角特性Confusion matrix 混淆矩阵Conic projections 圆锥投影Connectivity 连接性Consolidation 巩固Constant term 常数项Contagious diffusion 传染扩散Continuing professional development (CPD) 持续专业发展Coordinates 坐标Copyright 版权Corridor 走廊Cost-benefit analysis 成本效益分析Cost-effectiveness evaluation 成本效率评估Counting method 计算方法Cresswell, PaulCustomer support 客户支持Cylindrical Equidistant Projection 圆柱等距投影Cylindrical projections 圆柱投影> >Dangermond, Jack 美国ESRI总裁>> dasymetric mapping 分区密度制图>>data 数据>>automation 自动化>>capture costs 获取代价>>capture project 获取工程>>collection workflow 采集工作流>> compression 压缩>>conversion 转换>>definition 定义>>geographic, nature of 地理数据，数据的性质>> GIS 地理信息系统>>industry 产业>>integration 集成>>mining 挖掘>>transfer 迁移>>translation 转化>>data model 数据模型>> definition 定义>>levels of abstraction 提取等级>> in practice 实际上>>types 类型>>database 数据库>>definition 定义>>design 设计>>generalization 综合>>global 全球的>>index 索引>>multi-user editing 多用户编辑>> structuring 结构>>database management system (DBMS) 数据库管理系统>>capabilities 能力>>data storage 数据存储>>geographic extensions 地理扩展>>types 类型>>Dayton Accord 达顿协定，1995年12月达顿协定(DAYTON ACCORD)签订,巴尔干和平已经实现,波斯尼亚(包括黑塞哥维那)再被分解成两个国家>>decision support 决策支持>>deductive reasoning 演绎推理>>definitions of GIS 地理信息系统的各种定义>>degrees of freedom 自由度>>density estimation 密度估算>>dependence in space 空间依赖>>desktop GIS 桌面地理信息系统>>desktop paradigms 桌面范例>>Digital Chart of the World (DCW) 世界数字化图>>digital divide 数字鸿沟>>Digital Earth 数字地球>>Digital elevation models (DEMs) 数字高程模型>>Digital line graph (DLG) 数字线划图>>Digital raster graphic (DRG) 数字影像图>>Digital representation 数字表现>>Digital terrain models 数字地形模型>>Digitizing 数字化>>DIME (Dual Independent Map Encoding) program 美国人口调查局建立的双重独立地图编码系统>> Dine CARE >>Discrete objects 离散对象>>Douglas-Poiker algorithm 道格拉斯-普克算法，一种矢量数据抽稀算法>>Dublin Core metadata standard 都柏林核心元数据标准>>Dynamic segmentation 动态分割>>Dynamic simulation models 动态仿真模型>>> >Easting 朝东方>>Ecological fallacy 生态谬误>>e-commerce 电子商业>>editing 编辑>>education 教育>>electromagnetic spectrum 电磁光谱>>ellipsoids 偏振光椭圆率测量仪>>of rotation 旋转的>>emergency evacuation 应急撤退>>encapsulation 封装>>environmental applications 环境应用>>environmental impact 环境影响>>epidemiology 流行病学>>equal area property 等面积特性>>Equator 赤道>>ERDAS ERDAS公司是世界上最大的专业遥感图像处理软件公司，用户遍布100多个国家，软件套数超过17000套。

synopsys iC Compiler II 数据手册说明书

DATASHEETOverview IC Compiler™ II is the industry leading place and route solution that delivers best-in-class quality-of-results (QoR) for next-generation designs across all market verticals and process technologies while enabling unprecedented productivity. IC Compiler II includes innovative for flat and hierarchical design planning, early design exploration, congestion aware placement and optimization, clock tree synthesis, advanced node routing convergence, manufacturing compliance, and signoff closure.IC Compiler II is specifically architected to address aggressive performance, power, area (PPA), and time-to-market pressures of leading-edge designs. Key technologies include a pervasively parallel optimization framework, multi-objective global placement, routing driven placement optimization, full flow Arc based concurrent clock and data optimization, total power optimization, multi-pattern and FinFET aware flow and machine learning (ML) driven optimization for fast and predictive design closure. Advanced Fusion technologies offer signoff IR drop driven optimization, PrimeTime ® delay calculation within IC Compiler II, exhaustive path-based analysis (PBA) and signoff ECO within place and route for unmatched QoR and design convergence. F U S I O N D E S I G N P L A T F O R M PrimeTime, StarRC, PrimePower,IC Validator, RedHawk Analysis Fusion Fusion Compiler IC Compiler II Design Compiler NXT TestMAX F o r m a l i t y ECO Fusion S i g n o f f F u s i o n S i g n o f f F u s i o n Test Fusion Figure 1: IC Compiler II Anchor in Synopsys Design PlatformAccelerating DesignClosure on AdvancedDesignsIC Compiler II Industry Leading Place and Route SystemKey BenefitsProductivity• The highest capacity solution that supports 500M+ instances with a scalable and compact data model• A full suite of design planning features including transparent hierarchical optimization• Out-of-the-box simple reference methodology for easy setup• Multi-threaded and distributed computing for all major flow steps• Golden signoff accuracy with direct access to PrimeTime delay calculationPPA• Unified TNS driven optimization framework• Congestion, timing, and power-driven logic re-synthesis• IEEE 1801 UPF/multi-voltage support• Arc-based concurrent clock and data optimization• Global minima driven total power optimizationAdvanced Nodes• Multi-pattern and FinFET aware design flow• Next generation advanced 2D placement and legalization• Routing layer driven optimization, auto NDR, and via pillar optimization• Machine learning driven congestion prediction and DRC closure• Highest level of foundry support and certification for advanced process nodes• IC Validator in the loop signoff driven DRC validation and fixingAdvanced Fusion Technology• Physically aware logic re-synthesis• IR drop driven optimization during all major flow steps• PrimeTime delay calculation based routing optimization for golden accuracy• Integrated PrimeTime ECO flow during routing optimization for fastest turnaround timeEmpowering Design Across Diversified ApplicationsThe dizzying pace of innovation and highly diversified applications across the design spectrum is forcing a complete rethink of the place and route systems to design and implement differentiated designs in a highly competitive semiconductor market on schedule. Designers on emerging process nodes must meet aggressive PPA and productivity goals. It essentially means efficient and intelligent handling of 100s of millions of place-able instances, multiple levels of hierarchy, 1000s of hard macros, 100s of clocks, wide busses, and 10s of modes and corners power domains and complex design constraints and process technology mandates. Emphasis on Designer ProductivityIC Compiler II is architected from the ground up for speed and scalability. Its hierarchical data model consumes 2-3X less memory than conventional tools, boosting the limits of capacity to 500M placeable instances and beyond. Adaptive abstraction and on-the-fly data management minimize memory requirements and enable fast responsive data manipulation. Near-linear multi-core threading of key infrastructural components and core algorithms such as database access and timing analysis speed up optimization at all phases of design. Patented, lossless compact modeling and independent R and C extraction allow handling more modes and corners (MCMM scenarios) with minimal runtime impact.IC Compiler II has built-in Reference Methodology(RM) that ensures fast flow bring up. This RM Flow is Foundry Process/Design Type specific to ensure a robust starting point and seamless bring up. IC Compiler II has direct access to the Golden PrimeTime delay calculation engine to minimize ECO iterations.IC Compiler II’s new data model enables designers to perform fast exploration and floorplanning with complex layout requirements. IC Compiler II can create bus structures, handle designs with n-levels of physical hierarchy, and support Multiply Instantiated Blocks (MIBs) in addition to global route driven pin assignment/feedthrough flow, timing driven macro placement, MV area design planning.A design data mismatch inferencing engine analyzes the quality of inputs and drives construct creation on the fly, delivering design insights even with “incomplete” data early in the design cycle. Concurrent traversal of logical and physical data models enables hierarchical Data-Flow Analysis (DFA) and fast interactive analysis through multi-level design hierarchies and MIBs. Data flow and feedthrough paths highlighted in Figure 2 allow analysis and manipulation through n-levels of hierarchy to complete early design exploration and prototyping.Figure 2: Fast interactive analysis through multiple-levels of physical hierarchy and MIBPipeline-register-planning shown in Figure 3, provides guidance for optimal placement to meet the stringent timing requirementsof high-performance designs. Interactive route editor integrated which is advanced node aware shown in Figure 4, allows intricate editing and routing functions, including the creation of special signal routes, buses, etc.Figure 3: Pipeline register placement enables superior QoR for designs with complex busesAchieving Best Performance, Power, Area, and TATIC Compiler II features a new optimization framework built on global analytics. This Unified TNS Driven Optimization framework is shared with Design Compiler NXT synthesis to enable physically-aware synthesis, layer assignment, and route-based optimization for improved PPA and TAT. Multi-Corner Multi-Mode (MCMM) and Multi-Voltage (MV) aware, level-based analytical algorithms continuously optimize using parallel heuristic algorithms. Multi-factor costing functions deliver faster results on both broad and targeted design goals. Concurrent PPA driven logic remapping, rewiring, and legalization interleaved with placement minimizes congested logic, resulting in simple localized logic cones that maximize routability and QoR.IC Compiler II minimizes leakage with fast and efficient cell-by-cell power selection across HVT, SVT and LVT cells and varying channel lengths. Activity-driven power optimization uses VCD/ SAIF, net toggle rates, or probability functions to drive placement decisions and minimize pin capacitances. Multi-bit register banking optimizes clock tree structures, reduces area, and net length, while automatically managing clock, data, and scan chain connections.Advanced modeling of congestion across all layers highlighted in Figure 4 provides accurate feedback throughput the flow from design planning to post- route optimization.Figure 4: Intelligent and accurate analysis for congestion and powerIC Compiler II introduces a new Concurrent Clock and Data (CCD) analysis and optimization engine that is built-in to every flow step resulting in meeting both aggressive performance and minimizing total power footprint. ARC-based CCD optimization performs clock tree traversal across all modes/corners in path-based fashion to ensure optimal delay budgeting.Robust support for clock distribution enables virtually any clock style, including mesh, multi-source, or H-tree topologies. Advanced analysis and debugging features perform accurate clock QoR analysis and debugging as highlighted in Figure 5.Figure 5: Accurate clock QoR analysis and debugging (a & b) Abstracted clock graph and schematic.(c) Latency clock graph. (d) Colored clock tree in layout.IC Compiler II features many innovative technologies that make it the ideal choice for high-performance, energy-efficient Arm®processor core implementation, resulting in industry-best milliwatts/megahertz (mW/MHz) for mobile and other applications across the board. Synopsys and Arm work closely together to offer optimized implementation of popular Arm cores for IC Compiler II,with reference flows available for Arm Cortex®-A high-performance processors and Mali GPUs. In addition, Arm offers off-the-shelf Artisan® standard cell and memory models that have been optimally tuned and tested for fast deployment in an IC Compiler II environment. Continuous technology innovation and close collaboration makes IC Compiler II the leading choice for Arm-based high- performance design.Highest Level of Advanced Node Certification and SupportIC Compiler II provides advanced node design enablement across major foundries and technology nodes—including 16/14nm,12/10nm, 7/5nm, and sub-5nm geometries. Zroute digital router technology ensures early and full compliance with the latest design rules required for these advanced node technologies. Synopsys collaborates closely with all the leading foundries to ensure that IC Compiler II is the first to deliver support for early prototype design rules and support for the final production design rules. IC Compiler II design technologies maximize the benefits of new process technologies and offer optimal return on investment for cutting-edge silicon applications.IC Compiler II advanced node design support includes multi-pattern/FinFET aware placement and routing, Next-generation advanced 2D placement and legalization, routing layer driven optimization, auto NDR, and via pillar optimization. IC Validator in the loop provides signoff DRC feedback during Implementation.Foundry ﬁll Track based ﬁllFigure 6: IC Validator In-Design metal fill color aware metal fill, optimized for density and foundry requirementsMachine learning driven congestion prediction and DRC closure allow for fastest routing convergence with best PPA. Multiple sets of training data are used to extract key predictive elements that guide the pre-route flow.Advanced Fusion TechnologyThe Fusion Design Platform™ delivers unprecedented full-flow QoR and time-to-results (TTR) to accelerate the next wave of semiconductor industry innovation. The industry’s first AI-enhanced, cloud-ready Design Platform with Fusion Technology™ isbuilt from Synopsys’ market-leading, massively-parallel digital design tools, and augmented with innovative capabilities to tacklethe escalating challenges in cloud computing, automotive, mobile, and IoT market segments and accelerate the next wave of industry innovation.Fusion Technology redefines conventional EDA tool boundaries across synthesis, place-and-route, and signoff, sharing integrated engines across the industry’s premier digital design products. It enables designers to accelerate the delivery of their next-generation designs with the industry-best QoR and the TTR.©2019 Synopsys, Inc. All rights reserved. Synopsys is a trademark of Synopsys, Inc. in the United States and other countries. A list of Synopsys trademarks isavailable at /copyright.html . All other names mentioned herein are trademarks or registered trademarks of their respective owners.。

数据库系统概念(database system concepts)英文第六版第一章

n In the early days, database applications were built directly on top of file systems
Databa se Sy stem Concept s - 6th Edition
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n Relational model (Chapter 2) n Example of tabular data in the relational model Columns
_____ Rows
Databa se Sy stem Concept s - 6th Edition
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n Physical Data Independence – the ability to modify the physical schema without changing the logical schema l Applications depend on the logical schema l In general, the interfaces between the various levels and components should be well defined so that changes in some parts do not seriously influence others.
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n Phys ical level : describes how a record (e.g., customer) is stored. n Logical level : describes data stored in database, and the relationships among the data. type instructor = record ID : string;

FPGA名词概念

FPGA名词概念1、ASIC:application-specific integrated circuits专用集成电路是指应特定用户要求和特定电子系统的需要而设计、制造的集成电路。

ASIC分为全定制和半定制。

ASIC的特点是面向特定用户的需求，ASIC在批量生产时与通用集成电路相比具有体积更小、功耗更低、可靠性提高、性能提高、保密性增强、成本降低等优点。

全定制设计需要设计者完成所有电路的设计，因此需要大量人力物力，灵活性好但开发效率低下。

如果设计较为理想，全定制能够比半定制的ASIC芯片运行速度更快。

半定制使用库里的标准逻辑单元(Standard Cell)，设计时可以从标准逻辑单元库中选择SSI(门电路)、MSI(如加法器、比较器等)、数据通路(如ALU、存储器、总线等)、存储器甚至系统级模块(如乘法器、微控制器等)和IP核，这些逻辑单元已经布局完毕，而且设计得较为可靠，设计者可以较方便地完成系统设计。

2、ALU:arithmetic an logic unit算术逻辑单元是中央处理器(CPU)的执行单元，是所有中央处理器的核心组成部分，由“And Gate”（与门）和“Or Gate”（或门）构成的算术逻辑单元，主要功能是进行二位元的算术运算，如加减乘(不包括整数除法)。

基本上，在所有现代CPU体系结构中，二进制都以补码的形式来表示。

3、BCD:binary-coded decimal BCD码或二-十进制代码，亦称二进码十进数是一种二进制的数字编码形式，用二进制编码的十进制代码。

这种编码形式利用了四个位元来储存一个十进制的数码，使二进制和十进制之间的转换得以快捷的进行。

4、CLBs:configurable logic blocks可配置逻辑模块。

包含一个可配置开关矩阵，此矩阵有选型电路（多路复用器），触发器和4或6个输入组成。

在Xilinx公司的FPGA器件中，CLB由多个（一般为4个或2个）相同的slice和附加逻辑构成。

Granular Computing

Granular ComputingY.Y. YaoDepartment of Computer Science, University of ReginaRegina, Saskatchewan, Canada S4S 0A2E-mail: yyao@cs.uregina.ca, http://www.cs.uregina.ca/~yyaoAbstract The basic ideas and principles of granular computing (GrC) have been studied explicitly or implicitly in many fields in isolation. With the recent renewed and fast growing interest, it is time to extract the commonality from a diversity of fields and to study systematically and formally the domain independent principles of granular computing in a unified model. A framework of granular computing can be established by applying its own principles. We examine such a framework from two perspectives, granular computing as structured thinking and structured problem solving. From the philosophical perspective or the conceptual level, granular computing focuses on structured thinking based on multiple levels of granularity. The implementation of such a philosophy in the application level deals with structured problem solving.Keywords: Granularity, granule, level, hierarchy, structured thinking, structured problem solving1. IntroductionHuman problem solving involves the perception, abstraction, representation and understanding of real world problems, as well as their solutions, at different levels of granularity [4, 6, 23, 28, 32-35]. The consideration of granularity is motivated by the practical needs for simplification, clarity, low cost, approximation, and tolerance of uncertainty [32]. As an emerging field of study, granular computing attempts to formally investigate and model the family of granule-oriented problem solving methods and information processing paradigms [14, 23, 28].Ever since the introduction of the term of “Granular computing (GrC)” by T.Y. Lin in 1997 [8, 32], we have witnessed a rapid development of and a fast growing interest in the topic [2, 5, 8-10, 13, 14,16-20, 22-31, 33, 35, 37]. Many models and methodsof granular computing have been proposed and studied. From the wide spectrum of current research, one can easily make several observations. There does not exist a general agreement about what is granular computing, nor there is a unified model [36]. Many studies concentrate on concrete models in particular contexts, and hence only capture limited aspects of granular computing. Consequently, the potential applicability and usefulness of granular computing are not well perceived and appreciated.The studies of concrete models and methods are important for the development of a field in its early stage. It is equally important, if not more, to study a general theory that avoids constraints of a concrete model.The basic notions and principles of granular computing, though under different names, have in fact been appeared in many related fields, such as programming, artificial intelligence, divide and conquer, interval computing, quantization, data compression, chunking, cluster analysis, rough set theory, quotient space theory, belief functions, machine learning, databases, and many others [8, 23, 28, 32, 33]. However, granular computing has not been fully explored in its own right. It is time to extract the commonality from these diverse fields andto study systematically and formally the domain independent principles of granular computing in a unified and well-formulated framework.In this paper, we study high level and qualitative characteristics of a theory of granular computing. A general domain independent framework is presented,in which basic issues are examined.2. Perspectives of Granular ComputingIt may be difficult, if not impossible, to give a formal, precise and uncontroversial definition of granular computing. N evertheless, one can still extract the fundamental elements from the human problem solving experiences and methods. There are basic principles, techniques and methodologies that are commonly used in most types of problem solving. Granular computing, therefore, focuses on problem solving based on the commonsense concepts of granule, granulated view, granularity, and hierarchy. They are interpreted as the abstraction, generalization, clustering, levels of abstraction, levelsof detail, and so on in various domains. We view granular computing as a study of a general theory of problem solving based on different levels of granularity and detail [28].Granular computing can be studied by applying its principles and ideas. It can be investigated in different levels or perspectives by focusing on itsphilosophical foundations, basic components, fundamental issues, and general principles. The philosophical level concerns structured thinking, and the application level deals with principles of structured problem solving. While structured thinking provides guidelines and leads naturally to structured problem solving, structured problem solving implements the philosophy structured thinking.The philosophy of thinking in terms of levels of granularity, and its implementation in more concrete models, would result in disciplined procedures that help to avoid errors and to save time for solving a wide range of complex problems.3. Basic Components of Granular ComputingIn modeling granular computing, we focus on three basic components and their interactions.3.1. GranulesA granule may be interpreted as one of the numerous small particles forming a larger unit. Collectively, they provide a representation of the unit with respect to a particular level of granularity. That is, a granule may be considered as a localized view or a specific aspect of a large unit.Granules are regarded as the primitive notion of granular computing. Its physical meanings become clearer when dealing with more concrete models. For example, in set-theoretic setting, such as rough sets, quotient space theory and cluster analysis, a granule may be interpreted as a subset of a universal set [12, 13, 34, 35]. In planning, a granule can be a sub-plan [6]. In programming, a granule can be a program module [7]. For the conceptual formulation of granular computing, we do not attempt to interpret the notion of granules based on more intuitive, but rather restrictive, concepts. We focus on some fundamental issues based on this weak view of granules.The size of a granule is considered as a basic property. Intuitively, the size may be interpreted as the degree of abstraction, concreteness, or detail. In the set-theoretic setting, the size of a granule can be the cardinality of the granule.Connections and relationship between granules can be represented by binary relations. In concrete models, they may be interpreted as dependency, closeness, or overlapping. For example, based on the notion of size, one can define an order relation on granules. Depending on the particular context, the relation may be interpreted as “greater than or equal to”, “more abstract than”, or “coarser than”. The order relation may be reflexive and transitive, but not symmetric. The order relation is particularly useful in studying connections between granules in different levels.One can define operations on granules so that one can operate on granules, such as combining many granules to form a new granule or decomposing a granule into many granules. The operations on granules must be consistent with the binary relations on the granules. For example, the combined granule should be more abstract than its components. The sizes of granules, the relations between granules, and the operations on granules provide the essential ingredients for developing a theory of granular computing.3.2. Granulated views and levelsIn his work on vision, Marr convincingly made the point that a full understanding of an information processing system involves explanations at various levels [11]. The three levels considered are the computational, algorithmic, and implementational. The computational level describes the information processing problem to be solved by the system. The algorithmic level describes the steps that need to be carried out to solve the problem. The implementational level deals with physical realization of the system. Although there does exist a general agreement on the interpretations and the exact number of levels, it is commonly accepted that the notion of levels is an important one in computer science [3].Foster critically reviewed and systematically compared various definitions and interpretations of the notion of levels [3]. Three basic issues, namely, definition of levels, number of levels, and relationship between levels, are clarified. Levels are considered simply as descriptions or points of views and often for the purpose of explanation. The number of levels is not fixed, but depends on the context and the purpose of description or explanation.A multi-layered theory of levels captures two senses of abstraction. One is the abstraction in terms of concreteness and is represented by planes along the dimension from top to bottom. The other is the abstraction in terms of the amount of detail and can be modeled along another dimension from less detail to more detail on the same plane.By viewing a level as a description or a point of view, one can immediately apply it as a basic notion to model granular computing. In order to emphasize the context of granular computing, we also refer to a level as a granulated view. A level consists of entities called granules whose properties characterize and describe the subject matters of study, such as a real world problem, a theory, a design, a plan, a program, or an information processing system. Granules are formed with respect to a particular degree of granularity or detail. Granules in a level are defined and formed within a particular context and are related to granules in other levels.There are two types of information and knowledge encoded in a level. A granule captures a particular aspect, and collectively, all granules in the level provide a granulated view. The granularity of a level refers to the collective properties of granules in a level with respect to their sizes. The granularity is reflected by the sizes of all granules involved.3.3. HierarchiesGranules in different levels are linked by the order relations and operations on granules. The order relation on granules can be extended to granulated views (levels). A level is above another level if each granule in the former level is ordered before a granule in the latter level, and each granule in the latter level is ordered after a granule in the former level, under the order relation. The ordering of levels can be described by the notion of hierarchy.The theory of hierarchy provides a multi-layered framework based on levels. Mathematically, a hierarchy may be viewed as a partially ordered set [1]. For the study of granular computing, the elements of the ordered set are interpreted as hierarchical levels or granulated views. The ordering of levels in a hierarchy is based on criteria that are related to the order relations on granules. A higher level may provide a constraint to and/or context of a lower level, and may contain and be made of lower levels. Depending on the context, a hierarchy may consist of levels of interpretation, levels of abstraction, levels of organization, levels of observation, and levels of detail. A hierarchy represents relationships between different granulated views, and explicitly shows the structure of granulation.A granule in a higher level can be decomposed into many granules in a lower level, and conversely many granules in a lower level can be combined into one granule in a higher level. A granule in a lower level may be a more detailed description of a granule in a higher level with added information. In the other direction, a granule in a higher level is a coarse-grained description of a granule in a lower level by omitting irrelevant details.3.4. Granular structuresWith the introduction of the three components, one can examine three types of structures for modeling their interactions. They are the internal structure of a granule, the collective structure of the all granules (i.e., the internal structure of a granulated view or level), and the overall structure of all levels.Although a granule is normally considered as a whole instead of many sub-granules at a given level, its internal structure needs to be examined. The internal structure of a granule provides a proper description, interpretation, and characterization of the granule. A granule may have a complex structure itself. For examples, the internal structure of a granule may be a hierarchy consisting of many levels. The internal structure is also useful in establishing linkage among granules in different levels.All granules in a level may collectively show a certain structure. This is the internal structure of a granulated view. Granules in a level, although may be relatively independent, are somehow related to a certain degree. This stems from the fact that they together form a granulated view. On the other hand, it is expected that in many situations the relationships between different granules are much weaker. The internal structure of a level is only meaningful if all the granules in the level are considered together.A hierarchy represents the overall structure of all levels. In a hierarchy, both the internal structure of granule and the internal structure of granulated views are reflected, to some degree, by the order relations. In a hierarchy, not any two granulated views can be compared based on the order relation. In the special case, the hierarchy is a tree.The three structures as a whole is referred to as the granular structure. One can establish more connections between three structures. For example, granules in a higher level may have greater integrity and higher bond strength than those in a lower level. The structures need to be fully explored to establish a basis of granular computing.3.5. A partition modelThe three basic components of granular computing can be easily illustrated by a concrete model known as the partition model of granular computing [28], which is based on rough set theory [12, 13] and quotient space theory [34, 35].A central notion of the partition model is equivalence relations. In rough set theory, an equivalence relation on a set of objects can be concretely defined in an information table based on their values on a finite set of attributes [12, 31]. Two objects are equivalent if they have exact the same values on a set of attributes.An equivalence relation divides a universal set into a family of pair-wise disjoint subsets, called the partition of the universe. A granule of a partition model is therefore an equivalence class defined by an equivalence relation. The internal structure of an equivalence class is captured by the same values of some attributes. A granulated view is the partition induced by an equivalence relation, and its structure is defined by the properties of the partition. Different equivalence relations can be ordered based on set inclusion, which leads to a hierarchy of partitions. In an information table, we only consider partitions generated by different subsets of attributes. The overall hierarchical structure is therefore induced bysubsets of attributes.The partition model may be viewed as a special case of cluster analysis. Following the same argument, one can easily find the correspondence between basic components of granular computing and its structures in cluster analysis. In general, given any concrete model of granular computing, we can easily find the corresponding components and structures.4. Basic Issues of Granular ComputingThe discussions of this section summarize and extend the preliminary results reported in [23, 28]. The list of issues discussed should not be viewed as a complete one. It can only be viewed as a set of representatives. Based on the principles of granular computing, these issues may also be studied at different levels of detail.Granular computing may be studied based on two related issues, i.e., granulation and computation 23, 28]. The former deals with the construction, interpretation, and representation of the three basic components, and the latter deals with the computing and reasoning with granules and granular structures.Studies of granular computing cover two perspectives, namely, the algorithmic and the semantic [23, 28]. Algorithmic study concerns the procedures for constructing granules and related computation, and the semantic study concerns the interpretation and physical meaningfulness of various algorithms. Studies from both aspects are necessary and important. The results from semantic study may provide not only interpretations and justifications for a particular granular computing model, but also guidelines that prevent possible misuses of the model. The results from algorithmic study may lead to efficient and effective granular computing methods and tools.4.1. GranulationGranulation involves the construction of the three basic components, granules, granulated views and hierarchies. Two basic operations are the top-down decomposition of large granules to smaller granules, or the bottom-up combination of smaller granules into larger granules.The notion of granulation can be studied in many different contexts. The granulation of a problem, a theory, or a universe, particularly the semantics of granulation, is domain and application dependent. Nevertheless, one can still identify some domain independent issues. For clarity, some of these issues are discussed in the set-theoretic setting.In the set-theoretic setting, a granule may be viewed as a subset of the universe, which may be either fuzzy or crisp. A family of granules containingevery object in the universe is called a granulatedview of the universe. A granulated view may consistof a family of either disjoint or overlapping granules.There are many granulated views of the same universe. Different views of the universe can belinked together, and a hierarchy of granulated viewscan be established.Granulation criteria. A granulation criteriondeals with the semantic issues and addresses the question of why two objects are put into the same granule. It is domain specific and relies on the available knowledge. In many situations, objects are usually grouped together based on their relationships,such as indistinguishability, similarity, proximity, or functionality [32]. One needs to build models to provide both semantical and operational interpretations of these notions. They enable us to formally and precisely define various notions involved, and to systematically study the meaningsand rationale of a granulation criterion.Granulation methods. From the algorithmic aspect, a granulation method addresses the problemof how to put two objects into the same granule. It is necessary to develop algorithms for constructing granules and granulated views efficiently based on a granulation criterion.Representation/description. The next issue isthe interpretation of the results of a granulation method, i.e., the granular structures. Once constructed, it is necessary to describe, to name andto label granules using certain languages. One may assign a name to a granule such that an element in the granule is an instance of the named category. Onemay also provide a formal description of objects inthe same granule. By pooling the representations of granules, one can obtain the overall representation ofa granulated view.Qualitativ e and quantitativ e characterization.One can associate quantitative measures to the three components, granules, granulated views, and hierarchies. The measures should reflect and be consistent with the three structures, the internal structure of a granule, the collective structure of a granulated view, and the overall structure of a hierarchy.4.2. Computing with granulesComputing and reasoning with granules explorethe three types of structures. They can be similarly studied from both the semantic and algorithmic perspectives. One needs to design and interpret various methods based on the interpretation of granules and relationships between granules, as wellas to define and interpret operations of granular computing.Mappings. The connections between differentlevels of granulations can be described by mappings. At each level of the hierarchy, a problem is represented with respect to the granularity of the level. The mapping links different representations of the same problem at different levels of detail. In general, one can classify and study different types of granulations by focusing on the properties of the mappings.Granularity conversion. A basic task of granular computing is to change views with respect to different levels of granularity. As we move from one level of detail to another, we need to convert the representation of a problem accordingly. A move to a more detailed view may reveal information that otherwise cannot be seen, and a move to a simpler view can improve the high level understanding by omitting irrelevant details of the problem.Operators. Operators can precisely define the conversion of granularity in different levels. They serve as the basic building blocks of granular computing. There are at least two types of operators that can be defined. One type deals with the shift from a fine granularity to a coarse granularity. A characteristic of such an operator is that it will discard certain details, which makes distinct objects no longer differentiable. Depending on the context, many interpretations and definitions are available, such as abstraction, simplification, generalization, coarsening, zooming-out, and so on. The other type deals with the change from a coarse granularity to a fine granularity. A characteristic of such an operator is that it will provide more details, so that a group of objects can be further classified. They can be defined and interpreted differently, such as articulation, specification, expanding, refining, zooming-in, and so on.Property preservation. Granulation allows different representations of the same problem in different levels of detail. It is naturally expected that the same problem must be consistently represented. Granulation and its related computing methods are meaningful only if they preserve certain desired properties. For example, Zhang and Zhang studied the “false-preserving” property, which states that if a coarse-grained space has no solution for a problem then the original fine-grained space has no solution [34, 35]. Such a property can be explored to improve the efficiency of problem solving by eliminating a more detailed study in a coarse-grained space. One may require that the structure of a solution in a coarse-grained space is similar to the solution in a fine-grained space. Such a property is used in top-down problem solving techniques. More specifically, one starts with a sketched solution and successively refines it into a full solution. In the context of hierarchical planning, one may impose similar properties, such as upward solution property, downward solution property, monotonicity, etc. [6]. 4.3. The rough set modelAs an illustration, we discuss the basic issues of granular computing based on the results from the rough set theory. Many applications of the rough set theory are based on the exploration of those issues.Granulation. The granulation criterion is an equivalence relation on a set of objects, which is concretely defined in an information table based on the values of a set of attributes. The granulation method is simply the collection of equivalent objects. One associates a formula to each equivalence class, which provides a formal description of the equivalence class. One also associates quantitative measures to equivalence classes and the partition induced by the equivalence relation.Computing with granules. Many of the applications of rough set theory can be viewed as concrete examples of computing with granules. With respect to an information table, mappings between different granulated views are in fact defined by different subsets of attributes. The conversion of granularity is achieved by adding or deleting attributes. The rough set approximation operators are granularity conversion operators.An important application of rough set theory is to learn classification rules [12, 21]. One of the important steps is to find a reduct of attributes, i.e., a set of individually necessary and collectively sufficient attributes that provide the correct classification [12, 21]. Conceptually, this can be easily modeled as searching the partition hierarchy defined by all subsets of attributes. Even in this simple search process, we have to deal with the issues discussed earlier. The mappings between levels direct the search direction; granularity conversion and property preserving principles govern the quality of the searched granulated views, the operators can be used to define the quality of each decision rule.5. ConclusionBy explicitly introducing an umbrella term of granular computing, one can explore, organize and unify the divergent concepts, theories, and applications into a well-formulated and unified theory of problem solving. It is time to move from studies of particular methods and concrete models of granular computing to a more abstract level. One needs to study its basic philosophy and principles, and to build a more general framework. This paper may be viewed as a step toward this goal.Although this paper does not cover all aspects of a complete model of granular computing, the results are useful in building a concrete model in which one can examine specific techniques and issues of granular computing in the context of particularapplications.The notions of granules, granulated views (levels) and hierarchies are sufficient for us to discuss the basic issues of granular computing. The sizes of granules, the granular structures, and the operations on granules provide the essential ingredients for the development of a theory of granular computing. References1.Ahl, V. and Allen, T.F.H. (1996) Hierarchy Theory, aision, V ocabulary and Epistemology, Columbia University Press.2.Bargiela, A. and Pedrycz W. (2002) GranularComputing: an Introduction,Kluwer Academic Publishers, Boston.3.Foster, C.L. (1992) Algorithms, Abstraction andImplementation: Levels of Detail in Cognitive Science,Academic Press, London.4.Hobbs, J.R. (1985) Granularity, Proceedings of the 9thInternational Joint Conference on Artificial Intelligence, 432-435.5.Inuiguchi, M., Hirano, S. and Tsumoto, S. (Eds.)(2003) Rough Set Theory and Granular Computing,Springer, Berlin.6.Knoblock, C.A. (1993) Generating AbstractionHierarchies: an Automated Approach to ReducingSearch in Planning, Kluwer Academic Publishers,Boston.7.Ledgard, H.F., Gueras, J.F. and N agin, P.A. (1979)PASCAL with Style: Programming Proverbs, HaydenBook Company, Inc., Rechelle Park, New Jersey.8.Lin, T.Y. (1997) Granular computing, announcementof the BISC Special Interest Group on GranularComputing.9.Lin, T.Y. (2003) Granular computing, LN CS 2639,Springer, Berlin, 16-24.10.Lin, T.Y., Yao, Y.Y. and Zadeh, L.A. (Eds.) (2002)Data Mining, Rough Sets and Granular Computing,Physica-Verlag, Heidelberg.11.Marr, D. (1982) V ision: A ComputationalInvestigation into the Human Representation andProcessing of Visual Information, W.H. Freeman andCompany, New York.12.Pawlak, Z. (1991) Rough Sets, Theoretical Aspects ofReasoning about Data, Kluwer Academic Publishers,Dordrecht.13.Pawlak, Z. (1998) Granularity of knowledge,indiscernibility and rough sets, Proceedings of 1998IEEE International Conference on Fuzzy Systems,106-110.14.Pedrycz, W. (Ed.), 2001, Granular Computing: anEmerging Paradigm, Physica-Verlag, Heidelberg.15.Peikoff, L. (1981) Objectivism: the Philosophy of AynRand, Dutton, New York.16.Peters, J.F., Pawlak, Z. and Skowron, A. (2002) Arough set approach to measuring information granules,Proceedings of COMPSAC 2002, 1135-1139.17.Polkowski, L. and Skowron, A. (1998) Towardsadaptive calculus of granules, Proceedings of 1998IEEE International Conference on Fuzzy Systems,111-116.18.Skowron, A. (2001) Toward intelligent systems:calculi of information granules, Bulletin of International Rough Set Society, 5, 9-30.19.Skowron, A. and Stepaniuk, J. (2001) Informationgranules: towards foundations of granular computing,International Journal of Intelligent Systems, 16, 57-85.20.Wang, G., Liu, Q., Yao, Y.Y. and Skowron, A. (Eds.)(2003) Rough Sets, Fuzzy Sets, Data Mining, andGranular Computing, LNCS 2639, Springer, Berlin. 21.Wang, J. (2002), Rough sets and their applications indata mining, in: Fuzzy Logic and Soft Computing,Chen, G., Ying, M. and Cai, K.-Y. (Eds.), KluwerAcademic Publishers, Boston.22.Yao, Y.Y., (1999) Granular computing usingneighborhood systems, in: Advances in Soft Computing: Engineering Design and Manufacturing,Roy, R., Furuhashi, T., and Chawdhry, P.K. (Eds),Springer-Verlag, London, 539-553.23.Yao, Y.Y. (2000) Granular computing: basic issuesand possible solutions, Proceedings of the 5th JointConference on Information Sciences, 186-189.24.Yao, Y.Y. (2001) Information granulation and roughset approximation, International Journal of IntelligentSystems, 16, 87-104.25.Yao, Y.Y. (2001) Modeling data mining with granularcomputing, Proceedings of COMPSAC 2001, 638-643.26.Yao, Y.Y. (2003) Information granulation andapproximation in a decision-theoretical model of rough sets, in: Rough-Neural Computing: Techniquesfor Computing with Words, Pal, S.K., Polkowski, L.,and Skowron, A. (Eds), Springer, Berlin, 491-518.27.Yao, Y.Y. (2003) Granular computing for the designof information retrieval support systems, in: Information Retrieval and Clustering, Wu, W., Xiong,H. and Shekhar, S. (Eds.), Kluwer AcademicPublishers 299.28.Yao, Y.Y. (2004) A partition model of granularcomputing, LNCS Transactions on Rough Sets, toappear.29.Yao, Y.Y. and Liau, C.-J. (2002) A generalizeddecision logic language for granular computing, Proceedings of FUZZ-IEEE'02, 1092-1097.30.Yao, Y.Y., Liau, C.-J. and Zhong, N. (2003) Granularcomputing based on rough sets, quotient space theory,and belief functions, Proceedings of ISMIS'03, 152-159.31.Yao, Y.Y. and Zhong, N. (2002) Granular computingusing information tables, in: Data Mining, Rough Setsand Granular Computing, Lin, T.Y., Yao, Y.Y. andZadeh, L.A. (Eds.), Physica-Verlag, Heidelberg, 102-124.32.Zadeh, L.A. (1997) Towards a theory of fuzzyinformation granulation and its centrality in humanreasoning and fuzzy logic, Fuzzy Sets and Systems, 19,111-127.33.Zadeh, L.A. (1998) Some reflections on softcomputing, granular computing and their roles in theconception, design and utilization of information/ intelligent systems, Soft Computing, 2, 23-25.34.Zhang, B. and Zhang, L. (1992) Theory andApplications of Problem Solving, N orth-Holland, Amsterdam.35.Zhang, L. and Zhang, B. (2003) The quotient spacetheory of problem solving, LNCS 2639, 11-15.36.Zhao, M. (2004) Data Description based on RuductTheory, Ph.D. Dissertation, Institute of Automation,Chinese Academy of Sciences.37.Zhong, N., Skowron, A. and Ohsuga S. (Eds.) (1999)New Directions in Rough Sets, Data Mining, andGranular-Soft Computing, LN AI 1711, Springer,。

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bus specific features
• typedef generic_payload • Define new payload • Define new phases
Implementation Example
OCP-IP Modelling Kit • Support for advanced communication
protocols at various abstraction levels
– Built on top of TLM2.0 – Payload extensions – Phase extensions – Master Sockets with memory management for
– Compatible with OSCI BP wherever possible
Terminologies ..
OSCI TLM2.0 • Provides generic framework for memory
mapped busses • Defines a Base protocol • Provides infrastructure for extending base
IntБайду номын сангаасoduction
• SoC Modelling: Software model / Executable representation of SoC
• Various use cases
– Functional verification – Early s/w development – HW/SW partitioning, resource sharing – Architecture Exploration – Verify memory and bus designs – Cycle accurate h/w models
Implementation
• By extending OSCI TLM2.0
– blocking and non_blocking transport APIs – blocking can use wait, temporal decoupling – non_blocking uses phases and PEQs – Extend protocol for lower abstraction levels or
abstractions
Terminologies ..
Popular Terminology • Programmer's View: functional correct, fast
models for embedded software development • Architect's View: explore design features like
Abstraction Levels
• Required to cater to different use-cases • Control amount and frequency of
communication • Control simulation speed and accuracy • SystemC signal: RTL • TLM2.0 (Payload / Phases): Higher
BusSignal
Terminologies ..
Source: STARC TL Guideline, 2nd Edition
Terminologies ..
Terminologies ..
Mapping UseCases
Source: STARC TL Guideline, 2nd Edition
– TL2/TL3: approximate timed modelling, fewer extensions and phases
– TL4: loosely timed modelling, phases are not used, blocking transport mechanism is used
bus-width, memory organization, die-area etc • Verification View: cycle-accurate modelling,
simulate actual timing and memory requirements, closest to RTL
Terminologies ..
OCP-IP modelling kit • Introduces four levels
– TL1: cycle accurate modelling, supports all dataflow signals of OCP through extensions and phases
Puneet Arora ESCUG, 09 Abstraction Levels in SoC Modelling
Agenda
• Introduction • Abstraction levels • Terminologies • Implementation • Implementation Example • Adaptors • Conclusion and References
define abstraction levels • Combines points on these axis to define
Abstraction levels • Timing : UnTimed, ApproximatelyTimed,
CycleAccurate • Data : TRansaction, BusPhase, BusCycle,
protocol to model at different abstraction levels • Recommends two coding styles • Abstraction levels not well defined
Terminologies ..
STARC TLM Guideline • Uses timing and data granularity axis to