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Wiseguyreports.Com Adds “EDA Software -Market Demand, Growth, Opportunities and analysis of Top Key Player Forecast to 2021” To Its Research Database This report studies sales (consumption) of EDA Software in Global market, especially in United States, China, Europe, Japan, focuses on top players in these regions/countries, with sales, price, revenue and market share for each player in these regions, covering Market Segment by Regions, this report splits Global into several key Regions, with sales (consumption), revenue, market share and growth rate of EDA Software in these regions, from 2011 to 2021 (forecast), like United States China Europe Japan Split by product Types, with sales, revenue, price and gross margin, market share and growth rate of each type, can be divided into Electronic Circuit Design and Simulation Tool PCB Software IC Design Software PLD Design Tools Other EDA Software Split by applications, this report focuses on sales, market share and growth rate of EDA Software in each application, can be divided into Application 1 Application 2 Application 3 Global EDA Software Sales Market Report 2016 1 EDA Software Overview 1.1 Product Overview and Scope of EDA Software 1.2 Classification of EDA Software 1.2.1 Electronic Circuit Design and Simulation Tool 1.2.2 PCB Software 1.2.3 IC Design Software 1.2.4 PLD Design Tools 1.2.5 Other EDA Software 1.3 Application of EDA Software 1.3.1 Application 1 1.3.2 Application 2 1.3.3 Application 3 1.4 EDA Software Market by Regions 1.4.1 United States Status and Prospect (2011-2021) 1.4.2 China Status and Prospect (2011-2021) 1.4.3 Europe Status and Prospect (2011-2021) 1.4.4 Japan Status and Prospect (2011-2021) 1.5 Global Market Size (Value and Volume) of EDA Software (2011-2021) 1.5.1 Global EDA Software Sales and Growth Rate (2011-2021) 1.5.2 Global EDA Software Revenue and Growth Rate (2011-2021) 7 Global EDA Software Manufacturers Analysis 7.1 Cadence (USA) 7.1.1 Company Basic Information, Manufacturing Base and Competitors 7.1.2 EDA Software Product Type, Application and Specification 7.1.2.1 Type I 7.1.2.2 Type II 7.1.3 Cadence (USA) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.1.4 Main Business/Business Overview 7.2 Mentor Graphics?USA? 7.2.1 Company Basic Information, Manufacturing Base and Competitors 7.2.2 111 Product Type, Application and Specification 7.2.2.1 Type I 7.2.2.2 Type II 7.2.3 Mentor Graphics?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.2.4 Main Business/Business Overview 7.3 ALTIUM?Australia? 7.3.1 Company Basic Information, Manufacturing Base and Competitors 7.3.2 136 Product Type, Application and Specification 7.3.2.1 Type I 7.3.2.2 Type II 7.3.3 ALTIUM?Australia? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.3.4 Main Business/Business Overview 7.4 ZUKEN?Japan? 7.4.1 Company Basic Information, Manufacturing Base and Competitors 7.4.2 Nov Product Type, Application and Specification 7.4.2.1 Type I 7.4.2.2 Type II 7.4.3 ZUKEN?Japan? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.4.4 Main Business/Business Overview 7.5 Synopsys?USA? 7.5.1 Company Basic Information, Manufacturing Base and Competitors 7.5.2 Product Type, Application and Specification 7.5.2.1 Type I 7.5.2.2 Type II 7.5.3 Synopsys?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.5.4 Main Business/Business Overview 7.6 Magma Design Automation?USA? 7.6.1 Company Basic Information, Manufacturing Base and Competitors 7.6.2 Million USD Product Type, Application and Specification 7.6.2.1 Type I 7.6.2.2 Type II 7.6.3 Magma Design Automation?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.6.4 Main Business/Business Overview 7.7 Agilent EEsof?USA? 7.7.1 Company Basic Information, Manufacturing Base and Competitors 7.7.2 Software Product Type, Application and Specification 7.7.2.1 Type I 7.7.2.2 Type II 7.7.3 Agilent EEsof?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.7.4 Main Business/Business Overview 7.8 SpringSoft?China Taiwan? 7.8.1 Company Basic Information, Manufacturing Base and Competitors 7.8.2 Product Type, Application and Specification 7.8.2.1 Type I 7.8.2.2 Type II 7.8.3 SpringSoft?China Taiwan? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.8.4 Main Business/Business Overview 7.9 ANSYS?USA? 7.9.1 Company Basic Information, Manufacturing Base and Competitors 7.9.2 Product Type, Application and Specification 7.9.2.1 Type I 7.9.2.2 Type II 7.9.3 ANSYS?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.9.4 Main Business/Business Overview 7.10 Apache Design Solutions?USA? 7.10.1 Company Basic Information, Manufacturing Base and Competitors 7.10.2 Product Type, Application and Specification 7.10.2.1 Type I 7.10.2.2 Type II 7.10.3 Apache Design Solutions?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.10.4 Main Business/Business Overview 7.11 Applied Wave Research?USA? 7.12 Vennsa Technologies?Canada? 7.13 CIDC?China?


News Article | November 18, 2016
Site: marketersmedia.com

Wiseguyreports.Com Adds “EDA Software -Market Demand, Growth, Opportunities and analysis of Top Key Player Forecast to 2021” To Its Research Database This report studies sales (consumption) of EDA Software in Global market, especially in United States, China, Europe, Japan, focuses on top players in these regions/countries, with sales, price, revenue and market share for each player in these regions, covering Market Segment by Regions, this report splits Global into several key Regions, with sales (consumption), revenue, market share and growth rate of EDA Software in these regions, from 2011 to 2021 (forecast), like United States China Europe Japan Split by product Types, with sales, revenue, price and gross margin, market share and growth rate of each type, can be divided into Electronic Circuit Design and Simulation Tool PCB Software IC Design Software PLD Design Tools Other EDA Software Split by applications, this report focuses on sales, market share and growth rate of EDA Software in each application, can be divided into Application 1 Application 2 Application 3 Global EDA Software Sales Market Report 2016 1 EDA Software Overview 1.1 Product Overview and Scope of EDA Software 1.2 Classification of EDA Software 1.2.1 Electronic Circuit Design and Simulation Tool 1.2.2 PCB Software 1.2.3 IC Design Software 1.2.4 PLD Design Tools 1.2.5 Other EDA Software 1.3 Application of EDA Software 1.3.1 Application 1 1.3.2 Application 2 1.3.3 Application 3 1.4 EDA Software Market by Regions 1.4.1 United States Status and Prospect (2011-2021) 1.4.2 China Status and Prospect (2011-2021) 1.4.3 Europe Status and Prospect (2011-2021) 1.4.4 Japan Status and Prospect (2011-2021) 1.5 Global Market Size (Value and Volume) of EDA Software (2011-2021) 1.5.1 Global EDA Software Sales and Growth Rate (2011-2021) 1.5.2 Global EDA Software Revenue and Growth Rate (2011-2021) 7 Global EDA Software Manufacturers Analysis 7.1 Cadence (USA) 7.1.1 Company Basic Information, Manufacturing Base and Competitors 7.1.2 EDA Software Product Type, Application and Specification 7.1.2.1 Type I 7.1.2.2 Type II 7.1.3 Cadence (USA) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.1.4 Main Business/Business Overview 7.2 Mentor Graphics(USA) 7.2.1 Company Basic Information, Manufacturing Base and Competitors 7.2.2 111 Product Type, Application and Specification 7.2.2.1 Type I 7.2.2.2 Type II 7.2.3 Mentor Graphics(USA) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.2.4 Main Business/Business Overview 7.3 ALTIUM(Australia) 7.3.1 Company Basic Information, Manufacturing Base and Competitors 7.3.2 136 Product Type, Application and Specification 7.3.2.1 Type I 7.3.2.2 Type II 7.3.3 ALTIUM(Australia) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.3.4 Main Business/Business Overview 7.4 ZUKEN(Japan) 7.4.1 Company Basic Information, Manufacturing Base and Competitors 7.4.2 Nov Product Type, Application and Specification 7.4.2.1 Type I 7.4.2.2 Type II 7.4.3 ZUKEN(Japan) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.4.4 Main Business/Business Overview 7.5 Synopsys(USA) 7.5.1 Company Basic Information, Manufacturing Base and Competitors 7.5.2 Product Type, Application and Specification 7.5.2.1 Type I 7.5.2.2 Type II 7.5.3 Synopsys(USA) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.5.4 Main Business/Business Overview 7.6 Magma Design Automation(USA) 7.6.1 Company Basic Information, Manufacturing Base and Competitors 7.6.2 Million USD Product Type, Application and Specification 7.6.2.1 Type I 7.6.2.2 Type II 7.6.3 Magma Design Automation(USA) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.6.4 Main Business/Business Overview 7.7 Agilent EEsof(USA) 7.7.1 Company Basic Information, Manufacturing Base and Competitors 7.7.2 Software Product Type, Application and Specification 7.7.2.1 Type I 7.7.2.2 Type II 7.7.3 Agilent EEsof(USA) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.7.4 Main Business/Business Overview 7.8 SpringSoft(China Taiwan) 7.8.1 Company Basic Information, Manufacturing Base and Competitors 7.8.2 Product Type, Application and Specification 7.8.2.1 Type I 7.8.2.2 Type II 7.8.3 SpringSoft(China Taiwan) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.8.4 Main Business/Business Overview 7.9 ANSYS(USA) 7.9.1 Company Basic Information, Manufacturing Base and Competitors 7.9.2 Product Type, Application and Specification 7.9.2.1 Type I 7.9.2.2 Type II 7.9.3 ANSYS(USA) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.9.4 Main Business/Business Overview 7.10 Apache Design Solutions(USA) 7.10.1 Company Basic Information, Manufacturing Base and Competitors 7.10.2 Product Type, Application and Specification 7.10.2.1 Type I 7.10.2.2 Type II 7.10.3 Apache Design Solutions(USA) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.10.4 Main Business/Business Overview 7.11 Applied Wave Research(USA) 7.12 Vennsa Technologies(Canada) 7.13 CIDC(China) For more information, please visit https://www.wiseguyreports.com/sample-request/747637-global-eda-software-sales-market-report-2016


Wiseguyreports.Com Adds “EDA Software -Market Demand, Growth, Opportunities and analysis of Top Key Player Forecast to 2021” To Its Research Database This report studies sales (consumption) of EDA Software in Global market, especially in United States, China, Europe, Japan, focuses on top players in these regions/countries, with sales, price, revenue and market share for each player in these regions, covering Market Segment by Regions, this report splits Global into several key Regions, with sales (consumption), revenue, market share and growth rate of EDA Software in these regions, from 2011 to 2021 (forecast), like United States China Europe Japan Split by product Types, with sales, revenue, price and gross margin, market share and growth rate of each type, can be divided into Electronic Circuit Design and Simulation Tool PCB Software IC Design Software PLD Design Tools Other EDA Software Split by applications, this report focuses on sales, market share and growth rate of EDA Software in each application, can be divided into Application 1 Application 2 Application 3 Global EDA Software Sales Market Report 2016 1 EDA Software Overview 1.1 Product Overview and Scope of EDA Software 1.2 Classification of EDA Software 1.2.1 Electronic Circuit Design and Simulation Tool 1.2.2 PCB Software 1.2.3 IC Design Software 1.2.4 PLD Design Tools 1.2.5 Other EDA Software 1.3 Application of EDA Software 1.3.1 Application 1 1.3.2 Application 2 1.3.3 Application 3 1.4 EDA Software Market by Regions 1.4.1 United States Status and Prospect (2011-2021) 1.4.2 China Status and Prospect (2011-2021) 1.4.3 Europe Status and Prospect (2011-2021) 1.4.4 Japan Status and Prospect (2011-2021) 1.5 Global Market Size (Value and Volume) of EDA Software (2011-2021) 1.5.1 Global EDA Software Sales and Growth Rate (2011-2021) 1.5.2 Global EDA Software Revenue and Growth Rate (2011-2021) 7 Global EDA Software Manufacturers Analysis 7.1 Cadence (USA) 7.1.1 Company Basic Information, Manufacturing Base and Competitors 7.1.2 EDA Software Product Type, Application and Specification 7.1.2.1 Type I 7.1.2.2 Type II 7.1.3 Cadence (USA) EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.1.4 Main Business/Business Overview 7.2 Mentor Graphics?USA? 7.2.1 Company Basic Information, Manufacturing Base and Competitors 7.2.2 111 Product Type, Application and Specification 7.2.2.1 Type I 7.2.2.2 Type II 7.2.3 Mentor Graphics?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.2.4 Main Business/Business Overview 7.3 ALTIUM?Australia? 7.3.1 Company Basic Information, Manufacturing Base and Competitors 7.3.2 136 Product Type, Application and Specification 7.3.2.1 Type I 7.3.2.2 Type II 7.3.3 ALTIUM?Australia? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.3.4 Main Business/Business Overview 7.4 ZUKEN?Japan? 7.4.1 Company Basic Information, Manufacturing Base and Competitors 7.4.2 Nov Product Type, Application and Specification 7.4.2.1 Type I 7.4.2.2 Type II 7.4.3 ZUKEN?Japan? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.4.4 Main Business/Business Overview 7.5 Synopsys?USA? 7.5.1 Company Basic Information, Manufacturing Base and Competitors 7.5.2 Product Type, Application and Specification 7.5.2.1 Type I 7.5.2.2 Type II 7.5.3 Synopsys?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.5.4 Main Business/Business Overview 7.6 Magma Design Automation?USA? 7.6.1 Company Basic Information, Manufacturing Base and Competitors 7.6.2 Million USD Product Type, Application and Specification 7.6.2.1 Type I 7.6.2.2 Type II 7.6.3 Magma Design Automation?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.6.4 Main Business/Business Overview 7.7 Agilent EEsof?USA? 7.7.1 Company Basic Information, Manufacturing Base and Competitors 7.7.2 Software Product Type, Application and Specification 7.7.2.1 Type I 7.7.2.2 Type II 7.7.3 Agilent EEsof?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.7.4 Main Business/Business Overview 7.8 SpringSoft?China Taiwan? 7.8.1 Company Basic Information, Manufacturing Base and Competitors 7.8.2 Product Type, Application and Specification 7.8.2.1 Type I 7.8.2.2 Type II 7.8.3 SpringSoft?China Taiwan? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.8.4 Main Business/Business Overview 7.9 ANSYS?USA? 7.9.1 Company Basic Information, Manufacturing Base and Competitors 7.9.2 Product Type, Application and Specification 7.9.2.1 Type I 7.9.2.2 Type II 7.9.3 ANSYS?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.9.4 Main Business/Business Overview 7.10 Apache Design Solutions?USA? 7.10.1 Company Basic Information, Manufacturing Base and Competitors 7.10.2 Product Type, Application and Specification 7.10.2.1 Type I 7.10.2.2 Type II 7.10.3 Apache Design Solutions?USA? EDA Software Sales, Revenue, Price and Gross Margin (2011-2016) 7.10.4 Main Business/Business Overview 7.11 Applied Wave Research?USA? 7.12 Vennsa Technologies?Canada? 7.13 CIDC?China?


Chen Y.,Vennsa Technologies | Safarpour S.,Vennsa Technologies | Marques-Silva J.,University College Dublin | Veneris A.,University of Toronto
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems | Year: 2010

As contemporary very large scale integration designs grow in complexity, design debugging has rapidly established itself as one of the largest bottlenecks in the design cycle today. Automated debug solutions such as those based on Boolean satisfiability (SAT) enable engineers to reduce the debug effort by localizing possible error sources in the design. Unfortunately, adaptation of these techniques to industrial designs is still limited by the performance and capacity of the underlying engines. This paper presents a novel formulation of the debugging problem using MaxSAT to improve the performance and applicability of automated debuggers. Our technique not only identifies errors in the design but also indicates when the bug is excited in the error trace. MaxSAT allows for a simpler formulation of the debugging problem, reducing the problem size by 80% compared to a conventional SAT-based technique. Empirical results demonstrate the effectiveness of the proposed formulation as run-time improvements of 4.5 × are observed on average. This paper introduces two performance improvements to further reduce the time required to find all error sources within the design by an order of magnitude. © 2006 IEEE.


Keng B.,University of Toronto | Safarpour S.,Vennsa Technologies | Veneris A.,University of Toronto
Proceedings -Design, Automation and Test in Europe, DATE | Year: 2011

In the last decade, functional verification has become a major bottleneck in the design flow. To relieve this growing burden, assertion-based verification has gained popularity as a means to increase the quality and efficiency of verification. Although robust, the adoption of assertion-based verification poses new challenges to debugging due to presence of errors in the assertions. These unique challenges necessitate a departure from past automated circuit debugging techniques which are shown to be ineffective. In this work, we present a methodology, mutation model and additional techniques to debug errors in SystemVerilog assertions. The methodology uses the failing assertion, counterexample and mutation model to produce alternative properties that are verified against the design. These properties serve as a basis for possible corrections. They also provide insight into the design behavior and the failing assertion. Experimental results show that this process is effective in finding high quality alternative assertions for all empirical instances. © 2011 EDAA.


Keng B.,University of Toronto | Safarpour S.,Vennsa Technologies | Veneris A.,University of Toronto
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems | Year: 2010

Design debugging is a major bottleneck in modern very large scale integration design flows as both the design size and the length of the error trace contribute to its inherent complexity. With typical design blocks exceeding half a million synthesized logic gates and error traces in the thousands of clock cycles, the complexity of the debugging problem poses a great challenge to automated debugging techniques. This paper aims to address this daunting challenge by introducing the bounded model debugging methodology that iteratively analyzes bounded sequences of the error trace. Two techniques are introduced in this methodology to solve this growing problem. The first technique iteratively analyzes bounded subsequences of the error trace of increasing size until the error is found or the entire trace is analyzed. The second technique partitions the error trace into non-overlapping bounded sequences of clock cycles which are each separately analyzed. A discussion of these two techniques is presented and a unified methodology that leverages the strengths of both techniques is developed. Empirical results on real industrial designs show that for large designs and long error traces the proposed methodology can find the actual error in 79% of cases with the first technique and 100% of cases with the second technique. In cases where the methodology is not used only 21% of cases are able to find the actual error. These numbers confirm the benefits of the proposed methodology to allow conventional automated debuggers to handle much larger real-life circuits. © 2006 IEEE.


Yang Y.-S.,Vennsa Technologies | Veneris A.,University of Toronto | Nicolici N.,McMaster University
IEEE Transactions on Very Large Scale Integration (VLSI) Systems | Year: 2012

With the growing size of modern designs and more strict time-to-market constraints, design errors can unavoidably escape pre-silicon verification and reside in silicon prototypes. Due to those errors and faults in the fabrication process, silicon debug has become a necessary step in the digital integrated circuit design flow. Embedded hardware blocks, such as scan chains and trace buffers, provide a means to acquire data of internal signals in real time for debugging. However, the amount of the data is limited compared to pre-silicon debugging. This paper presents an automated software solution to analyze this sparse data to detect suspects of the failure in both the spatial and temporal domain. It also introduces a technique to automate the configuration process for trace-buffer-based hardware in order to acquire helpful information for debugging the failure. The technique takes the hardware constraints into account and identifies alternatives for signals not part of the traceable set so that their values can be restored by implications. The experiments demonstrate the effectiveness of the proposed software solution in terms of run-time and resolution. © 2012 IEEE.


Veneris A.,University of Toronto | Keng B.,University of Toronto | Safarpour S.,Vennsa Technologies
Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC | Year: 2011

Computer-aided design tools are continuously improving their scalability and efficiency to mitigate the high cost associated with designing and fabricating modern VLSI systems. A key step in the design process is the root-cause analysis of detected errors. Debugging may take months to close, introduce high cost and uncertainty ultimately jeopardizing the chip release date. This study makes the case for debug automation in each part of the design flow (RTL to silicon) to bridge the gap. Contemporary research, challenges and future directions motivate for the urgent need in automation to relieve the pain from this highly manual task. ©2011 IEEE.


Safarpour S.,Vennsa Technologies | Veneris A.,University of Toronto | Najm F.,University of Toronto
Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC | Year: 2010

Managing long verification error traces is one of the key challenges of automated debugging engines. Today, debuggers rely on the iterative logic array to model sequential behavior which drastically limits their application. This work presents Bounded Model Debugging, an iterative, systematic and practical methodology to allow debuggers to tackle larger problems than previously possible. Based on the empirical observation that errors are excited in temporal proximity of the observed failures, we present a framework that improves performance by up to two orders of magnitude and solve 2.7x more problems than a conventional debugger.


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