Tech Explainer -- Clear, Confident, Intelligent, Relatable, Informative



Explainer for Cadence Computational Software. Informative, confident, intelligent, relatable, real person.

Vocal Characteristics



Voice Age

Middle Aged (35-54)


North American (General)


Note: Transcripts are generated using speech recognition software and may contain errors.
at Cadence. We empower engineers at world leading semiconductor and systems companies to create intelligent and highly differentiated Elektronik products that rely on the most advanced semiconductor devices, from consumer products like mobile devices and autonomous driving to next generation hyper scale computing. The technologies of the future will be integral in our lives and intelligently connected Elektronik design Automation e. D. A. Has always been in the forefront of breakthrough design. Driven by advanced computational software, the bedrock of what cadence delivers with the explosion of big data and massive computational workloads, it's more important than ever toe leverage proven software computational in nature that includes best in class design, verification I P and system analysis capabilities. Recent advancements in silicon design and computational software address These design challenges head on with an intelligent dimension. The different centers on select he innovations integration and co mingling of previously independent design analysis and implementation to achieve optimal results. Partitioning and scaling of computation to thousands of CPU cores and servers, and the introduction of machine learning to improve and harness design heuristics for system optimization. Today, most large system on chips are designed at the RTL level using System C C or C plus plus as the programming language with high level synthesis and various forms of verification from simulation, toe emulation and formal. These enable designers to create and debug designs and automate the process of transforming the high level descriptions toe low level implementation required for manufacturing. To counter the growth in design, size, complexity and computational scope, algorithms now utilize multiple CPU course. This approach enables early software development and system debugging analysis and modeling before the chip is manufactured. Another key facet of computational software is at the system level. The complexity of systems requires co design and co optimization of the semiconductor. With its icy package, PCBs, connectors and cables, multi physics simulation is now a necessity for system design. One example is high speed data communications, which have data rates up to 112 gigabits per second that require analysis tools connected to those environments to deliver automated selection of optimal system implementation decisions. Design tools and designers often apply recipes or ordered sets of steps when applying computational algorithms to their design challenge. Machine learning is particularly good at large scale pattern based algorithms and is implemented with the same matrix analysis technology found in E. D. A and system analysis. By evaluating and learning from successful prior designs, Cadence tools can evaluate thousands of possibilities, and the best outcome could be selected by focusing on the system level requirements and employing machine learning. To optimize decision making cadences. Computational software know how gives engineers the ability to create the intelligent Elektronik technologies of tomorrow Cadence Computational software for intelligence system design.