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As the chip design market continues to drive demand for greater functionality, bandwidth, and performance, semiconductor businesses race to create integrated circuits with as much capability as possible. For this reason, development in the semiconductor industry now requires competitors to reduce their chip design time and enter the market with advanced functionality and performance.

Companies find themselves on an endless complexity vs. productivity treadmill where chip complexity increases faster than productivity. This is driven by a mix of customer demand and companies trying to implement more functionality through larger development teams. However, by enhancing product development productivity, companies can achieve:

  • Faster time-to-market
  • On-time scheduled performance
  • Competitive development costs

To break the cycle where productivity chases complexity, world-class development capabilities with leading-edge R&D analytics environments are necessary. Additionally, to close the chip design time gap, companies will need to utilize embedded software development capabilities, strategic IP licensing, AI and machine learning, and high-performance compute enabled by the cloud.


Recent Trends in the Semiconductor Industry to Reduce Chip Design Time

Today, semiconductor companies are gaining a competitive advantage through their product development, rather than manufacturing, capabilities. Many chip makers that were once vertically integrated are now getting rid of their fabs and outsourcing fabrication. As fab costs soar, fewer companies can afford the investment, resulting in fabless organizations. Consequently, product-development productivity has become the primary aspect of development time. However, as we’ve discussed, productivity is hard-pressed to keep pace with the ever-growing circuit complexity. Successful semiconductor companies must develop capabilities to narrow the gap between complexity and productivity without increasing team size.

Semiconductor companies often suffer from imbalances between R&D capacity and product development requirements. In utilizing predictive analytics for resource planning and schedule estimation, companies can more reliably match team size to complexity to ensure good utilization of resources and faster development time. Advanced analytics and processes can help teams identify product-development bottlenecks and increase efficiency.

Another method companies use to improve R&D initiatives is by shifting from hardware to embedded software for functionality implementations. Only the most high-performance demanding functions utilize custom hardware. For all other functions, embedded software offers significant cost savings. Furthermore, enhancements and upgrades can be implemented more frequently and less expensively than in hardware. Software developers are also more readily available and cost-effective than IC engineers. Additionally, products utilizing software interfaces are more easily integrated into customer environments, increasing their appeal.

The most time-consuming phases of chip design involve designing, verifying, and validating designs, especially with the increase in SOC devices. For this reason, more and more companies turn to IP cores in the chip design process. By using third-party logic, circuit blocks, and processor cores, companies can speed up development. In cases where a complex circuit block must be implemented, the team can use IP cores to save time and reduce development costs.


Utilizing Cloud Resources to Speed Up Chip Design Time

Interestingly, some of the pressures necessitating faster design times may also provide the solutions. Specifically, cloud-based high-performance computing (HPC) and big data applications constantly require stronger and more efficient chips for increased functionality. Likewise, AI and machine learning applications require high-bandwidth and high-density multi-port memories to consolidate and analyze data from a variety of sources.

At the same time, these elements that demand more from chip design can also help reduce chip design time. AI and Machine learning technologies increasingly are used to assist in faster chip development. In addition, HPC capabilities can accelerate chip validation and design, further reducing time-to-market.


Synopsys, EDA, and the Cloud

Synopsys is the industry’s largest provider of electronic design automation (EDA) technology used in the design and verification of semiconductor devices, or chips. With Synopsys Cloud, we’re taking EDA to new heights, combining the availability of advanced compute and storage infrastructure with unlimited access to EDA software licenses on-demand so you can focus on what you do best – designing chips, faster. Delivering cloud-native EDA tools and pre-optimized hardware platforms, an extremely flexible business model, and a modern customer experience, Synopsys has reimagined the future of chip design on the cloud, without disrupting proven workflows.

 

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