Primary Challenges to Getting Better Visibility Across Your Chip Design Flows

The best way to get an end-to-end view of how your designs are progressing is to get all the required data and metrics in the right format in a centralized place. In our previous blog, we identified 3 challenges that make this hard to do:

1. Getting the right data

Data, metadata, and metrics from EDA tools can be hard to unlock making it hard to get a complete view of the design and design activity. It can be in different formats and even be spread across different tools. One key challenge is getting the right data from the design tools. Making this hard are the different formats of the data and usage of a wide variety of tools from multiple vendors.

2. Tracking and understanding data analysis and metrics

Design teams usually create large volumes of data but they rarely track and understand what they have. This can lead to data being stuck in silos within different teams, and the data analysis itself is often not shared. This makes it hard to track the overall progress of the design as well as the time and effort spent by different members of the team.

Design teams also need to understand the relationship between phases of the flow. For example, a synthesis team needs to know how stable the RTL is, a physical design team needs to know, for example how the area and utilization correlates different logical blocks and whether the area reported during synthesis will cause downstream problems, as power analysis team might need to data from both the verification and the backend team. Coordinating this is often time consuming and requires a lot of manual effort.

3. Getting the data to the right people for actionable insights

There are two problems with the current approach of sending out status reports and metrics to different stakeholders. The first is the amount of time it takes to create the status and metrics report. Secondly, even when the status report is created, it sometimes doesn’t end up in the hands of the right decision makers, especially in large organizations.

Enabling Data-Driven Decision Making

Enabling data-driven decision making for chip designs requires the ability to centralize all the required data and metrics from across your design and flow. This requires tools that can do the grunt work of data collection, analysis, and reporting.

It also requires tooling that can get the data to the right people in the right formats for actionable insights. This is critical for getting the most out of the data. It also allows different stakeholders to be able to collaborate on the same data.

Much like it is now impossible to imagine software development without version control and history, we anticipate visibility and analytics to become a core part of chip development.

In our next blog, we will touch on the importance of automation to enable the visibility needed to help your chip design teams do more with less.

To learn more about how our solution can help you increase the productivity of your team through better visibility, contact us at: