Presentation
Boosting IP Quality and Productivity Through Ipdelta Profile-Driven Change Detection
DescriptionAbstract:
Incremental changes are common during IP delivery, with approximately half of IP releases involving limited updates such as view additions, PVT updates, cell fixes, or layout modifications. While expected, these changes significantly complicate IP qualification, as conventional version-to-version validation often produces excessive false positives, increasing debug effort and slowing delivery cycles. Efficiently distinguishing intended modifications from unintended regressions is therefore critical to maintaining IP quality at scale.
This paper presents a profile-driven IP validation framework deployed at STMicroelectronics using Solido IPDelta and integrated within the internal IP QA infrastructure. The approach introduces predefined validation profiles that explicitly model expected changes between IP versions, such as layout-only updates, layout-plus-abstract changes, netlist updates, or liberty model revisions. By waiving known, intentional differences through profile definitions, the framework isolates unexpected inconsistencies for focused analysis across CAD views including GDS, OA, LEF, DEF, netlists, and liberty formats.
Applied across diverse IP types and technology nodes, the profile-based methodology significantly reduces validation noise and improves debugging efficiency. Measured results demonstrate up to a 60% reduction in manual QA effort per IP delivery, while provide a scalable and consistent validation solution for evolving IP ecosystems. This work shows that profile-driven change detection enables robust, efficient IP qualification in incremental delivery environments.
Incremental changes are common during IP delivery, with approximately half of IP releases involving limited updates such as view additions, PVT updates, cell fixes, or layout modifications. While expected, these changes significantly complicate IP qualification, as conventional version-to-version validation often produces excessive false positives, increasing debug effort and slowing delivery cycles. Efficiently distinguishing intended modifications from unintended regressions is therefore critical to maintaining IP quality at scale.
This paper presents a profile-driven IP validation framework deployed at STMicroelectronics using Solido IPDelta and integrated within the internal IP QA infrastructure. The approach introduces predefined validation profiles that explicitly model expected changes between IP versions, such as layout-only updates, layout-plus-abstract changes, netlist updates, or liberty model revisions. By waiving known, intentional differences through profile definitions, the framework isolates unexpected inconsistencies for focused analysis across CAD views including GDS, OA, LEF, DEF, netlists, and liberty formats.
Applied across diverse IP types and technology nodes, the profile-based methodology significantly reduces validation noise and improves debugging efficiency. Measured results demonstrate up to a 60% reduction in manual QA effort per IP delivery, while provide a scalable and consistent validation solution for evolving IP ecosystems. This work shows that profile-driven change detection enables robust, efficient IP qualification in incremental delivery environments.
Event Type
Engineering Poster
Engineering Presentation
TimeWednesday, July 293:00pm - 3:45pm PDT
LocationDAC Pavilion, Exhibit Floor