Navigating the challenges of manual IP design migrations
In semiconductor design, the migration of IP across different technology nodes is a complex but business critical process. This task, traditionally manual, involves a detailed analysis of source and target technologies, migration of schematics and testbenches, and iterative design adjustments to meet specific performance requirements for the final design layout.
The challenges of manual migration
The manual process is intricate and lengthy, taking weeks to months, depending on the complexity of the circuit and IPs involved. Designers must deeply understand circuit behavior across Process, Voltage, and Temperature (PVT) corners, and engage in extensive simulations and iterations to achieve the desired specifications.
Additionally, the rate at which new technology nodes are introduced is accelerating, with each new node introducing more design rule complexity, leading to higher development costs and greater pressure on engineering resources due to the additional time needed to manage the migration process.
A shortage of skilled engineers further complicates the situation, not only extending design timelines and inflating costs due to the premium on expert talent, but also putting companies at risk of falling behind in the fiercely competitive race to secure fab capacity.
To read the full article, click here
Related Semiconductor IP
- xSPI Multiple Bus Memory Controller
- MIPI CSI-2 IP
- PCIe Gen 7 Verification IP
- WIFI 2.4G/5G Low Power Wakeup Radio IP
- Radar IP
Related Blogs
- Can AI-Driven Chip Design Meet the Challenges of Tomorrow?
- Navigating the Complexity of Address Translation Verification in PCI Express 6.0
- Navigating Integration Challenges for the RISC-V Ecosystem with Networks-on-Chips (NoCs)
- Industry Leaders Discuss "Overcoming the Challenges of Multi-die Systems Verification"
Latest Blogs
- The Growing Importance of PVT Monitoring for Silicon Lifecycle Management
- Unlock early software development for custom RISC-V designs with faster simulation
- HBM4 Boosts Memory Performance for AI Training
- Using AI to Accelerate Chip Design: Dynamic, Adaptive Flows
- Locking When Emulating Xtensa LX Multi-Core on a Xilinx FPGA