5 Steps to Confront the Talent Shortage With IP-Centric Design
By Vishal Moondhra, Perforce Software
EETimes (January 4, 2024)
The talent shortage is one of the biggest challenges the U.S. semiconductor industry must confront.
According to the Semiconductor Industry Association, of the 115,000 open jobs in the industry through 2030, 58% will not be filled. The demand for these skilled employees isn’t going away anytime soon, especially as the chip industry accelerates design and production sparked by the 2022 CHIPS and Science Act. Projects are coming to market faster, budgets are tighter and teams are spread across the globe, making efficiency paramount across the board. However, U.S. chipmakers could come to a standstill if they don’t figure out how to close the talent gap.
One way to help alleviate the effects of the talent shortage is changing how semiconductors are designed so that organizations can achieve more with their existing workforce. This requires moving away from project-centric design and transitioning to an IP-centric design methodology. But why make this switch?
To read the full article, click here
Related Semiconductor IP
- DeWarp IP
- 6-bit, 12 GSPS Flash ADC - GlobalFoundries 22nm
- LunaNet AFS LDPC Encoder and Decoder IP Core
- ReRAM NVM in DB HiTek 130nm BCD
- UFS 5.0 Host Controller IP
Related Articles
- EDA in the Cloud Will be Key to Rapid Innovative SoC Design
- FPGAs - The Logical Solution to the Microcontroller Shortage
- Paving the way for the next generation of audio codec for True Wireless Stereo (TWS) applications - PART 5 : Cutting time to market in a safe and timely manner
- It's Just a Jump to the Left, Right? Shift Left in IC Design Enablement
Latest Articles
- VolTune: A Fine-Grained Runtime Voltage Control Architecture for FPGA Systems
- A Lightweight High-Throughput Collective-Capable NoC for Large-Scale ML Accelerators
- Quantifying Uncertainty in FMEDA Safety Metrics: An Error Propagation Approach for Enhanced ASIC Verification
- SoK: From Silicon to Netlist and Beyond Two Decades of Hardware Reverse Engineering Research
- An FPGA-Based SoC Architecture with a RISC-V Controller for Energy-Efficient Temporal-Coding Spiking Neural Networks