AI For Data Management


Data management is becoming a significant new challenge for the chip industry, as well as a brand new opportunity, as the amount of data collected at every step of design through manufacturing continues to grow. Exacerbating the problem is the rising complexity of designs, many of which are highly customized and domain-specific at the leading edge, as well as increasing demands for reliabili... » read more

Embracing The Future: 5G NTN – Satellite Service For The Masses


In a world where communication is paramount, access to reliable networks is not just a luxury but a necessity. Traditionally, satellite communications have been reserved for specialized terminals with cumbersome antennas and costly subscription plans. However, with the advent of 5G Non-Terrestrial Networks (NTNs), the landscape of satellite phone availability is undergoing a revolutionary tran... » read more

Trouble Ahead For IC Verification


Verification complexity is roughly the square of design complexity, but until recently verification success rates have remained fairly consistent. That's beginning to change. There are troubling signs that verification is collapsing under the load. The first-time success rate fell (see figure 1) in the last survey conducted by Wilson Research, on behalf of Siemens EDA, in 2022. A new survey ... » read more

Considerations to Successfully Integrate Chiplets in Designs


Chiplet integration is a promising approach to creating heterogeneous and complex system-on-chips (SoCs) with significant performance, power, scalability, flexibility, and cost benefits. However, chiplet integration also poses substantial design, verification, testing, and packaging challenges, requiring new standards and design methodologies. Electronic design automation (EDA) software and sim... » read more

Blog Review: May 22


Cadence's Sree Parvathy introduces Verilog-A, a high-level language that uses modules to describe the structure and behavior of analog systems and enables the top-down system to be defined before the actual transistor circuits are assembled. Siemens' Keith Felton suggests the process of package substrate design is improved by leveraging the collective expertise of multiple design domain spec... » read more

Running More Efficient AI/ML Code With Neuromorphic Engines


Neuromorphic engineering is finally getting closer to market reality, propelled by the AI/ML-driven need for low-power, high-performance solutions. Whether current initiatives result in true neuromorphic devices, or whether devices will be inspired by neuromorphic concepts, remains to be seen. But academic and industry researchers continue to experiment in the hopes of achieving significant ... » read more

Blog Review: May 15


Cadence's Anika Sunda suggests that RISC-V has opened numerous doors for innovation and believes EDA tools can help bridge the knowledge gap and foster a growing community of RISC-V developers. Synopsys' Alessandra Costa chats with industry experts about challenges facing analog design, what's needed for multi-die designs, and the potential of AI. Siemens' Bill Ji explains why understandi... » read more

How To Calculate The ROI Of Semiconductor IP Management


Intellectual property (IP) is a vital asset for technology companies. IP is often a critical factor in the valuation of a company and must be protected from accidental damage, leakage, and other negative consequences of poor handling. In the context of silicon companies that work on building silicon chips, the term IP involves overseeing both internal IP developed by the company itself and exte... » read more

Chip Industry Week In Review


Synopsys refocused its security priorities around chips, striking a deal to sell off its Software Integrity Group subsidiary to private equity firms Clearlake Capital Group and Francisco Partners for about $2.1 billion. That deal comes on the heels of Synopsys' recent acquisition of Intrinsic ID, which develops physical unclonable function IP. Sassine Ghazi, Synopsys' president and CEO, said in... » read more

Using AI/ML To Combat Cyberattacks


Machine learning is being used by hackers to find weaknesses in chips and systems, but it also is starting to be used to prevent breaches by pinpointing hardware and software design flaws. To make this work, machine learning (ML) must be trained to identify vulnerabilities, both in hardware and software. With proper training, ML can detect cyber threats and prevent them from accessing critic... » read more

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