Gate-All-Around: TCAD and DTCO Approach To Evaluate Power and Performance (imec, et al.)


A new technical paper titled "Exploring GAA-Nanosheet, Forksheet and GAA-Forksheet Architectures: a TCAD-DTCO Study at 90 nm & 120 nm Cell Height" was published by imec, Huawei Technologies and Global TCAD Solutions. Abstract "This study presents a Technology Computer Aided Design (TCAD) and comprehensive Design-Technology Co-Optimization (DTCO) approach to evaluate and enhance power an... » read more

Goal-Driven AI


For many, the long-term dream for AI within EDA is the ability to define a set of goals and tell the computer to go design it for them. A short while later, an optimized design will pop out. All of today's EDA tools will remain hidden, if they even exist at all. You would only be limited by your imagination. But we also know that AI is not to be trusted today, especially when millions of dol... » read more

Is PPA Relevant Today?


The optimization of power, performance, and area (PPA) has been at the core of chip design since the dawn of EDA, but these metrics are becoming less valuable without the context of how and where these chips will be used. Unlike in the past, however, that context now comes from factors outside of hardware development. And while PPA still serves as a useful proxy for many parts of the hardwar... » read more

Higher Density, More Data Create New Bottlenecks In AI Chips


Data movement is becoming a bigger problem at advanced nodes and in advanced packaging due to denser circuitry, more physical effects that can affect the integrity of signals or the devices themselves, and a significant increase in data from AI and machine learning. Just shrinking features in a design is no longer sufficient, given the scaling mismatch between SRAM-based L1 cache and digital... » read more

5 Novel Layout Design Methodologies For The 3nm Nanosheet FET Library (Samsung, KNU)


A new technical paper titled "Design Technology Co-Optimization and Time-Efficient Verification for Enhanced Pin Accessibility in the Post-3-nm Node" was published by researchers at Samsung Electronics and Kyungpook National University (KNU). Abstract: "As the technology nodes approach 3 nm and beyond, nanosheet FETs (NSFETs) are replacing FinFETs. However, despite the migration of devices ... » read more

Intel Vs. Samsung Vs. TSMC


The three leading-edge foundries — Intel, Samsung, and TSMC — have started filling in some key pieces in their roadmaps, adding aggressive delivery dates for future generations of chip technology and setting the stage for significant improvements in performance with faster delivery time for custom designs. Unlike in the past, when a single industry roadmap dictated how to get to the next... » read more

Design Flow Challenged By 3D-IC Process, Thermal Variation


3D-ICs are proving a challenge even for designers accustomed to dealing with power and performance tradeoffs, but they are considered an inevitable migration path for leading-edge designs due to the compute demands of AI and the continual shrinking of digital logic. 3D-ICs are widely viewed as the way to continue scaling beyond the limits of planar SoCs, and a way to add more heterogeneous d... » read more

Securing The World’s Data: A Looming Challenge


A combination of increasingly complex designs, more connected devices, and a mix of different generations of security technology are creating a whole new set of concerns about the safety of data nearly everywhere. While security experts have been warning of a growing threat in electronics for decades, there have been several recent fundamental changes that elevate the risk. Among them: ... » read more

Getting Optimal PPA For HPC & AI Applications With Foundation IP


By Andrew Appleby, Xiaorui Hu, and Bhavana Chaurasia The demand for application-specific system-on-chips (SoCs) for compute applications is ever-increasing. Today, the diversity of requirements means there is a need for a rich set of compute solutions in a wide range of process technologies. The resulting products may have very different but demanding power, performance, and area (PPA) requi... » read more

AI-Driven Macro Placement Boosts PPA


In the era of EDA 4.0, artificial intelligence (AI) and machine learning (ML) are transforming what electronic design automation tools are capable of. For many of the challenges of physical IC design, AI can provide significant benefits to both the turnaround time and the quality of the design, as measured by performance, power, and area (PPA) metrics. One implementation step due for improve... » read more

← Older posts