tag: AI

The Price Of Fear
By Brian Bailey - 27 Feb, 2025 - Comments: 0

In my last blog, I talked about how pain is important when making predictions in the semiconductor industry. Pain is related to time to market and risk, and the flip side of risk is fear. Fear is one of the main drivers for a large number of EDA tools, such as those related to verification. The fear is taping out a chip, then waiting for what seems like an eternity to get the first chips bac... » read more

Improving Verification Methodologies
By Brian Bailey - 27 Feb, 2025 - Comments: 0

Methodology improvements and automation are becoming pivotal for keeping pace with the growing complexity and breadth of the tasks assigned to verification teams, helping to compensate for lagging speed improvements in the tools. The problem with the tools is that many of them still run on single processor cores. Functional simulation, for example, cannot make use of an unlimited number of c... » read more

AI’s Rapid Growth: The Crucial Role Of High Bandwidth Memory
By Subash Peddu - 27 Feb, 2025 - Comments: 0

System efficiency is dictated by the performance of crucial components. For AI hardware systems, memory subsystem performance is the single most crucial component. In this blog post, we will provide an overview of the AI model landscape and the impact of HBM memory subsystems on effective system performance. AI models have grown from a few billions of parameters from the early '90s to today�... » read more

Lines Blurring Between Supercomputing And HPC
By Ann Mutschler - 27 Feb, 2025 - Comments: 1

Supercomputers and high-performance computers are becoming increasingly difficult to differentiate due to the proliferation of AI, which is driving huge performance increases in commercial and scientific applications and raising similar challenges for both. While the goals of supercomputing and high-performance computing (HPC) have always been similar — blazing fast processing — the mark... » read more

Key Challenges In Scaling AI Clusters
By Emily Yan - 27 Feb, 2025 - Comments: 0

AI is evolving at an unprecedented pace, driving an urgent need for more powerful and efficient data centers. In response, nations and companies are ramping up investments into AI infrastructure. According to Forbes, AI spending from the Big Tech sector will exceed $250 billion in 2025, with the bulk going towards infrastructure. By 2029, global investments in AI infrastructure, including dat... » read more

What Scares Chip Engineers About Generative AI
By Adam Kovac - 26 Feb, 2025 - Comments: 0

Experts At The Table: LLMs and other generative AI programs are a long way away from being able to design entire chips on their own from scratch, but the emergence of the tech has still raised some genuine concerns. Semiconductor Engineering sat down with a panel of experts, which included Rod Metcalfe, product management group director at Cadence; Syrus Ziai, vice-president of engineering at E... » read more

Advanced Packaging Evolution: Chiplet And Silicon Photonics-CPO
By Vincent Lin - 20 Feb, 2025 - Comments: 0

As we enter the AI era, the demand for enhanced connectivity in cloud services and AI computing continues to surge. With Moore’s Law slowing down, the increasing data rate requirements are surpassing the advancements of any single semiconductor technology. This shift underscores the importance of heterogeneous integration (HI) as a crucial solution for alleviating bandwidth bottlenecks. Tod... » read more

Memory Wall Problem Grows With LLMs
By Katherine Derbyshire - 20 Feb, 2025 - Comments: 0

The growing imbalance between the amount of data that needs to be processed to train large language models (LLMs) and the inability to move that data back and forth fast enough between memories and processors has set off a massive global search for a better and more energy- and cost-efficient solution. Much of this is evident in the numbers. The GPU market is forecast to reach $190 billion in ... » read more

EUV’s Future Looks Even Brighter
By Gregory Haley - 20 Feb, 2025 - Comments: 1

The rapidly increasing demand for advanced-node chips to support everything-AI is putting pressure on the industry's ability to meet demand. The need for cutting-edge semiconductors is accelerating in applications ranging from hyperscale data centers powering large language models to edge AI in smartphones, IoT devices, and autonomous systems. But manufacturing those chips relies heavily on ... » read more

Normalization Keeps AI Numbers In Check
By Bryon Moyer - 13 Feb, 2025 - Comments: 0

AI training and inference are all about running data through models — typically to make some kind of decision. But the paths that the calculations take aren’t always straightforward, and as a model processes its inputs, those calculations may go astray. Normalization is a process that can keep data in bounds, improving both training and inference. Foregoing normalization can result in at... » read more

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