tag: AI/ML

Using ML For Improved Fab Scheduling
By Katherine Derbyshire - 25 Jul, 2023 - Comments: 0

Expanding fab capacity is slow and expensive even under ideal circumstances. It has been still more difficult in recent years, as pandemic-related shortages have strained equipment supply chains. When integrated circuit demand rises faster than expansions can fill the gap, fabs try to find “hidden” capacity through improved operations. They hope that more efficient workflows will allow e... » read more

Goals of Going Green
By Anne Meixner - 25 Jul, 2023 - Comments: 0

The chip industry is stepping up efforts to be seen as environmentally friendly, driven by growing pressure from customers and government regulations. Some manufacturers have been addressing sustainability challenges for more than a decade, but they are becoming more aggressive in their efforts, while others are joining them. A review of sustainability reports across the semiconductor indust... » read more

HBM’s Future: Necessary But Expensive
By Karen Heyman - 20 Jul, 2023 - Comments: 0

High-bandwidth memory (HBM) is becoming the memory of choice for hyperscalers, but there are still questions about its ultimate fate in the mainstream marketplace. While it’s well-established in data centers, with usage growing due to the demands of AI/ML, wider adoption is inhibited by drawbacks inherent in its basic design. On the one hand, HBM offers a compact 2.5D form factor that enables... » read more

HBM3 And GDDR6: Memory Solutions For AI
By Rambus - 31 May, 2023 - Comments: 0

AI/ML changes everything, impacting every industry and touching the lives of everyone. With AI training sets growing at a pace of 10X per year, memory bandwidth is a critical area of focus as we move into the next era of computing and enable this continued growth. AI training and inference have unique feature requirements that can be served by tailored memory solutions. Learn how HBM3 and GDDR6... » read more

Making Tradeoffs With AI/ML/DL
By Ann Mutschler - 11 May, 2023 - Comments: 0

Machine learning, deep learning, and AI increasingly are being used in chip design, and they are being used to design chips that are optimized for ML/DL/AI. The challenge is understanding the tradeoffs on both sides, both of which are becoming increasingly complex and intertwined. On the design side, machine learning has been viewed as just another tool in the design team's toolbox. That's s... » read more

ML Automotive Chip Design Takes Off
By Ann Mutschler - 04 May, 2023 - Comments: 0

Machine learning is increasingly being deployed across a wide swath of chips and electronics in automobiles, both for improving reliability of standard parts and for the creation of extremely complex AI chips used in increasingly autonomous applications. On the design side, the majority of EDA tools today rely on reinforcement learning, a machine learning subset of AI that teaches a machine ... » read more

From Data Center To End Device: AI/ML Inference With GDDR6
By Rambus - 03 May, 2023 - Comments: 0

Created to support 3D gaming on consoles and PCs, GDDR packs performance that makes it an ideal solution for AI/ML inference. As inference migrates from the heart of the data center to the network edge, and ultimately to a broad range of AI-powered IoT devices, GDDR memory’s combination of high bandwidth, low latency, power efficiency and suitability for high-volume applications will be incre... » read more

Smarter Ways To Manufacture Chips
By Anne Meixner - 20 Apr, 2023 - Comments: 0

OSAT and wafer fabs are beginning to invest in Industry 4.0 solutions in order to improve efficiency and reduce operating costs, but it's a complicated process that involves setting up frameworks to evaluate different options and goals. Semiconductor manufacturing facilities have relied on dedicated automation teams for decades. These teams track and schedule chip production, respond to equi... » read more

Combination of AI Techniques To Find The Best Ways to Place Transistors on Silicon Chips
By Technical Paper Link - 30 Mar, 2023 - Comments: 0

A new technical paper titled "AutoDMP: Automated DREAMPlace-based Macro Placement" was published by researchers at NVIDIA. Abstract: "Macro placement is a critical very large-scale integration (VLSI) physical design problem that significantly impacts the design power-performance-area (PPA) metrics. This paper proposes AutoDMP, a methodology that leverages DREAMPlace, a GPU-accelerated place... » read more

Cooling The Data Center
By Karen Heyman - 15 Mar, 2023 - Comments: 0

Since British mathematician and entrepreneur Clive Humby coined the rallying cry, “Data is the new oil,” some 20 years ago, it has been an upbeat phrase at data science conferences. But in engineering circles, that increasingly includes a daily grind of hardware challenges, and chief among them is how to cool the places where all that data is processed and stored. An estimated 65 zettaby... » read more

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