tag: training

What Is Intern Reading Club?
By John Chawner - 12 Aug, 2021 - Comments: 0

As the summer winds down, interns are busy completing their assigned projects and preparing their end of summer presentations. These presentations have been a rite of passage for interns on the Pointwise team for many years and gives each intern a chance to show off what they learned and accomplished. And the rest of the team gets to hear all the details of what they've been working on. Anothe... » read more

Continuous Education For Engineers
By Brian Bailey - 29 Jul, 2021 - Comments: 0

Continuous education is essential for engineers, but many companies don't recognize the value or they are unwilling to provide the necessary resources. This should be a line of questioning before every new hire makes the decision about where they want to work, because it not only affects their future career, but also impacts the value they can provide to that company during the course of the... » read more

RaPiD: AI Accelerator for Ultra-low Precision Training and Inference
By Technical Paper Link - 02 Jul, 2021 - Comments: 0

Abstract—"The growing prevalence and computational demands of Artificial Intelligence (AI) workloads has led to widespread use of hardware accelerators in their execution. Scaling the performance of AI accelerators across generations is pivotal to their success in commercial deployments. The intrinsic error-resilient nature of AI workloads present a unique opportunity for performance/energy i... » read more

Challenges Of Edge AI Inference
By Vinay Mehta - 01 Jul, 2021 - Comments: 0

Bringing convolutional neural networks (CNNs) to your industry—whether it be medical imaging, robotics, or some other vision application entirely—has the potential to enable new functionalities and reduce the compute requirements for existing workloads. This is because a single CNN can replace more computationally expensive image processing, denoising, and object detection algorithms. Howev... » read more

Architectural Considerations For AI
By Brian Bailey - 24 Jun, 2021 - Comments: 2

Custom chips, labeled as artificial intelligence (AI) or machine learning (ML), are appearing on a weekly basis, each claiming to be 10X faster than existing devices or consume 1/10 the power. Whether that is enough to dethrone existing architectures, such as GPUs and FPGAs, or whether they will survive alongside those architectures isn't clear yet. The problem, or the opportunity, is that t... » read more

Applications, Challenges For Using AI In Fabs
By Mark LaPedus - 14 Apr, 2021 - Comments: 0

Experts at the Table: Semiconductor Engineering sat down to discuss chip scaling, transistors, new architectures, and packaging with Jerry Chen, head of global business development for manufacturing & industrials at Nvidia; David Fried, vice president of computational products at Lam Research; Mark Shirey, vice president of marketing and applications at KLA; and Aki Fujimura, CEO of D2S. Wh... » read more

HBM2E Raises The Bar For AI/ML Training
By Frank Ferro - 11 Mar, 2021 - Comments: 0

The largest AI/ML neural network training models now exceed an enormous 100 billion parameters. With the rate of growth over the last decade on a 10X annual pace, we’re headed to trillion parameter models in the not-too-distant future. Given the tremendous value that can be derived from AI/ML (it is mission critical to five of six of the top market cap companies in the world), there has been ... » read more

Stretching Engineers
By Brian Bailey - 22 Dec, 2020 - Comments: 1

Engineering has one constant — you innovate or fall by the wayside. That is true both for the things that are designed and for the engineers who design and build them. Today’s systems are putting new strains on engineers who can no longer be "tall and thin" or "short and fat." Those descriptions pertain to an engineer who is either highly specialized or one who has much broader experience. ... » read more

Difficult Memory Choices In AI Systems
By Ann Mutschler - 12 Nov, 2020 - Comments: 0

The number of memory choices and architectures is exploding, driven by the rapid evolution in AI and machine learning chips being designed for a wide range of very different end markets and systems. Models for some of these systems can range in size from 10 billion to 100 billion parameters, and they can vary greatly from one chip or application to the next. Neural network training and infer... » read more

Big Changes In AI Design
By SE Staff - 06 Aug, 2020 - Comments: 0

Semiconductor Engineering sat down to discuss AI and its move to the edge with Steven Woo, vice president of enterprise solutions technology and distinguished inventor at Rambus; Kris Ardis, executive director at Maxim Integrated; Steve Roddy, vice president of Arm's Products Learning Group; and Vinay Mehta, inference technical marketing manager at Flex Logix. What follows are excerpts of that ... » read more

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