tag: machine learning

Power Challenges In ML Processors
By Brian Bailey - 12 Mar, 2020 - Comments: 0

The design of artificial intelligence (AI) chips or machine learning (ML) systems requires that designers and architects use every trick in the book and then learn some new ones if they are to be successful. Call it style, call it architecture, there are some designs that are just better than others. When it comes to power, there are plenty of ways that small changes can make large differences.... » read more

Machine Learning At The Edge
By Mentor, a Siemens Business - 11 Mar, 2020 - Comments: 0

Moving machine learning to the edge has critical requirements on power and performance. Using off-the-shelf solutions is not practical. CPUs are too slow, GPUs/TPUs are expensive and consume too much power, and even generic machine learning accelerators can be overbuilt and are not optimal for power. In this paper, learn about creating new power/memory efficient hardware architectures to meet n... » read more

AI Roadmap: A human-centric approach to AI in aviation
By Technical Paper Link - 09 Mar, 2020 - Comments: 0

Source: EASA European Union Aviation Safety Agency February 2020 "EASA published its Artificial Intelligence Roadmap 1.0 which establishes the Agency’s initial vision on the safety and ethical dimensions of development of AI in the aviation domain. The AI Roadmap 1.0 is to be viewed as a starting point, intended to serve as a basis for discussion with the Agency’s stakeholders. It... » read more

High-Performance Memory For AI And HPC
By Ed Sperling - 09 Mar, 2020 - Comments: 0

Frank Ferro, senior director of product management at Rambus, examines the current performance bottlenecks in high-performance computing, drilling down into power and performance for different memory options, and explains what are the best solutions for different applications and why. » read more

Degradation Monitoring
By proteanTecs - 09 Mar, 2020 - Comments: 0

This paper describes a reliability degradation modeling and monitoring method based on a combination of IC novel embedded circuits (Agents), and off-chip machine learning algorithms which infer the digital readouts of these circuits during test and operational lifetime. Together, they monitor the margin degradation of an IC, as well as other vital parameters of the IC and its environmental s... » read more

HBM2E and GDDR6: Memory Solutions for AI
By Rambus - 04 Mar, 2020 - Comments: 0

Artificial Intelligence/Machine Learning (AI/ML) growth proceeds at a lightning pace. In the past eight years, AI training capabilities have jumped by a factor of 300,000 driving rapid improvements in every aspect of computing hardware and software. Meanwhile, AI inference is being deployed across the network edge and in a broad spectrum of IoT devices including in automotive/ADAS. Training and... » read more

The Challenges Of Building Inferencing Chips
By Ann Mutschler - 27 Feb, 2020 - Comments: 0

Putting a trained algorithm to work in the field is creating a frenzy of activity across the chip world, spurring designs that range from purpose-built specialty processors and accelerators to more generalized extensions of existing and silicon-proven technologies. What's clear so far is that no single chip architecture has been deemed the go-to solution for inferencing. Machine learning is ... » read more

Wrestling With Variation In Advanced Node Designs
By Ann Mutschler - 19 Feb, 2020 - Comments: 5

Variation is becoming a major headache at advanced nodes, and issues that used to be dealt with in the fab now must be dealt with on the design side, as well. What is fundamentally changing is that margin, which has long been used as a buffer for variation and other manufacturing process-related problems, no longer works in these leading-edge designs for a couple of reasons. First, margin im... » read more

Thinking About AI Power In Parallel
By Ed Sperling - 13 Feb, 2020 - Comments: 0

Most AI chips being developed today run highly parallel series of multiply/accumulate (MAC) operations. More processors and accelerators equate to better performance. This is why it's not uncommon to see chipmakers stitching together multiple die that are larger than a single reticle. It's also one of the reasons so much attention is being paid to moving to the next process node. It's not ne... » read more

AI: A Perfect Solution But At What Cost?
By Chris Bergey - 13 Feb, 2020 - Comments: 0

The advancement of artificial intelligence (AI) has been a great enabler for the Internet of things (IoT). Given the ability to think for itself, it’s shrugged off its original definition as a network of tiny sensors and grown to incorporate a host of more intelligent AIoT (AI+IoT) devices, from smartphones all the way up to autonomous vehicles. AI has also paved the way for new IoT device... » read more

← Older posts Newer posts →

  • Sponsors

About

Navigation

Connect With Us

Copyright ©2013-2025 SMG   |  Terms of Service  |  Privacy Policy