tag: machine learning

Factoring Reliability Into Chip Manufacturing
By Ed Sperling - 20 Jun, 2019 - Comments: 0

Making chips that can last two decades is possible, even if it's developed at advanced process nodes and is subject to extreme environmental conditions, such as under the hood of a car or on top of a light pole. But doing that at the same price point as chips that go into consumer electronics, which are designed to last two to four years, is a massively complex challenge. Until a couple of y... » read more

Wrestling With High-Speed SerDes
By Ann Mutschler - 19 Jun, 2019 - Comments: 2

SerDes has emerged as the primary solution in chips where there is a need for fast data movement and limited I/O, but this technology is becoming significantly more challenging to work with as speeds continue to rise to offset the massive increase in data. A Serializer/Deserializer is used to convert parallel data into serial data, allowing designers to speed up data communication without h... » read more

Thinking Differently About IIoT Analytics
By Michael Schuldenfrei - 17 Jun, 2019 - Comments: 0

Manufacturers are rushing to keep up with the latest technology trends and perhaps the most significant ones are around the smart factory. Whether you call it Industry 4.0, Smart Manufacturing or the Industrial Internet of Things (IIoT), what all these initiatives have in common is the desire to maximize value from manufacturing data and improve overall manufacturing efficiency. With the ave... » read more

Building Your First Chip For Artificial Intelligence? Read This First
By Ron Lowman - 13 Jun, 2019 - Comments: 0

As artificial intelligence (AI) capabilities enter new markets, the IP selected for integration provides the critical components of the AI SoC. But beyond the IP, designers are finding a clear advantage in leveraging AI expertise, services, and tools to ensure the design is delivered on time, with a high level of quality and value to the end customer for new and innovative applications. Over... » read more

Memory Options And Tradeoffs
By Ed Sperling - 13 Jun, 2019 - Comments: 0

Steven Woo, Rambus fellow and distinguished inventor, talks with Semiconductor Engineering about different memory options, why some are better than others for certain tasks, and what the tradeoffs are between the different memory types and architectures.     Related Articles/Videos Memory Tradeoffs Intensify In AI, Automotive Applications Why choosing memories and archi... » read more

Deep Learning Models With MATLAB And Cortex-A
By Jason Andrews - 13 Jun, 2019 - Comments: 0

Today, I’ve teamed up with Ram Cherukuri of MathWorks to provide an overview of the MathWorks toolchain for machine learning (ML) and the deployment of embedded ML inference on Arm Cortex-A using the Arm Compute Library. MathWorks enables engineers to get started quickly and makes machine learning possible without having to become an expert. If you’re an algorithm engineer interested ... » read more

Data Confusion At The Edge
By Ed Sperling - 11 Jun, 2019 - Comments: 0

Disparities in pre-processing of data at the edge, coupled with a total lack of standardization, are raising questions about how that data will be prioritized and managed in AI and machine learning systems. Initially, the idea was that 5G would connect edge data to the cloud, where massive server farms would infer patterns from that data and send it back to the edge devices. But there is far... » read more

Using ML For Post-Silicon Validation
By Ed Sperling - 11 Jun, 2019 - Comments: 0

Ira Leventhal, vice president of Advantest’s new concept product initiative, talks about how to use machine learning to ferret out hidden relationships in a complex design and to utilize that data to improve chips. » read more

Do Large Batches Always Improve Neural Network Throughput?
By Geoff Tate - 06 Jun, 2019 - Comments: 1

Common benchmarks like ResNet-50 generally have much higher throughput with large batch sizes than with batch size =1. For example, the Nvidia Tesla T4 has 4x the throughput at batch=32 than when it is processing in batch=1 mode. Of course, larger batch sizes have a tradeoff: latency increases which may be undesirable in real-time applications. Why do larger batches increase throughput... » read more

Machine Learning Drives High-Level Synthesis Boom
By Kevin Fogarty - 06 Jun, 2019 - Comments: 0

High-level synthesis (HLS) is experiencing a new wave of popularity, driven by its ability to handle machine-learning matrices and iterative design efforts. The obvious advantage of HLS is the boost in productivity designers get from working in C, C++ and other high-level languages rather than RTL. The ability to design a layout that should work, and then easily modify it to test other confi... » read more

← Older posts Newer posts →

  • Sponsors

About

Navigation

Connect With Us

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