tag: machine learning

Using ASICs For AI Inferencing
By Ed Sperling - 10 Oct, 2018 - Comments: 0

Flex Logix’s Cheng Wang looks at why ASICs are the best way to improve performance and optimize power and area for inferencing, and how to add flexibility into those designs to deal with constantly changing algorithms and data sets. https://youtu.be/XMHr7sz9JWQ » read more

System Bits: Oct. 9
By Ann Mutschler - 09 Oct, 2018 - Comments: 0

Sensing with light pulses In a development expected to be useful in applications including distance measurement, molecular fingerprinting and ultrafast sampling, EPFL researchers have found a way to implement an optical sensing system by using spatial multiplexing, a technique originally developed in optical-fiber communication, which produces three independent streams of ultrashort optical pu... » read more

Making Buildings Smarter
By Jeff Dorsch - 04 Oct, 2018 - Comments: 1

Calling a building “smart” implies that technology is embedded to make that building more efficient, useful, convenient and profitable. The goal is to program efficiency beyond what humans can provide. But “smart” also may imply a healthy dose of marketing hype. No one wants to live in a “dumb building,” but it's difficult to define what makes a building smart. And while much is ... » read more

Cloud Drives Changes In Network Chip Architectures
By Ann Mutschler - 03 Oct, 2018 - Comments: 0

Cloud data centers have changed the networking topology and how data moves throughout a large data center, prompting significant changes in the architecture of the chips used to route that data and raising a whole new set of design challenges. Cloud computing has emerged as the fast growing segment of the data center market. In fact, it is expected to grow three-fold in the next few years, a... » read more

System Bits: Oct. 2
By Ann Mutschler - 02 Oct, 2018 - Comments: 0

Computer algorithms exhibit prejudice based on datasets Researchers at Cardiff University and MIT have shown that groups of autonomous machines are capable of demonstrating prejudice by identifying, copying, and learning this behavior from one another. The team noted that while it may seem that prejudice is a human-specific phenomenon that requires human cognition to form an opinion of, or ... » read more

Next-Generation Liberty Verification And Debugging
By WeiLii Tan - 27 Sep, 2018 - Comments: 1

Accurate library characterization is a crucial step for modern chip design and verification. For full-chip designs with billions of transistors, timing sign-off through simulation is unfeasible due to run-time and memory constraints. Instead, a scalable methodology using static timing analysis (STA) is required. This methodology uses the Liberty file to encapsulate library characteristics such ... » read more

AI Chips Must Get The Floating-Point Math Right
By Sergio Marchese - 27 Sep, 2018 - Comments: 0

Most AI chips and hardware accelerators that power machine learning (ML) and deep learning (DL) applications include floating-point units (FPUs). Algorithms used in neural networks today are often based on operations that use multiplication and addition of floating-point values, which subsequently need to be scaled to different sizes and for different needs. Modern FPGAs such as Intel Arria-10 ... » read more

Betting Big On Discontinuity
By Ed Sperling - 27 Sep, 2018 - Comments: 0

Wally Rhines, president and CEO of Mentor, a Siemens Business, sat down with Semiconductor Engineering to talk about the booming chip industry, what's driving it, how long it will last and what changes are ahead in EDA and chip architectures. What follows are excerpts of that conversation. SE: The EDA and semiconductor industries are doing well right now. What's driving that growth? Rhine... » read more

Machine Learning Shifts More Work to FPGAs, SoCs
By Kevin Fogarty - 24 Sep, 2018 - Comments: 0

A wave of machine-learning-optimized chips is expected to begin shipping in the next few months, but it will take time before data centers decide whether these new accelerators are worth adopting and whether they actually live up to claims of big gains in performance. There are numerous reports that silicon custom-designed for machine learning will deliver 100X the performance of current opt... » read more

System Bits: Sept. 18
By SE Staff - 18 Sep, 2018 - Comments: 0

Better AI technique for chemistry predictions CalTech researchers have found a new technique that uses machine learning more effectively to predict how complex chemicals will react to reagents. The tool is a new twist on similar machine learning techniques to find more effective catalysts without having the time-consuming trial-and-error research, making it a time-saver for drug researchers. ... » read more

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