tag: machine learning

NN-Baton: DNN Workload Orchestration & Chiplet Granularity Exploration for Multichip Accelerators
By Technical Paper Link - 14 Jun, 2021 - Comments: 0

"Abstract—The revolution of machine learning poses an unprecedented demand for computation resources, urging more transistors on a single monolithic chip, which is not sustainable in the Post-Moore era. The multichip integration with small functional dies, called chiplets, can reduce the manufacturing cost, improve the fabrication yield, and achieve die-level reuse for different system scales... » read more

Thermal Floorplanning For Chips
By Brian Bailey - 10 Jun, 2021 - Comments: 0

Heat management is becoming crucial to an increasing number of chips, and it's one of a growing number of interconnected factors that must be considered throughout the entire development flow. At the same time, design requirements are exacerbating thermal problems. Those designs either have to increase margins or become more intelligent about the way heat is generated, distributed, and dissi... » read more

There’s More To Machine Learning Than CNNs
By Bryon Moyer - 09 Jun, 2021 - Comments: 1

Neural networks – and convolutional neural networks (CNNs) in particular – have received an abundance of attention over the last few years, but they're not the only useful machine-learning structures. There are numerous other ways for machines to learn how to solve problems, and there is room for alternative machine-learning structures. “Neural networks can do all this really comple... » read more

Security Solutions for AI/ML
By Rambus - 02 Jun, 2021 - Comments: 0

AI/ML is increasingly pervasive across all industries driven by a massive wave of digitization. Data, the raw material of AI/ML and Deep Learning algorithms, is available in enormous quantities from all aspects of business operations. AI/ML promises great gains in responsiveness and adaptability in an ever-changing technology landscape, and industries are enthusiastically responding to that app... » read more

Monitoring Performance From Inside A Chip
By Ed Sperling - 01 Jun, 2021 - Comments: 0

Deep data, which is generated inside the chip rather than externally, is becoming more critical at each new process node and in advanced packages. Uzi Baruch, chief strategy officer at proteanTecs, talks with Semiconductor Engineering about using that data to identify potential problems before they result in failures in the field, and why it's essential to monitor these devices throughout their... » read more

Do We Have An IC Model Crisis?
By Brian Bailey - 27 May, 2021 - Comments: 0

Models are critical for IC design. Without them, it's impossible to perform analysis, which in turn limits optimizations. Those optimizations are especially important as semiconductors become more heterogenous, more customized, and as they are integrated into larger systems, creating a need for higher-accuracy models that require massive compute power to develop. But those factors, and other... » read more

Scaling Simulation
By Brian Bailey - 27 May, 2021 - Comments: 1

Without functional simulation the semiconductor industry would not be where it is today, but some people in the industry contend it hasn't received the attention and research it deserves, causing a stagnation in performance. Others disagree, noting that design sizes have increased by orders of magnitude while design times have shrunk, pointing to simulation remaining a suitable tool for the job... » read more

One-On-One: Lip-Bu Tan
By Ed Sperling - 26 May, 2021 - Comments: 0

Lip-Bu Tan, CEO of Cadence, sat down with Semiconductor Engineering to talk about the impact of massive increases in data across a variety of industries, the growing need for computational software, and the potential implications of U.S.-China relations. What follows are excerpts of that discussion. SE: What do you see as the biggest change for the chip industry? Tan: We're in our fifth g... » read more

The Increasingly Uneven Race To 3nm/2nm
By Mark LaPedus and Ed Sperling - 24 May, 2021 - Comments: 2

Several chipmakers and fabless design houses are racing against each other to develop processes and chips at the next logic nodes in 3nm and 2nm, but putting these technologies into mass production is proving both expensive and difficult. It's also beginning to raise questions about just how quickly those new nodes will be needed and why. Migrating to the next nodes does boost performance an... » read more

Machine Learning At The Edge
By Siemens EDA - 12 May, 2021 - 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

← Older posts Newer posts →

  • Sponsors

About

Navigation

Connect With Us

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