tag: machine learning

Why Data Center Power Will Never Come Down
By Bryon Moyer - 10 Feb, 2022 - Comments: 3

Data centers have become significant consumers of energy. In order to deal with the proliferation of data centers and the servers within them, there is a big push to reduce the energy consumption of all data center components. With all that effort, will data center power really come down? The answer is no, despite huge improvements in energy efficiency. “Keeping data center power consum... » read more

Technology Advancements For Dynamic Function eXchange In Vivado ML Edition
By Xilinx - 08 Feb, 2022 - Comments: 0

As systems become more complex and designers are asked to do more with less, adaptability is a critical asset. While Xilinx FPGAs and SoCs always provided the flexibility to perform on-site device reprogramming, current constraints including increased cost, tighter board space, and power consumption demand even more efficient design strategies. Xilinx Dynamic Function eXchange (DFX) extends the... » read more

ML Focus Shifting Toward Software
By Bryon Moyer - 03 Feb, 2022 - Comments: 1

New machine-learning (ML) architectures continue to garner a huge amount of attention as the race continues to provide the most effective acceleration architectures for the cloud and the edge, but attention is starting to shift from the hardware to the software tools. The big question now is whether a software abstraction eventually will win out over hardware details in determining who the f... » read more

Addressing Library Characterization And Verification Challenges Using ML
By Siemens EDA - 02 Feb, 2022 - Comments: 0

At advanced process nodes, Liberty or library (.lib) requirements are more demanding due to design complexities, increased number of corners required for timing signoff, and the need for statistical variation modeling. This results in an increase in size, complexity, and the number of .lib characterizations. Validation and verification of these complex and large .lib files is a challenging task... » read more

Inverse Design of Inflatable Soft Membranes Through Machine Learning
By Technical Paper Link - 27 Jan, 2022 - Comments: 0

Abstract "Across fields of science, researchers have increasingly focused on designing soft devices that can shape-morph to achieve functionality. However, identifying a rest shape that leads to a target 3D shape upon actuation is a non-trivial task that involves inverse design capabilities. In this study, a simple and efficient platform is presented to design pre-programmed 3D shapes starting... » read more

Growth Spurred By Negatives
By Brian Bailey - 27 Jan, 2022 - Comments: 0

The success and health of the semiconductor industry is driven by the insatiable appetite for increasingly complex devices that impact every aspect of our lives. The number of design starts for the chips used in those devices drives the EDA industry. But at no point in history have there been as many market segments driving innovation as there are today. Moreover, there is no indication this... » read more

Greener Design Verification
By Brian Bailey - 27 Jan, 2022 - Comments: 0

Chip designs are optimized for lower cost, better performance, or lower power. The same cannot be said about verification, where today very little effort is spent on reducing execution cost, run time, or power consumption. Admittedly, one is a per unit cost while the other is a development cost, but could the industry be doing more to make development greener? It can take days for regression... » read more

Next Generation Reservoir Computing
By Technical Paper Link - 18 Jan, 2022 - Comments: 0

Abstract: "Reservoir computing is a best-in-class machine learning algorithm for processing information generated by dynamical systems using observed time-series data. Importantly, it requires very small training data sets, uses linear optimization, and thus requires minimal computing resources. However, the algorithm uses randomly sampled matrices to define the underlying recurrent neural n... » read more

Is Programmable Overhead Worth The Cost?
By Brian Bailey - 13 Jan, 2022 - Comments: 0

Programmability has fueled the growth of most semiconductor products, but how much does it actually cost? And is that cost worth it? The answer is more complicated than a simple efficiency formula. It can vary by application, by maturity of technology in a particular market, and in the context of much larger systems. What's considered important for one design may be very different for anothe... » read more

How Inferencing Differs From Training in Machine Learning Applications
By Sam Fuller - 06 Jan, 2022 - Comments: 0

Machine learning (ML)-based approaches to system development employ a fundamentally different style of programming than historically used in computer science. This approach uses example data to train a model to enable the machine to learn how to perform a task. ML training is highly iterative with each new piece of training data generating trillions of operations. The iterative nature of the tr... » read more

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