Making Sensors More Reliable


Experts at the Table: Semiconductor Engineering sat down to talk about the latest issues in sensors with Prakash Madhvapathy, director of product marketing, Tensilica audio/voice DSPs group at Cadence; Kevin Hughes, senior product manager for MEMS sensors at Infineon; and Matthew Hogan, product management director at Siemens EDA. What follows are excerpts of that conversation. [L-R] Kevin ... » read more

Supercomputing Efficiency Lags Performance Gains


In last month’s article, Top 500: Frontier is Still on Top, I wrote about the latest versions of the Top500 and Green500 lists. Power is an incredibly important aspect of designing a world performance leading supercomputer. (Why, I can remember back to when you could run the world’s fastest machine on only a couple MW of power.) The first Green500 list was published back in 2013. Happy 1... » read more

Smart Devices Enabled To Efficiently Communicate, Sense, Hear, Act And Interact With User


The latest advancements in embedded systems and communication and sensing technology have led to the increasing development of smart applications. This has been a continuously evolving process, involving either the creation of completely new solutions or the rapid transformation of existing ones into corresponding highly smart environments. The main driving forces of the smart transformation ha... » read more

Algorithm HW Framework That Minimizes Accuracy Degradation, Data Movement, And Energy Consumption Of DNN Accelerators (Georgia Tech)


This new research paper titled "An Algorithm-Hardware Co-design Framework to Overcome Imperfections of Mixed-signal DNN Accelerators" was published by researchers at Georgia Tech. According to the paper's abstract, "In recent years, processing in memory (PIM) based mixed-signal designs have been proposed as energy- and area-efficient solutions with ultra high throughput to accelerate DNN com... » read more

AI Power Consumption Exploding


Machine learning is on track to consume all the energy being supplied, a model that is costly, inefficient, and unsustainable. To a large extent, this is because the field is new, exciting, and rapidly growing. It is being designed to break new ground in terms of accuracy or capability. Today, that means bigger models and larger training sets, which require exponential increases in processin... » read more

A Minimal RISC-V


Microcontrollers exist in almost everything, but can RISC-V satisfy the needs of this market? Is it small enough to replace 8-bit processors? What might help people migrate to a more modern processor architecture? RISC-V defines a 32-bit processor instruction set architecture (ISA) that is open source and free to be implemented in any number of ways. It is touted for being a very small and e... » read more

Improving Energy And Power Efficiency In The Data Center


Energy costs in data centers are soaring as the amount of data being generated explodes, and it's being made worse by an imbalance between increasingly dense processing elements that are producing more heat and uneven server utilization, which requires more machines to be powered up and cooled. The challenge is to maximize utilization without sacrificing performance, and in the past that has... » read more

Powering The Edge: Driving Optimal Performance With Ethos-N77 Processor


Repurposing a CPU, GPU, or DSP is an easy way to add ML capabilities to an edge device. However, where responsiveness or power efficiency is critical, a dedicated Neural Processing Unit (NPU) may be the best solution. In this paper, we describe how the Arm Ethos-N77 NPU delivers optimal performance. Click here to immediately download the paper. » read more

How Much Power Will AI Chips Use?


AI and machine learning have voracious appetites when it comes to power. On the training side, they will fully utilize every available processing element in a highly parallelized array of processors and accelerators. And on the inferencing side they, will continue to optimize algorithms to maximize performance for whatever task a system is designed to do. But as with cars, mileage varies gre... » read more

Multiphysics Simulations for AI Silicon to System Success


Achieving power efficiency, power integrity, signal integrity, thermal integrity and reliability is paramount for enabling product success by overcoming the challenges of size and complexity in AI hardware and optimizing the same for rapidly evolving AI software. ANSYS’ comprehensive chip, package and system solutions empower AI hardware designers by breaking down design margins and siloed de... » read more

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