Week In Review: Design, Low Power


Tools & IP Synopsys debuted VIP and a UVM source code test suite for IP supporting Ethernet 800G. The VIP supports DesignWare 56G Ethernet, 112G Ethernet, and 112G USR/XSR PHYs for FinFET processes, which can be integrated for 800G implementations based on 8 lane x 100 Gb/s technology. The VIP can switch speed configurations dynamically at run time and includes a customizable set of frame ... » read more

Blog Review: March 25


Rambus' Steven Woo checks out common memory systems that are used in the highest performance AI applications and points to the differences between on-chip memory, HBM, and GDDR. Mentor's Colin Walls considers whether software for embedded systems should be delivered as a binary library or source code and warns of some key potential issues when requesting source code. A Synopsys writer poi... » read more

Blog Review: March 18


Arm's Divya Prasad investigates whether power rails that are buried below the BEOL metal stack and back-side power delivery can help alleviate some of the major physical design challenges facing 3nm nodes and beyond. Rambus' Steven Woo takes a look at a Roofline model for analyzing machine learning applications that illustrates how AI applications perform on Google’s tensor processing unit... » read more

Designing Resilient Electronics


Electronic systems in automobiles, airplanes and other industrial applications are becoming increasingly sophisticated and complex, required to perform an expanding list of functions while also becoming smaller and lighter. As a result, pressure is growing to design extremely high-performance chips with lower energy consumption and less sensitivity to harsh environmental conditions. If this ... » read more

HBM Issues In AI Systems


All systems face limitations, and as one limitation is removed, another is revealed that had remained hidden. It is highly likely that this game of Whac-A-Mole will play out in AI systems that employ high-bandwidth memory (HBM). Most systems are limited by memory bandwidth. Compute systems in general have maintained an increase in memory interface performance that barely matches the gains in... » read more

HBM2E Memory: A Perfect Fit For AI/ML Training


Artificial Intelligence/Machine Learning (AI/ML) growth proceeds at a lightning pace. In the past eight years, AI training capabilities have jumped by a factor of 300,000 (10X annually), driving rapid improvements in every aspect of computing hardware and software. Memory bandwidth is one such critical area of focus enabling the continued growth of AI. Introduced in 2013, High Bandwidth Memo... » read more

Power Management Becomes Top Issue Everywhere


Power management is becoming a bigger challenge across a wide variety of applications, from consumer products such as televisions and set-top-boxes to large data centers, where the cost of cooling server racks to offset the impact of thermal dissipation can be enormous. Several years ago, low-power design was largely relegated to mobile devices that were dependent on a battery. Since then, i... » read more

Blog Review: Mar. 11


Rambus' Steven Woo examines how the upcoming deployment of 5G will enable processing at the edge, and how the edge is getting refined further into the near edge and the far edge with a range of AI solutions across it. A Synopsys writer explains the types of Compute Express Link devices and CXL's unique verification challenges like maintaining the cache coherency between a host CPU and an acc... » read more

5G And AI Raise Security Risks For IoT Devices


This IDC Technology Spotlight, sponsored by Rambus, highlights the fifth generation of cellular network technology (5G) is scaling further in 2020, enabling a new wave of AI-powered end points. To remain competitive, manufacturers must implement enhanced security measures on edge and IoT devices designed for the increased performance in speed, latency, and connection density. Click here to r... » read more

High-Performance Memory For AI And HPC


Frank Ferro, senior director of product management at Rambus, examines the current performance bottlenecks in high-performance computing, drilling down into power and performance for different memory options, and explains what are the best solutions for different applications and why. » read more

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