Delivering High-Speed Communications: The Back Story


Back in January, I posted a blog about what it takes to deliver high-speed communication. In that post, I talked about a new test board for our high-speed 7nm 56G PAM4 & NRZ DSP-based long-reach SerDes. We collaborated with several companies to build a high-precision board that could be used to test our SerDes in a system context. At that time, we were just finishing the opening act for thi... » read more

Engineering The Signal For GDDR6


DDR1 through DDR3 had their challenges, but speeds were below one gigabit and signal integrity (SI) challenges were more centered around static timing and running pseudo random binary sequence (PRBS) simulations. Now, with GDDR6, we are working on 16 to 20 gigabits per second (Gbps) signaling and even faster in the near future. As a result, engineering the signal for GDDR6 will require careful ... » read more

Latency Under Load: HBM2 vs. GDDR6


Steven Woo, Rambus fellow and distinguished inventor, explains why data traffic and bandwidth are critical to choosing the type of DRAM, options for improving traffic flow in different memory types, and how this works with multiple memory types.   Related Video GDDR6 - HBM2 Tradeoffs Why designers choose one memory type over another. Applications for each were clearly delineate... » read more

GDDR6 And HBM2: Signal Integrity Challenges For AI


In a nutshell, Artificial Intelligence (AI) and its growing list of applications demand a considerably large amount of bandwidth to push bits in and out of memory at the highest speeds possible. AI has been getting a lot of industry attention, and certainly it’s not a new phenomenon because it’s been gaining even greater traction in the last year or two. This is especially true since a n... » read more

GDDR6: Signal Integrity Challenges For Automotive Systems


Signal integrity (SI) is at the forefront of SoC and system designers’ thinking as they plan for upcoming high-speed GDDR6 DRAM and PHY implementations for automotive and advanced driver assistance system (ADAS) applications. Rambus and its partners are closely looking at how GDDR6’s 16 gigabit per second speed at each pin affects signal integrity given the cost and system constraints for a... » read more

2.5D, 3D Power Integrity


Chris Ortiz, principal applications engineer at ANSYS, zeroes in on some common issues that are showing up in 2.5D and 3D packaging, which were not obvious in the initial implementations of these packaging technologies. This includes everything from how to build a power delivery network to minimize the coupling between chips to dealing with variability and power integrity and placement of diffe... » read more

New Design Approaches At 7/5nm


The race to build chips with a multitude of different processing elements and memories is making it more difficult to design, verify and test these devices, particularly when AI and leading-edge manufacturing processes are involved. There are two fundamental problems. First, there are much tighter tolerances for all of the components in those designs due to proximity effects. Second, as a re... » read more

Why Parallelization Is So Hard


Semiconductor Engineering sat down to talk about parallelization efforts within EDA with Andrea Casotto, chief scientist for Altair; Adam Sherer, product management group director in the System & Verification Group of Cadence; Harry Foster, chief scientist for Mentor, a Siemens Business; Vladislav Palfy, global manager for applications engineering at OneSpin; Vigyan Singhal, chief Oski for ... » read more

Blog Review: Mar. 14


Cadence's Meera Collier considers the issues of bias implementation in algorithms and AI systems, and whether immense training sets can really solve the problem. Mentor's Cristian Filip digs into the evolution of signal integrity analysis methods and why different data rates require different solutions. Synopsys' Naveen G explains key features introduced in the latest generation of interc... » read more

GDDR6 PHYs: From The Data Center To Self-Driving Cars


The demand for ever-increasing bandwidth has resulted in a growing interest in GDDR across a number of market verticals, including data centers and the automotive sector. As an example of the former, deep learning applications require ever-increasing speed and bandwidth memory solutions in the data center. In deep learning and other emerging technologies, GDDR memory can help companies addre... » read more

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