Week In Review: Manufacturing, Test


On Sunday, a 6.8-magnitude earthquake struck the southeast region of Taiwan, causing devastation. TSMC officials reported “no known significant impact for now.” Market research firm TrendForce arrived at a similar conclusion based on its analysis of individual fabs. The Biden administration announced appointment of the leadership team charged with implementing the US CHIPS and Science Ac... » read more

Strengthening The Global Semi Supply Chain


Within the semiconductor ecosystem, there are a number of dynamics pointing to the need for new ways of partnering in more meaningful ways that bring resiliency to the global semiconductor supply chain. One of these is the move to bespoke silicon, stemming from a shift in the companies that create most SoCs today -- the hyperscalar cloud providers. These market leaders know their workloads so w... » read more

The Data Center Journey, From Central Utility To Center Of The Universe


High-performance computing (HPC) has taken on many meanings over the years. The primary goal of HPC is to provide the needed computational power to run a data center – a utilitarian facility dedicated to storing, processing, and distributing data. The beginning of HPC Historically, the data being processed was the output of business operations for a given organization. Transactions, custome... » read more

How Memory Design Optimizes System Performance


Exponential increases in data and demand for improved performance to process that data has spawned a variety of new approaches to processor design and packaging, but it also is driving big changes on the memory side. While the underlying technology still looks very familiar, the real shift is in the way those memories are connected to processing elements and various components within a syste... » read more

Blog Review: Sept. 21


Arm's Neil Burgess and Sangwon Ha explain why they've joined Intel and Nvidia in proposing a new 8-bit floating point specification to enable neural network models developed on one platform to be run on other platforms without encountering the overhead of having to convert the vast amounts of model data between formats while reducing task loss to a minimum. Synopsys' Manuel Mota examines ver... » read more

Securing The Aerospace And Defense Microelectronics Supply Chain With DoD Trusted Suppliers


Since our inception 35 years ago, Synopsys has supported the U.S. defense industry. Over the last five years, we’ve increased our efforts with the government and aerospace sectors via program support at Defense Advanced Research Projects Agency (DARPA) and Intelligence Advanced Research Projects Activity (IARPA) as well as at traditional and non-traditional defense prime contractors. In 20... » read more

The High Price Of Smaller Features


The semiconductor industry’s push for higher numerical apertures is driven by the relationship between NA and critical dimension. As the NA goes up, the CD goes down: Where λ is the wavelength and k1 is a process coefficient. While 0.55 NA exposure systems will improve resolution, Larry Melvin, principal engineer at Synopsys, noted that smaller features always come with a process cos... » read more

Blog Review: Sept. 14


Synopsys' Godwin Maben, Piyush Sancheti, and Hany Elhak examine some of the top chip design considerations for medical devices and why they require careful analysis of power to reduce the number surgeries to replace batteries, reliability for devices that can be expected to last for ten years or more, and security to protect private medical data and prevent breaches. Siemens' Chris Spear exp... » read more

What Is UCIe?


The semiconductor industry is undertaking a major strategy shift towards multi-die systems. The shift is fueled by several converging trends: Size of monolithic SoCs is becoming too big for manufacturability Some SoC functionalities may require different process nodes for optimal implementation Desire for enhanced product scalability and composability is increasing Multi-die syste... » read more

Rethinking Machine Learning For Power


The power consumed by machine learning is exploding, and while advances are being made in reducing the power consumed by them, model sizes and training sets are increasing even faster. Even with the introduction of fabrication technology advances, specialized architectures, and the application of optimization techniques, the trend is disturbing. Couple that with the explosion in edge devices... » read more

← Older posts Newer posts →