Is Advanced Packaging The Next SoC?


Device scaling appears to be possible down to 1.2nm, and maybe even beyond that. What isn't obvious is when scaling will reach that node, how many companies will actually use it, or even what chips will look like when foundries actually start turning out these devices using multi-patterning with high-NA EUV and dielectrics with single-digit numbers of atoms. There are two big changes playing... » read more

SM2: A Deep Neural Network Accelerator In 28nm


Deep learning algorithms present an exciting opportunity for efficient VLSI implementations due to several useful properties: (1) an embarrassingly parallel dataflow graph, (2) significant sparsity in model parameters and intermediate results, and (3) resilience to noisy computation and storage. Exploiting these characteristics can offer significantly improved performance and energy efficiency.... » read more

Who Will Regulate Technology?


Outside regulation and technological innovation don't mix well, particularly when it comes to modern electronics, but the potential for that kind of oversight is rising. In the past, most of the problems involving regulation stemmed from a lack of understanding about technology and science. This is hardly a new phenomenon. It literally dates back centuries. Galileo was forced to recant helio... » read more

Deconstructing Deep Learning


I discuss AI and deep learning a lot these days. The discussion usually comes back to “what is a deep learning chip?” These devices are basically hardware implementations of neural networks. While neural nets have been around for a while, what’s new is the performance advanced semiconductor technology brings to the party. Applications that function in real time are now possible. But wh... » read more

Using Data Mining Differently


The semiconductor industry generates a tremendous quantity of data, but until very recently engineers had to sort through it on their own to spot patterns, trends and aberrations. That's beginning to change as chipmakers develop their own solutions or partner with others to effectively mine this data. Adding some structure and automation around all of this data is long overdue. Data mining h... » read more

Transistor Options Beyond 3nm


Despite a slowdown in chip scaling amid soaring costs, the industry continues to search for a new transistor type 5 to 10 years out—particularly for the 2nm and 1nm nodes. Specifically, the industry is pinpointing and narrowing down the transistor options for the next major nodes after 3nm. Those two nodes, called 2.5nm and 1.5nm, are slated to appear in 2027 and 2030, respectively, accord... » read more

System Bits: Feb. 13


Enabling individual manufacturing apps Researchers at the Fraunhofer Institute for Computer Graphics Research IGD focused on Industrie 4.0 recognize that manufacturing is turning toward batch sizes of one and individualized production in what is sometimes referred to as ‘highly customized mass production.’ [caption id="attachment_24131609" align="aligncenter" width="300"] The scanning ... » read more

The Race To Accelerate


Geoff Tate, CEO of [getentity id="22921" e_name="Flex Logix"], sat down with Semiconductor Engineering to discuss how the chip industry is changing, why that bodes well for embedded FPGAs, and what you need to be aware of when using programmable logic on the same die as other devices. What follows are excerpts of that conversation. SE: What are the biggest challenges facing the chip industry... » read more

Customizing Power And Performance


Designing chips is getting more difficult, and not just for the obvious technical reasons. The bigger issue revolves around what these chips going to be used for-and how will they be used, both by the end user and in the context of other electronics. This was a pretty simple decision when hardware was developed somewhat independently of software, such as in the PC era. Technology generally d... » 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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