What Is An xPU?


Almost every day there is an announcement about a new processor architecture, and it is given a three-letter acronym — TPU, IPU, NPU. But what really distinguishes them? Are there really that many unique processor architectures, or is something else happening? In 2018, John L. Hennessy and David A. Patterson delivered the Turing lecture entitled, "A New Golden Age for Computer Architecture... » read more

Improving Power Efficiency In Ultra-Low Power Designs


Faster data communications in phones and data centers grabs headlines, but many applications don't require the continuous, high-data-rate communications needed for video streaming or image processing. In fact, for many devices, designing for better performance results in wasted energy and sharply curtails the time between battery charges. That is especially true for machine-to-machine (M2M) ... » read more

Changing Server Architectures In The Data Center


Data centers are undergoing a fundamental shift to boost server utilization and improve efficiency, optimizing architectures so available compute resources can be leveraged wherever they are needed. Traditionally, data centers were built with racks of servers, each server providing computing, memory, interconnect, and possibly acceleration resources. But when a server is selected, some of th... » read more

Debugging Embedded Applications


Debugging embedded designs is becoming increasingly difficult as the number of observed and possible interactions between hardware and software continue to grow, and as more features are crammed into chips, packages, and systems. But there also appear to be some advances on this front, involving a mix of techniques, including hardware trace, scan chain-based debug, along with better simulation ... » read more

Enablers And Barriers For Connecting Diverse Data


More data is being collected at every step of the manufacturing process, raising the possibility of combining data in new ways to solve engineering problems. But this is far from simple, and combining results is not always possible. The semiconductor industry’s thirst for data has created oceans of it from the manufacturing process. In addition, semiconductor designs large and small now ha... » read more

More Errors, More Correction in Memories


As memory bit cells of any type become smaller, bit error rates increase due to lower margins and process variation. This can be dealt with using error correction to account for and correct bit errors, but as more sophisticated error-correction codes (ECC) are used, it requires more silicon area, which in turn drives up the cost. Given this trend, the looming question is whether the cost of ... » read more

Coping With Parallel Test Site-to-Site Variation


Testing multiple devices in parallel using the same ATE results in reduced test time and lower costs, but it requires engineering finesse to make it so. Minimizing test measurement variation for each device under test (DUT) is a multi-physics problem, and it's one that is becoming more essential to resolve at each new process node and in multi-chip packages. It requires synchronization of el... » read more

Complex Chips Make Security More Difficult


Semiconductor supply chain management is becoming more complex with many more moving parts as chips become increasingly disaggregated, making it difficult to ensure where parts originated and whether they have been compromised before they are added into advanced chips or packages. In the past, supply chain concerns largely focused primarily on counterfeit parts or gray-market substitutions u... » read more

Improving Medical Image Processing With AI


Machine learning is being integrated with medical image processing, one of the most useful technologies for medical diagnosis and surgery, greatly expanding the amount of useful information that can be gleaned from scan or MRI. For the most part, ML is being used to augment manual processes that medical personnel use today. While the goal is to automate many of these functions, it's not clea... » read more

Easier And Faster Ways To Train AI


Training an AI model takes an extraordinary amount of effort and data. Leveraging existing training can save time and money, accelerating the release of new products that use the model. But there are a few ways this can be done, most notably through transfer and incremental learning, and each of them has its applications and tradeoffs. Transfer learning and incremental learning both take pre... » read more

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