Author's Latest Posts


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

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

Improving Accuracy In Satellite Navigation Systems


Increasing dependency on the global navigation satellite system (GNSS) constellations is raising concerns about what happens when signals are unavailable, even for short periods of time. GNSS systems affect our daily lives in ways we often don’t see, from location services to cell phone timing. In fact, these satellites have become a necessary part of critical infrastructure, and higher ac... » read more

Will Co-Packaged Optics Replace Pluggables?


As optical connections work their way deeper into the data center, a debate is underway. Is it better to use pluggable optical modules or to embed lasers deep into advanced packages? There are issues of convenience, power, and reliability driving the discussion, and an eventual winner isn’t clear yet. “The industry is definitely embracing co-packaged optics,” said James Pond, principal... » read more

PCB And IC Technologies Meet In The Middle


Surface-mount technology (SMT) is evolving far beyond its roots as a way of assembling packaged chips onto printed circuit boards without through-holes. It is now moving inside packages that will themselves be mounted on PCBs. But SMT for advanced packages isn’t the same as the SMT we’ve been used to. “Many systems include multiple ASICs, a lot of memory, and that's all integrated i... » read more

Competing Auto Sensor Fusion Approaches


As today’s internal-combustion engines are replaced by electric/electronic vehicles, mechanical-system sensors will be supplanted by numerous electronic sensors both for efficient operation and for achieving various levels of autonomy. Some of these new sensors will operate alone, but many prominent ones will need their outputs combined — or “fused” — with the outputs of other sensor... » read more

Will Monolithic 3D DRAM Happen?


As DRAM scaling slows, the industry will need to look for other ways to keep pushing for more and cheaper bits of memory. The most common way of escaping the limits of planar scaling is to add the third dimension to the architecture. There are two ways to accomplish that. One is in a package, which is already happening. The second is to sale the die into the Z axis, which which has been a to... » read more

New Memories Add New Faults


New non-volatile memories (NVM) bring new opportunities for changing how we use memory in systems-on-chip (SoCs), but they also add new challenges for making sure they will work as expected. These new memory types – primarily MRAM and ReRAM – rely on unique physical phenomena for storing data. That means that new test sequences and fault models may be needed before they can be released t... » read more

Will Automotive Ethernet Win?


As internal combustion engines are replaced by electric motors, and mechanical linkages increasingly replaced by electronic messaging, an in-vehicle network is needed to facilitate communication. Ethernet, amended for automotive and other time-sensitive applications, appears to be the network of choice. But is that choice a done deal? And will Ethernet replace all other in-car networks? The ... » read more

Why TinyML Is Such A Big Deal


While machine-learning (ML) development activity most visibly focuses on high-power solutions in the cloud or medium-powered solutions at the edge, there is another collection of activity aimed at implementing machine learning on severely resource-constrained systems. Known as TinyML, it’s both a concept and an organization — and it has acquired significant momentum over the last year or... » read more

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