MRAM Evolves In Multiple Directions


Magnetoresistive RAM (MRAM) is one of several new non-volatile memory technologies targeting broad commercial availability, but designing MRAM into chips and systems isn't as simple as adding other types of memory. MRAM isn’t an all-things-for-all-applications technology. It needs to be tuned for its intended purpose. MRAMs targeting flash will not do as well targeting SRAMs, and vice vers... » read more

Usage Models Driving Data Center Architecture Changes


Data center architectures are undergoing a significant change, fueled by more data and much greater usage from remote locations. Part of this shift involves the need to move some processing closer to the various memory hierarchies, from SRAM to DRAM to storage. There is more data to process, and it takes less energy and time to process that data in place. But workloads also are being distrib... » read more

Fearless Chip Forecasts For 2021


It’s been a roller coaster ride in the semiconductor industry. In early 2020, the semiconductor business looked bright, but then the Covid-19 pandemic struck, causing a sudden downturn. By mid-2020, though, the market bounced back, as the stay-at-home economy drove demand for computers, tablets and TVs. The chip market ended on a high note in 2020, but the question is, what’s in store fo... » read more

Hidden Costs In Faster, Low-Power AI Systems


Chipmakers are building orders of magnitude better performance and energy efficiency into smart devices, but to achieve those goals they also are making tradeoffs that will have far-reaching, long-lasting, and in some cases unknown impacts. Much of this activity is a direct result of pushing intelligence out to the edge, where it is needed to process, sort, and manage massive increases in da... » read more

More Data, More Memory-Scaling Problems


Memories of all types are facing pressures as demands grow for greater capacity, lower cost, faster speeds, and lower power to handle the onslaught of new data being generated daily. Whether it's well-established memory types or novel approaches, continued work is required to keep scaling moving forward as our need for memory grows at an accelerating pace. “Data is the new economy of this ... » read more

Five Key Changes Coming With DDR5 DIMMs


On July 14th of last year, JEDEC announced the publication of the DDR5 SDRAM standard. This signaled the nearing industry transition to DDR5 server dual-inline memory modules (DIMM). DDR5 memory brings a number of key enhancements that will bring great performance and power benefits in next generation servers. Scaling Data Rates to 6.4 Gb/s You can never have enough memory bandwidth, and DD... » read more

Process Window Optimization Of DRAM By Virtual Fabrication


New integration and patterning schemes used in 3D memory and logic devices have created manufacturing and yield challenges. Industrial focus has shifted from the scaling of predictable unit processes in 2D structures to the more challenging full integration of complex 3D structures. Conventional 2D layout DRC, offline wafer metrology, and offline electrical measurements are no longer sufficient... » read more

What Designers Need to Know About Error Correction Code (ECC) In DDR Memories


As with any electronic system, errors in the memory subsystem are possible due to design failures/defects or electrical noise in any one of the components. These errors are classified as either hard-errors (caused by design failures) or soft-errors (caused by system noise or memory array bit flips due to alpha particles, etc.). To handle these memory errors during runtime, the memory subsyst... » read more

Pushing The Envelope With HBM2E Memory


In September, Rambus announced the achievement of reaching 4 gigabits per second (Gbps) operation with our HBM2E memory interface. This milestone was demonstrated in silicon and required mastering substantial signal integrity and power integrity (SI/PI) challenges. The 4 Gbps mark represents a 20% rise from the previous maximum data rate of 3.2 Gbps for HBM2E. To date, the industry’s faste... » read more

Tapping Into Purpose-Built Neural Network Models For Even Bigger Efficiency Gains


Neural networks can be categorized as a set of algorithms modelled loosely after the human brain that can ‘learn’ by incorporating new data. Indeed, many benefits can be derived from developing purpose-built “computationally efficient” neural network models. However, to ensure your model is effective, there are several key requirements that need to be considered. One critical conside... » read more

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