tag: memory

Standards for the Characterization of Endurance in Resistive Switching Devices
By Technical Paper Link - 03 Nov, 2021 - Comments: 0

Abstract "Resistive switching (RS) devices are emerging electronic components that could have applications in multiple types of integrated circuits, including electronic memories, true random number generators, radiofrequency switches, neuromorphic vision sensors, and artificial neural networks. The main factor hindering the massive employment of RS devices in commercial circuits is related to... » read more

HBM3: Big Impact On Chip Design
By Ann Mutschler - 14 Oct, 2021 - Comments: 0

An insatiable demand for bandwidth in everything from high-performance computing to AI training, gaming, and automotive applications is fueling the development of the next generation of high-bandwidth memory. HBM3 will bring a 2X bump in bandwidth and capacity per stack, as well as some other benefits. What was once considered a "slow and wide" memory technology to reduce signal traffic dela... » read more

Multi-DRAM Memory Subsystems In SoCs
By Shyam Sharma - 14 Oct, 2021 - Comments: 0

Even with DRAM capacity going up with each generation of DRAM, the demand for memory densities by a variety of applications is growing at an even faster rate. To support these high memory densities and bus width requirements (that are typically more than what a single DRAM can support), almost all the new generation of memory subsystems and SoCs have multiple DRAM dies combined to effectively c... » read more

HBM3 Memory: Break Through To Greater Bandwidth
By Rambus - 06 Oct, 2021 - Comments: 0

AI/ML’s demands for greater bandwidth are insatiable driving rapid improvements in every aspect of computing hardware and software. HBM memory is the ideal solution for the high bandwidth requirements of AI/ML training, but it entails additional design considerations given its 2.5D architecture. Now we’re on the verge of a new generation of HBM that will raise memory and capacity to new hei... » read more

Modeling electrical conduction in resistive-switching memory through machine learning
By Technical Paper Link - 04 Oct, 2021 - Comments: 0

Published in AIP Advances on July 13, 2021. Read the full paper (open access). Abstract Traditional physical-based models have generally been used to model the resistive-switching behavior of resistive-switching memory (RSM). Recently, vacancy-based conduction-filament (CF) growth models have been used to model device characteristics of a wide range of RSM devices. However, few have focused o... » read more

On the Road To Higher Memory Bandwidth
By Frank Ferro - 09 Sep, 2021 - Comments: 0

In the decade since HBM was first announced, we’ve seen two-and-a-half generations of the standard come to market. HBM’s “wide and slow” architecture debuted first at a data rate of 1 gigabit per second (Gbps) running over a 1024-bit wide interface. The product of that data rate and that interface width provided a bandwidth of 128 gigabytes per second (GB/s). In 2016, HBM2 doubled the s... » read more

Will Monolithic 3D DRAM Happen?
By Bryon Moyer - 09 Sep, 2021 - Comments: 1

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
By Bryon Moyer - 07 Sep, 2021 - Comments: 1

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

Why TinyML Is Such A Big Deal
By Bryon Moyer - 02 Sep, 2021 - Comments: 1

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

A New Vision For Memory Chip Design And Verification
By Anand Thiruvengadam - 02 Sep, 2021 - Comments: 0

Discrete memory chips are arguably the most visible reminder of the opportunities and challenges for advanced semiconductor design. They are manufactured in huge quantities, becoming key drivers for new technology nodes and new fabrication processes. Price fluctuations have a major impact on the financial health of the electronics industry, and any shortages can shut down the manufacturing line... » read more

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