SRAM PUF – The Secure Silicon Fingerprint


For many years, silicon Physical Unclonable Functions (PUFs) have been seen as a promising and innovative security technology making steady progress. Today, Static Random-Access Memory (SRAM)-based PUFs have been deployed in hundreds of millions of devices and offer a mature and viable security component that is achieving widespread adoption in commercial products. They are found in devices ran... » read more

Fine-Grained Functional Partitioning For Low Level SRAM Cache in 3D-IC designs (imec)


A new technical paper titled "Towards Fine-grained Partitioning of Low-level SRAM Caches for Emerging 3D-IC Designs" was published by researchers at imec. "We propose a partitioning of low-level (faster access) caches in 3D using an Array Under CMOS (AuC) technology paradigm. Our study focuses on partitioning and optimization of SRAM bit-cells and peripheral circuits, enabling heterogeneous ... » read more

Memory Fundamentals For Engineers


Memory is one of a very few elite electronic components essential to any electronic system. Modern electronics perform extraordinarily complex duties that would be impossible without memory. Your computer obviously contains memory, but so does your car, your smartphone, your doorbell camera, your entertainment system, and any other gadget benefiting from digital electronics. This eBook prov... » read more

3.5D: The Great Compromise


The semiconductor industry is converging on 3.5D as the next best option in advanced packaging, a hybrid approach that includes stacking logic chiplets and bonding them separately to a substrate shared by other components. This assembly model satisfies the need for big increases in performance while sidestepping some of the thorniest issues in heterogeneous integration. It establishes a midd... » read more

Addressing Quantum Computing Threats With SRAM PUFs


You’ve probably been hearing a lot lately about the quantum-computing threat to cryptography. If so, you probably also have a lot of questions about what this “quantum threat” is and how it will impact your cryptographic solutions. Let’s take a look at some of the most common questions about quantum computing and its impact on cryptography. What is a quantum computer? A quantum comput... » read more

SRAM Security Concerns Grow


SRAM security concerns are intensifying as a combination of new and existing techniques allow hackers to tap into data for longer periods of time after a device is powered down. This is particularly alarming as the leading edge of design shifts from planar SoCs to heterogeneous systems in package, such as those used in AI or edge processing, where chiplets frequently have their own memory hi... » read more

A Design And Benchmarking Study Of CAM At 7nm In The Context Of Similarity Search Applications (Georgia Tech)


A technical paper titled “Cross-layer Modeling and Design of Content Addressable Memories in Advanced Technology Nodes for Similarity Search” was published by researchers at the Georgia Institute of Technology. Abstract: "In this paper we present a comprehensive design and benchmarking study of Content Addressable Memory (CAM) at the 7nm technology node in the context of similarity search... » read more

New Memory Architecture For Local Differential Privacy in Hardware


A technical paper titled "Two Birds with One Stone: Differential Privacy by Low-power SRAM Memory" was published by researchers at North Carolina State University, University of South Alabama, and University of Tennessee. Abstract "The software-based implementation of differential privacy mechanisms has been shown to be neither friendly for lightweight devices nor secure against side-channe... » read more

SRAM Scaling Issues, And What Comes Next


The inability of SRAM to scale has challenged power and performance goals forcing the design ecosystem to come up with strategies that range from hardware innovations to re-thinking design layouts. At the same time, despite the age of its initial design and its current scaling limitations, SRAM has become the workhorse memory for AI. SRAM, and its slightly younger cousin DRAM, have always co... » read more

CiM Integration For ML Inference Acceleration


A technical paper titled “WWW: What, When, Where to Compute-in-Memory” was published by researchers at Purdue University. Abstract: "Compute-in-memory (CiM) has emerged as a compelling solution to alleviate high data movement costs in von Neumann machines. CiM can perform massively parallel general matrix multiplication (GEMM) operations in memory, the dominant computation in Machine Lear... » read more

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