Copper TSV-Based Die-Level Via-Last 3D Integration Process with Parylene-C Adhesive Bonding Technique

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Embedded memories occupy an increasingly dominant part of the area and power budgets of modern systems-on-chips (SoCs). Multi-ported embedded memories, commonly used by media SoCs and graphical processing units, occupy even more area and consume higher pow ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

Addressing the environmental impact of electronic waste in biomedical sensing, an eco-conscious approach to the realization of a Chitosan-based Acetone sensor tag for wireless gas monitoring is presented. The fabrication involves inkjet printing of silver ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

Modern hardware is increasingly complex, requiring increasing effort to understand in order to carefully engineer systems for optimal performance and effective utilization. Moreover, established design principles and assumptions are not portable to modern ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

In order to develop sustainable and more powerful information technology (IT) infrastructures, the challenges posed by the "memory wall" are critical for the design of high-performance and high-efficiency many-core computing systems. In this context, recen ...

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...

Utilization of edge devices has exploded in the last decade, with such use cases as wearable devices, autonomous driving, and smart homes. As their ubiquity grows, so do expectations of their capabilities. Simultaneously, their formfactor and use cases lim ...

We present here, for the first time, a fabrication technique that allows manufacturing scallop free, non-tapered, high aspect ratio in through-silicon vias (TSVs) on silicon wafers. TSVs are among major technology players in modern high-volume manufacturin ...

A random access memory having a memory array having a plurality of local memory groups, each local memory group including a plurality of bitcells arranged in a bitcell column, a pair of local bitlines operatively connected to the plurality of bitcells, a p ...

This paper presents the set of simulation means used to develop the concept of N2C2 (neural network compute cube) based on a vertical transistor technology platform. On the basis of state-of-the-art junctionless nanowire transistors (JLNT), TCAD simulation ...

Harnessing quantum randomness for the generation of random numbers is an important concept crucial for information security and many other computer-related applications. Quantum random number generators (QRNGs) are evolving from bulky, slow, and expensive ...

Even if Dennard scaling came to an end fifteen years ago, Moore' s law kept fueling an exponential growth in compute performance through increased parallelization. However, the performance of memory and, in particular, Dynamic Random Access Memory (DRAM), ...

A burst image sensor named Hanabi, meaning fireworks in Japanese, includes a branching CCD and multiple CMOS readout circuits. The sensor is backside-illuminated with a light/charge guide pipe to minimize the temporal resolution by suppressing the horizont ...

This thesis aims to explore and exploit trade-offs in integrated circuits and systems to overcome the fundamental bottlenecks faced by future data acquisition and communication systems. Specifically, we target the emerging implantable neurotechnology and t ...

Next generation workloads, such as genome sequencing, have an astounding impact in the healthcare sector. Sequence alignment, the first step in genome sequencing, has experienced recent breakthroughs, which resulted in next generation sequencing (NGS). As ...

The rise of data-intensive applications has resulted in an increasing demand for high-density and low-power on-chip embedded memories. Gain-cell embedded DRAM (GC-eDRAM) is a logic-compatible alternative to conventional static random access memory (SRAM) w ...

Embedded memories, mostly implemented with static random access memory (SRAM), dominate the area and power of integrated circuits. Gain-cell embedded DRAM (GC-eDRAM) is an alternative to SRAM due to its high density, low power consumption, and two-ported f ...

Copper TSV-Based Die-Level Via-Last 3D Integration Process with Parylene-C Adhesive Bonding Technique

Chattez avec Graph Search

Multi-Ported GC-eDRAM Bitcell with Dynamic Port Configuration and Refresh Mechanism

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Eco-Conscious Approach to Wireless Gas Monitoring With a Hybrid Printed Passive Sensor Tag

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Chaosity: Understanding Contemporary NUMA-architectures

Rebooting Virtual Memory with Midgard

Full System Exploration of On-Chip Wireless Communication on Many-Core Architectures

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

In-Memory Hardware and Architectural Extensions for Workloads Acceleration

The Michelangelo step: removing scalloping and tapering effects in high aspect ratio through silicon vias

Memory chip or memory array for wide-voltage range in-memory computing using bitline technology

Modelling of vertical and ferroelectric junctionless technology for efficient 3D neural network compute cube dedicated to embedded artificial intelligence

Random flip-flop: adding quantum randomness to digital circuits for improved cyber security, artificial intelligence and more

Miss-Optimized Memory Systems: Turning Thousands of Outstanding Misses into Reuse Opportunities

A Pixel Design of a Branching Ultra-Highspeed Image Sensor

Resource Trade-Offs in Circuits and Systems: from Neurotechnology to Communications

Genome Sequence Alignment - Design Space Exploration for Optimal Performance and Energy Architectures

Current-Based Data-Retention-Time Characterization of Gain-Cell Embedded DRAMs Across the Design and Variations Space

Replica Bit-Line Technique for Internal Refresh in Logic-Compatible Gain-Cell Embedded DRAM