Vertical AlGaN Heterostructures For Integrated Photonics


A new technical paper titled "AlGaN/AlN heterostructures: an emerging platform for integrated photonics" was published by researchers at Humboldt-Universität zu Berlin and Ferdinand-Braun-Institut (FBH). Abstract "We introduce a novel material for integrated photonics and investigate aluminum gallium nitride (AlGaN) on aluminum nitride (AlN) templates as a platform for developing reconfig... » read more

Chip Industry Technical Paper Roundup: Jan. 20


New technical papers recently added to Semiconductor Engineering’s library: [table id=398 /] Find all technical papers here. » read more

Research Bits: Jan. 20


Self-correcting memristor array Researchers at Korea Advanced Institute of Science and Technology (KAIST), Seoul National University, Sungkyunkwan University, Electronics and Telecommunications Research Institute (ETRI), and Yonsei University developed a memristor-based neuromorphic chip that can learn and correct errors, enabling it to adapt to immediate environmental changes. The system c... » read more

Design-Space Analysis of M3D FPGA With BEOL Configuration Memories (Georgia Tech, UCLA)


A new technical paper titled "Monolithic 3D FPGAs Utilizing Back-End-of-Line Configuration Memories" was published by researchers at Georgia Tech and UCLA. Abstract "This work presents a novel monolithic 3D (M3D) FPGA architecture that leverages stackable back-end-of-line (BEOL) transistors to implement configuration memory and pass gates, significantly improving area, latency, and power ef... » read more

Chip Industry Week In Review


GlobalFoundries will create a new center for advanced packaging and testing of U.S.-made essential chips within its New York manufacturing facility. A flurry of announcements on advanced semiconductors and AI rolled out this week as U.S. President Biden wrapped up his term: The Biden-Harris Administration released an Interim Final Rule on Artificial Intelligence Diffusion to strengthen ... » read more

Loss Processes in Electrochemically Charged Semiconductor Nanocrystal Films (TU Delft)


A new technical paper titled "Where Do the Electrons Go? Studying Loss Processes in the Electrochemical Charging of Semiconductor Nanomaterials" was published by researchers at Delft University of Technology. Abstract "Electrochemical charging of films of semiconductor nanocrystals (NCs) allows precise control over their Fermi level and opens up new possibilities for use of semiconductor NC... » read more

Advanced Packaging: A Curse Or A Blessing For Trustworthiness?


In recent years, the issue of trustworthiness in electronics has become increasingly important, especially in areas where security is of the essence such as the automotive sector, industry, and critical infrastructure. These sectors depend on electronic systems that are not only powerful but also absolutely reliable and, above all, secure. This represents a major challenge, as the increasing co... » read more

How Ultra Ethernet And UALink Enable High-Performance, Scalable AI Networks


By Ron Lowman and Jon Ames AI workloads are significantly driving innovation in the interface IP market. The exponential increase in AI model parameters, doubling approximately every 4-6 months, stands in stark contrast to the slower pace of hardware advancements dictated by Moore's Law, which follows an 18-month cycle. This discrepancy demands hardware innovations to support AI workloads, c... » read more

Choosing The Right Memory Solution For AI Accelerators


To meet the increasing demands of AI workloads, memory solutions must deliver ever-increasing performance in bandwidth, capacity, and efficiency. From the training of massive large language models (LLMs) to efficient inference on endpoint devices, choosing the right memory technology is critical for chip designers. This blog explores three leading memory solutions—HBM, LPDDR, and GDDR—and t... » read more

MACs Are Not Enough: Why “Offload” Fails


For the past half-decade, countless chip designers have approached the challenges of on-device machine learning inference with the simple idea of building a “MAC accelerator” – an array of high-performance multiply-accumulate circuits – paired with a legacy programmable core to tackle the ML inference compute problem. There are literally dozens of lookalike architectures in the market t... » read more

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