Large-Scale Integration Of 2D Materials As The Semiconducting Channel In An In-Memory Processor (EPFL)


A technical paper titled “A large-scale integrated vector-matrix multiplication processor based on monolayer molybdenum disulfide memories” was published by researchers at École Polytechnique Fédérale de Lausanne (EPFL). Abstract: "Data-driven algorithms—such as signal processing and artificial neural networks—are required to process and extract meaningful information from the mass... » read more

Environmentally Sustainable FPGAs (Notre Dame, Univ. of Pittsburgh)


A new technical paper titled "REFRESH FPGAs: Sustainable FPGA Chiplet Architectures" was published by University of Notre Dame and University of Pittsburgh. Abstract "There is a growing call for greater amounts of increasingly agile computational power for edge and cloud infrastructure to serve the computationally complex needs of ubiquitous computing devices. Thus, an important challenge i... » read more

Mixed SRAM And eDRAM Cell For Area And Energy-Efficient On-Chip AI Memory (Yale Univ.)


A new technical paper titled "MCAIMem: a Mixed SRAM and eDRAM Cell for Area and Energy-efficient on-chip AI Memory" was published by researchers at Yale University. Abstract: "AI chips commonly employ SRAM memory as buffers for their reliability and speed, which contribute to high performance. However, SRAM is expensive and demands significant area and energy consumption. Previous studies... » read more

Analog Planar Memristor Device: Developing, Designing, and Manufacturing


A new technical paper titled "Analog monolayer SWCNTs-based memristive 2D structure for energy-efficient deep learning in spiking neural networks" was published by researchers at Delft University of Technology and Khalifa University. Abstract: "Advances in materials science and memory devices work in tandem for the evolution of Artificial Intelligence systems. Energy-efficient computation... » read more

Memory Devices-Based Bayesian Neural Networks For Edge AI


A new technical paper titled "Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks" was published by researchers at Université Grenoble Alpes, CEA, LETI, and CNRS. Abstract: "Safety-critical sensory applications, like medical diagnosis, demand accurate decisions from limited, noisy data. Bayesian neural networks excel at such tasks, offering... » read more

A Survey Of Recent Advances In Spiking Neural Networks From Algorithms To HW Acceleration


A technical paper titled “Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural networks: from Algorithms to Technology” was published by researchers at Intel Labs, University of California Santa Cruz, University of Wisconsin-Madison, and University of Southern California. Abstract: "Neuromorphic computing and, in particular, spiking neural networks (SNNs) have becom... » read more

Dual Instruction-Set Architecture, Supporting A TTA And RISC-V Instruction Set Via a Lightweight Microcode Hardware Unit


A technical paper titled “Energy-Efficient Exposed Datapath Architecture With a RISC-V Instruction Set Mode” was published by researchers at Tampere University. Abstract: "Transport triggered architectures (TTAs) follow the static programming model of very long instruction word (VLIW) processors but expose additional information of the processor datapath in the programming interface, whic... » read more

Enabling Scalable Accelerator Design On Distributed HBM-FPGAs (UCLA)


A technical paper titled “TAPA-CS: Enabling Scalable Accelerator Design on Distributed HBM-FPGAs” was published by researchers at University of California Los Angeles. Abstract: "Despite the increasing adoption of Field-Programmable Gate Arrays (FPGAs) in compute clouds, there remains a significant gap in programming tools and abstractions which can leverage network-connected, cloud-scale... » read more

Lego-Like Photonics Chip With Expanded RF Bandwidth And Advanced Filter Control


A technical paper titled “Integrated microwave photonic notch filter using a heterogeneously integrated Brillouin and active-silicon photonic circuit” was published by researchers at University of Sydney and Australian National University. Abstract: "Microwave photonics (MWP) has unlocked a new paradigm for Radio Frequency (RF) signal processing by harnessing the inherent broadband and tu... » read more

Chiplet Architecture: Scalable and Cost-Efficient Systems for Irregular Applications (Princeton)


A new technical paper titled "DCRA: A Distributed Chiplet-based Reconfigurable Architecture for Irregular Applications" was published by researchers at Princeton University. Abstract "In recent years, the growing demand to process large graphs and sparse datasets has led to increased research efforts to develop hardware- and software-based architectural solutions to accelerate them. While... » read more

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