category: AI/ML/DL

category: IoT, Security & Automotive

Electrochemical RAM Cross-Point Arrays For An Analog DL Accelerator
By Technical Paper Link - 13 Aug, 2024 - Comments: 0

A technical paper titled “Retention-aware zero-shifting technique for Tiki-Taka algorithm-based analog deep learning accelerator” was published by researchers at Pohang University of Science and Technology, Korea University, and Kyungpook National University. "We present the fabrication of 4 K-scale electrochemical random-access memory (ECRAM) cross-point arrays for analog neural network... » read more

Survey of Energy Efficient PIM Processors
By Technical Paper Link - 01 Aug, 2024 - Comments: 0

A new technical paper titled "Survey of Deep Learning Accelerators for Edge and Emerging Computing" was published by researchers at University of Dayton and the Air Force Research Laboratory. Abstract "The unprecedented progress in artificial intelligence (AI), particularly in deep learning algorithms with ubiquitous internet connected smart devices, has created a high demand for AI compu... » read more

MTJ-Based CRAM Array
By Technical Paper Link - 01 Aug, 2024 - Comments: 0

A new technical paper titled "Experimental demonstration of magnetic tunnel junction-based computational random-access memory" was published by researchers at University of Minnesota and University of Arizona, Tucson. Abstract "The conventional computing paradigm struggles to fulfill the rapidly growing demands from emerging applications, especially those for machine intelligence because ... » read more

Co-optimizing HW Architecture, Memory Footprint, Device Placement And Per-Chip Operator Scheduling (Georgia Tech, Microsoft)
By Technical Paper Link - 28 Jul, 2024 - Comments: 0

A technical paper titled “Integrated Hardware Architecture and Device Placement Search” was published by researchers at Georgia Institute of Technology and Microsoft Research. Abstract: "Distributed execution of deep learning training involves a dynamic interplay between hardware accelerator architecture and device placement strategy. This is the first work to explore the co-optimization ... » read more

6G And Beyond: Overall Vision And Survey of Research
By Technical Paper Link - 16 Jul, 2024 - Comments: 0

A new 92 page technical paper titled "6G: The Intelligent Network of Everything -- A Comprehensive Vision, Survey, and Tutorial" was published by IEEE researchers at Finland's University of Oulu. Abstract "The global 6G vision has taken its shape after years of international research and development efforts. This work culminated in ITU-R's Recommendation on "IMT-2030 Framework". While the d... » read more

In Situ Backpropagation Strategy That Progressively Updates Neural Network Layers Directly in HW (TU Eindhoven)
By Technical Paper Link - 16 Jul, 2024 - Comments: 0

A new technical paper titled "Hardware implementation of backpropagation using progressive gradient descent for in situ training of multilayer neural networks" was published by researchers at Eindhoven University of Technology. Abstract "Neural network training can be slow and energy-expensive due to the frequent transfer of weight data between digital memory and processing units. Neuromorp... » read more

Roadmap To Neuromorphic Computing (Collaboration of 27 Universities/Companies)
By Technical Paper Link - 09 Jul, 2024 - Comments: 0

A technical paper titled “Roadmap to Neuromorphic Computing with Emerging Technologies” was published by researchers at University College London, Politecnico di Milano, Purdue University, ETH Zurich and numerous other institutions. Summary: "The roadmap is organized into several thematic sections, outlining current computing challenges, discussing the neuromorphic computing approach, ana... » read more

Lower Energy, High Performance LLM on FPGA Without Matrix Multiplication
By Technical Paper Link - 27 Jun, 2024 - Comments: 0

A new technical paper titled "Scalable MatMul-free Language Modeling" was published by UC Santa Cruz, Soochow University, UC Davis, and LuxiTech. Abstract "Matrix multiplication (MatMul) typically dominates the overall computational cost of large language models (LLMs). This cost only grows as LLMs scale to larger embedding dimensions and context lengths. In this work, we show that MatMul... » read more

A Memory Device With MoS2 Channel For High-Density 3D NAND Flash-Based In-Memory Computing
By Technical Paper Link - 26 Jun, 2024 - Comments: 0

A technical paper titled “Low-Power Charge Trap Flash Memory with MoS2 Channel for High-Density In-Memory Computing" was published by researchers at Kyungpook National University, Sungkyunkwan University, Dankook University, and Kwangwoon University. Abstract: "With the rise of on-device artificial intelligence (AI) technology, the demand for in-memory computing has surged for data-intensiv... » read more

ML Method To Predict IR Drop Levels
By Technical Paper Link - 21 Jun, 2024 - Comments: 0

A new technical paper titled "IR drop Prediction Based on Machine Learning and Pattern Reduction" was published by researchers at National Tsing Hua University, National Taiwan University of Science and Technology, and MediaTek. Abstract (partial) "In this paper, we propose a machine learning-based method to predict IR drop levels and present an algorithm for reducing simulation patterns, w... » read more

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