category: AI/ML/DL

category: IoT, Security & Automotive

Memory-Computation Decoupling Execution To Achieve Ideal All-Bank PIM Performance
By Technical Paper Link - 18 Oct, 2022 - Comments: 0

A new technical paper titled "Achieving the Performance of All-Bank In-DRAM PIM With Standard Memory Interface: Memory-Computation Decoupling" was published by researchers at Korea University. "This paper proposed the memory-computation decoupled PIM architecture to provide the performance comparable to the all-bank PIM while preserving the standard DRAM interface, i.e., DRAM commands, powe... » read more

Nonvolatile ECRAM With A Short-Circuit Retention Time Several Orders of Magnitude Higher Than Previously Shown
By Technical Paper Link - 18 Oct, 2022 - Comments: 0

A new technical paper titled "Nonvolatile Electrochemical Random-Access Memory Under Short Circuit" was published by researchers at University of Michigan and Sandia National Laboratories. Abstract "Electrochemical random-access memory (ECRAM) is a recently developed and highly promising analog resistive memory element for in-memory computing. One longstanding challenge of ECRAM is attainin... » read more

Hardware Platform Based on 2D Memtransistors
By Technical Paper Link - 15 Oct, 2022 - Comments: 0

A new technical paper titled "Hardware implementation of Bayesian network based on two-dimensional memtransistors" from researchers at Penn State University. "In this work, we demonstrate hardware implementation of a BN [Bayesian networks] using a monolithic memtransistor technology based on two-dimensional (2D) semiconductors such as monolayer MoS2. First, we experimentally demonstrate a lo... » read more

Training a ML model On An Intelligent Edge Device Using Less Than 256KB Memory
By Technical Paper Link - 11 Oct, 2022 - Comments: 0

A new technical paper titled "On-Device Training Under 256KB Memory" was published by researchers at MIT and MIT-IBM Watson AI Lab. “Our study enables IoT devices to not only perform inference but also continuously update the AI models to newly collected data, paving the way for lifelong on-device learning. The low resource utilization makes deep learning more accessible and can have a bro... » read more

More Efficient Matrix-Multiplication Algorithms with Reinforcement Learning (DeepMind)
By Technical Paper Link - 11 Oct, 2022 - Comments: 0

A new research paper titled "Discovering faster matrix multiplication algorithms with reinforcement learning" was published by researchers at DeepMind. "Here we report a deep reinforcement learning approach based on AlphaZero for discovering efficient and provably correct algorithms for the multiplication of arbitrary matrices," states the paper. Find the technical paper link here. Publis... » read more

Speeding-Up Thermal Simulations Of Chips With ML
By Technical Paper Link - 02 Oct, 2022 - Comments: 0

A new technical paper titled "A Thermal Machine Learning Solver For Chip Simulation" was published by researchers at Ansys. Abstract "Thermal analysis provides deeper insights into electronic chips' behavior under different temperature scenarios and enables faster design exploration. However, obtaining detailed and accurate thermal profile on chip is very time-consuming using FEM or CFD. Th... » read more

Adaptive Memristive Hardware
By Technical Paper Link - 02 Oct, 2022 - Comments: 0

A new technical paper titled "Self-organization of an inhomogeneous memristive hardware for sequence learning" was just published by researchers at University of Zurich, ETH Zurich, Université Grenoble Alpes, CEA, Leti and Toshiba. "We design and experimentally demonstrate an adaptive hardware architecture Memristive Self-organizing Spiking Recurrent Neural Network (MEMSORN). MEMSORN incorp... » read more

Visual Fault Inspection Using A Hybrid System Of Stacked DNNs
By Technical Paper Link - 29 Sep, 2022 - Comments: 0

A technical paper titled "Improving automated visual fault inspection for semiconductor manufacturing using a hybrid multistage system of deep neural networks" was published by researchers at Chemnitz University of Technology (Germany). According to the paper, "this contribution introduces a novel hybrid multistage system of stacked deep neural networks (SH-DNN) which allows the localization... » read more

FP8: Cross-Industry Hardware Specification For AI Training And Inference (Arm, Intel, Nvidia)
By Technical Paper Link - 16 Sep, 2022 - Comments: 0

Arm, Intel, and Nvidia proposed a specification for an 8-bit floating point (FP8) format that could provide a common interchangeable format that works for both AI training and inference and allow AI models to operate and perform consistently across hardware platforms. Find the technical paper titled " FP8 Formats For Deep Learning" here. Published Sept 2022. Abstract: "FP8 is a natural p... » read more

New Method of Comparing Neural Networks (Los Alamos National Lab)
By Technical Paper Link - 13 Sep, 2022 - Comments: 0

A new research paper titled "If You’ve Trained One You’ve Trained Them All: Inter-Architecture Similarity Increases With Robustness" from researchers at Los Alamos National Laboratory (LANL) and was recently presented at the Conference on Uncertainty in Artificial Intelligence. The team developed a new approach for comparing neural networks and "applied their new metric of network simila... » read more

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