category: AI/ML/DL

category: IoT, Security & Automotive

Agile HW Design: Fully Automatic Equivalence Checking Workflow
By Technical Paper Link - 03 Mar, 2023 - Comments: 0

A new technical paper titled "An Equivalence Checking Framework for Agile Hardware Design" was published by researchers at Portland State University and Intel. Abstract "Agile hardware design enables designers to produce new design iterations efficiently. Equivalence checking is critical in ensuring that a new design iteration conforms to its specification. In this paper, we introduce an eq... » read more

Review of Methods to Design Secure Memristor Computing Systems
By Technical Paper Link - 27 Feb, 2023 - Comments: 0

A technical paper titled "Review of security techniques for memristor computing systems" was published by researchers at Israel Institute of Technology, Friedrich Schiller University Jena (Germany), and Leibniz Institute of Photonic Technology (IPHT). Abstract "Neural network (NN) algorithms have become the dominant tool in visual object recognition, natural language processing, and robotic... » read more

In-Memory Computing: Assessing Multilevel RRAM-Based VMM Operations
By Technical Paper Link - 26 Feb, 2023 - Comments: 0

A new technical paper titled "Experimental Assessment of Multilevel RRAM-Based Vector-Matrix Multiplication Operations for In-Memory Computing" was published by researchers at IHP (the Leibniz Institute for High Performance Microelectronics). Abstract: "Resistive random access memory (RRAM)-based hardware accelerators are playing an important role in the implementation of in-memory computin... » read more

ISA and Microarchitecture Extensions Over Dense Matrix Engines to Support Flexible Structured Sparsity for CPUs (Georgia Tech, Intel Labs)
By Technical Paper Link - 24 Feb, 2023 - Comments: 0

A technical paper titled "VEGETA: Vertically-Integrated Extensions for Sparse/Dense GEMM Tile Acceleration on CPUs" was published (preprint) by researchers at Georgia Tech and Intel Labs. Abstract: "Deep Learning (DL) acceleration support in CPUs has recently gained a lot of traction, with several companies (Arm, Intel, IBM) announcing products with specialized matrix engines accessible v... » read more

HW-SW Co-Design Solution For Building Side-Channel-Protected ML Hardware
By Technical Paper Link - 19 Feb, 2023 - Comments: 0

A technical paper titled "Hardware-Software Co-design for Side-Channel Protected Neural Network Inference" was published (preprint) by researchers at North Carolina State University and Intel. Abstract "Physical side-channel attacks are a major threat to stealing confidential data from devices. There has been a recent surge in such attacks on edge machine learning (ML) hardware to extract the... » read more

Review of Tools & Techniques for DL Edge Inference
By Technical Paper Link - 16 Feb, 2023 - Comments: 0

A new technical paper titled "Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A Review" was published in "Proceedings of the IEEE" by researchers at University of Missouri and Texas Tech University. Abstract: Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted in breakthroughs in many areas. However, deploying thes... » read more

New Method Improves Machine Learning Models’ Reliability, With Less Computing Resources (MIT, U. of Florida, IBM Watson)
By Technical Paper Link - 13 Feb, 2023 - Comments: 0

A new technical paper titled "Post-hoc Uncertainty Learning using a Dirichlet Meta-Model" was published (preprint) by researchers at MIT, University of Florida, and MIT-IBM Watson AI Lab (IBM Research). The work demonstrates how to quantify the level of certainty in its predictions, while using less compute resources. “Uncertainty quantification is essential for both developers and users o... » read more

Heterogeneous Multi-Core HW Architectures With Fine-Grained Scheduling of Layer-Fused DNNs
By Technical Paper Link - 29 Jan, 2023 - Comments: 0

A technical paper titled "Towards Heterogeneous Multi-core Accelerators Exploiting Fine-grained Scheduling of Layer-Fused Deep Neural Networks" was published by researchers at KU Leuven and TU Munich. Abstract "To keep up with the ever-growing performance demand of neural networks, specialized hardware (HW) accelerators are shifting towards multi-core and chiplet architectures. So far, thes... » read more

Efficiently Process Large RM Datasets In Underlying Memory Pool, Disaggregated Over CXL (KAIST)
By Technical Paper Link - 29 Jan, 2023 - Comments: 0

A technical paper titled "Failure Tolerant Training with Persistent Memory Disaggregation over CXL" was published (preprint) by researchers at KAIST and Panmnesia. "TRAININGCXL can efficiently process large-scale recommendation datasets in the pool of disaggregated memory while making training fault tolerant with low overhead," states the paper. Find the technical paper here. or here (IEE... » read more

Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPU (Ecole Polytechnique Montreal, IBM, Mila, CMC)
By Technical Paper Link - 10 Jan, 2023 - Comments: 1

A new technical paper titled "BARVINN: Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPU" was written by researchers at Ecole Polytechnique Montreal, IBM, Mila and CMC Microsystems. It was accepted for publication in the 2023, 28th Asia and South Pacific Design Automation Conference (ASP-DAC 2023) in Japan. Abstract: "We present a DNN accelerator that allows inference at arbitr... » read more

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