tag: deep learning

Using Deep Learning to Secure The CAN Bus From Advanced Intrusion Attacks
By Technical Paper Link - 03 Oct, 2023 - Comments: 0

A technical paper titled “CANShield: Deep Learning-Based Intrusion Detection Framework for Controller Area Networks at the Signal-Level” was published by researchers at Virginia Tech and others. "As modern vehicles become more connected to external networks, the attack surface of the CAN bus system grows drastically. To secure the CAN bus from advanced intrusion attacks, we propose a sig... » read more

When And Where To Implement AI/ML In Fabs
By Anne Meixner - 21 Sep, 2023 - Comments: 0

Deciphering complex interactions between variables is where machine learning and deep learning shine, but figuring out exactly how ML-based systems will be most useful is the job of engineers. The challenge is in pairing their domain expertise with available ML tools to maximize the value of both. This depends on sufficient quantities of good data, highly optimized algorithms, and proper tra... » read more

Automotive Intrusion Detection Methodologies (TU Denmark)
By Technical Paper Link - 06 Sep, 2023 - Comments: 0

A new technical paper titled "Intrusion Detection in the Automotive Domain: A Comprehensive Review" was published by researchers at DTU Compute Technical University of Denmark Abstract "The automotive domain has realized amazing advancements in communication, connectivity, and automation— and at a breakneck pace. Such advancements come with ample benefits, such as the reduction of traffic... » read more

Chiplets: Bridging The Gap Between The System Requirements And Design Aggregation, Planning, And Optimization
By Technical Paper Link - 14 Jun, 2023 - Comments: 0

A technical paper titled “System and Design Technology Co-optimization of Chiplet-based AI Accelerator with Machine Learning” was published by researchers at Auburn University. Abstract: "With the availability of advanced packaging technology and its attractive features, the chiplet-based architecture has gained traction among chip designers. The large design space and the lack of sys... » read more

A PIM Architecture That Supports Floating Point-Precision Computations Within The Memory Chip
By Technical Paper Link - 07 Jun, 2023 - Comments: 0

A technical paper titled “FlutPIM: A Look-up Table-based Processing in Memory Architecture with Floating-point Computation Support for Deep Learning Applications” was published by researchers at Rochester Institute of Technology and George Mason University. Abstract: "Processing-in-Memory (PIM) has shown great potential for a wide range of data-driven applications, especially Deep Learnin... » read more

Improving Image Resolution At The Edge
By Ed Sperling - 30 May, 2023 - Comments: 0

How much cameras see depends on how accurately the images are rendered and classified. The higher the resolution, the greater the accuracy. But higher resolution also requires significantly more computation, and it requires flexibility in the design to be able to adapt to new algorithms and network models. Jeremy Roberson, technical director and software architect for AI/ML at Flex Logix, talks... » read more

RL-Guided Detailed Routing Framework for Advanced Custom Circuits
By Technical Paper Link - 19 May, 2023 - Comments: 0

A technical paper titled "Reinforcement Learning Guided Detailed Routing for Custom Circuits" was published by researchers at UT Austin, Princeton University, and NVIDIA. "This paper presents a novel detailed routing framework for custom circuits that leverages deep reinforcement learning to optimize routing patterns while considering custom routing constraints and industrial design rules. C... » read more

Hyperscale HW Optimized Neural Architecture Search (Google)
By Technical Paper Link - 21 Apr, 2023 - Comments: 0

A new technical paper titled "Hyperscale Hardware Optimized Neural Architecture Search" was published by researchers at Google, Apple, and Waymo. "This paper introduces the first Hyperscale Hardware Optimized Neural Architecture Search (H2O-NAS) to automatically design accurate and performant machine learning models tailored to the underlying hardware architecture. H2O-NAS consists of three ... » read more

3D-IC: Operator Learning Framework For Ultra-Fast 3D Chip Thermal Prediction Under Multiple Chip Design Configurations
By Technical Paper Link - 24 Mar, 2023 - Comments: 0

A new technical paper titled "DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC Design" was published (preprint) by researchers at UCSB and Cadence. Abstract "Thermal issue is a major concern in 3D integrated circuit (IC) design. Thermal optimization of 3D IC often requires massive expensive PDE simulations. Neural network-based thermal prediction models can perform ... » read more

Co-Design View of Cross-Bar Based Compute-In-Memory
By Technical Paper Link - 15 Mar, 2023 - Comments: 0

A new review paper titled "Compute in-Memory with Non-Volatile Elements for Neural Networks: A Review from a Co-Design Perspective" was published by researchers at Argonne National Lab, Purdue University, and Indian Institute of Technology Madras. "With an over-arching co-design viewpoint, this review assesses the use of cross-bar based CIM for neural networks, connecting the material proper... » read more

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