Tootfinder

Microsoft and AMD announce a "strategic, multi-year partnership" to design custom silicon for a number of devices, including next-generation Xbox consoles (Jez Corden/Windows Central)
https://www.windowscentral.com/gaming/xbox

Microsoft and AMD have officially entered a new multi-year partnership for first-party Xbox hardware
Xbox President Sarah Bond shared an update on Xbox consoles today, confirming their ongoing partnership with AMD for first-party hardware, while committing to supporting your existing console library on next-gen systems.

heise übernimmt Hardware-Shop Mindfactory: Bundeskartellamt gibt grünes Licht
Das Bundeskartellamt stimmt der Übernahme von Mindfactory zu. Gute Nachrichten gibt es für Kunden im Vorfeld der Insolvenz.

Foldable iPhone voraus: Apple drängt Entwickler zu flexiblen Apps
Apple schwört Entwickler darauf ein, Apps mit anpassbarer Bedienoberfläche zu bauen. Es geht auch um die Kompatibilität mit Zukunfts-Hardware.

Cool research paper (presented at HARRIS but I finally had time to read the full paper) on hardware reverse engineering education https://dl.acm.org/doi/10.1145/3641554.3701797
According to their fairly extensive survey (section 4, figure 1), my 2014 course on hardware R…

I'm impressed with designers that create flat packed furniture. Crafting a jigsaw puzzle of wood and hardware that assembles into fashionable and sturdy furniture ranks right up there with aerospace engineering.
And then there's this. A shoe cabinet that my wife ordered to fit in our sunroom to hide our hideous footwear that we slip on when we go in the backyard. It came in 18 pieces, plus 8 separate tiny bags of hardware and minimal instructions. Two hours of assembly later, it's virtually the same size in volume as the shipping carton it arrived in. I know there are reasons why it's not shipped complete, but it's still a little irritating.
#things_that_make_me_go_hmmm

Google lädt zur nächsten Pixel-Vorstellung am 20. August 2025
Google verschickt Einladungen zum nächsten Hardware-Event. Erwartet werden neue Pixel-Smartphones, neue Smartwatches und neue Ohrhörer - wie jedes Jahr.

Hey, it’s Monday again. That means we are hosting Tech Pizza Monday again! Same place (Victory Cafe, 440 Bloor St. W.), same time (6 PM), same…actually, the menu changed recently, so the pizza is different than it has been in the past.
Word on the street is that there will definitely be a hardware demo. Cool, right?
#Toronto

Apple seems to be working on adding CUDA support to open-source ML framework MLX, which may mean that code developed using MLX would work with CUDA (Malcolm Owen/AppleInsider)
https://appleinsider.com/articles/25/0

Apple Silicon machine learning code may become more easily portable to Nvidia hardware
A project is trying to cut the cost of making machine learning applications for Nvidia hardware, by developing on an Apple Silicon Mac and exporting it to CUDA.

Learning Before Filtering: Real-Time Hardware Learning at the Detector Level
Bo\v{s}tjan Ma\v{c}ek
https://arxiv.org/abs/2506.11981 https://

Learning Before Filtering: Real-Time Hardware Learning at the Detector Level
Advances in sensor technology and automation have ushered in an era of data abundance, where the ability to identify and extract relevant information in real time has become increasingly critical. Traditional filtering approaches, which depend on a priori knowledge, often struggle to adapt to dynamic or unanticipated data features. Machine learning offers a compelling alternative-particularly when training can occur directly at or near the detector. This paper presents a digital hardware archit…

Solving Distance-Based Optimization Problems Using Optical Hardware
Guangyao Li, Richard Zhipeng Wang, Natalia G. Berloff
https://arxiv.org/abs/2507.11378 …

Solving Distance-Based Optimization Problems Using Optical Hardware
We present a practical approach to solving distance-based optimization problems using optical computing hardware. The objective is to minimize an energy function defined as the weighted sum of squared differences between measured distances and the squared Euclidean distances of point coordinates. By representing coordinates as complex numbers, we map the optimization problem onto optical fields, enabling its solution through either the canonical transformation (CT) method or the gain-based bifu…

BanditWare: A Contextual Bandit-based Framework for Hardware Prediction
Tain\~a Coleman, Hena Ahmed, Ravi Shende, Ismael Perez, \"Ilkay Altinta\c{s}
https://arxiv.org/abs/2506.13730

BanditWare: A Contextual Bandit-based Framework for Hardware Prediction
Distributed computing systems are essential for meeting the demands of modern applications, yet transitioning from single-system to distributed environments presents significant challenges. Misallocating resources in shared systems can lead to resource contention, system instability, degraded performance, priority inversion, inefficient utilization, increased latency, and environmental impact. We present BanditWare, an online recommendation system that dynamically selects the most suitable ha…

Replaced article(s) found for cs.AR. https://arxiv.org/list/cs.AR/new
[1/1]:
Large Language Model Inference Acceleration: A Comprehensive Hardware Perspective

I got talked into trying Meat Church “Holy Voodoo” seasoning today at Blackhawk Hardware by an employee and a customer. Both raved about it. I need a jalapeño enhanced rub to use with my smoked and sautéed veggies.
https://www.meatchurch.com/products/holy-voodoo-seasoning

Holy Voodoo Seasoning

from my link log —
The sorry state of Java deserialization.
https://www.marginalia.nu/log/a_110_java_io/
saved 2024-09-22 https://

Synesthesia of Machines (SoM)-Enhanced Sub-THz ISAC Transmission for Air-Ground Network
Zonghui Yang, Shijian Gao, Xiang Cheng, Liuqing Yang
https://arxiv.org/abs/2506.12831

Synesthesia of Machines (SoM)-Enhanced Sub-THz ISAC Transmission for Air-Ground Network
Integrated sensing and communication (ISAC) within sub-THz frequencies is crucial for future air-ground networks, but unique propagation characteristics and hardware limitations present challenges in optimizing ISAC performance while increasing operational latency. This paper introduces a multi-modal sensing fusion framework inspired by synesthesia of machine (SoM) to enhance sub-THz ISAC transmission. By exploiting inherent degrees of freedom in sub-THz hardware and channels, the framework opt…

Efficient Traffic Classification using HW-NAS: Advanced Analysis and Optimization for Cybersecurity on Resource-Constrained Devices
Adel Chehade, Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino
https://arxiv.org/abs/2506.11319

Efficient Traffic Classification using HW-NAS: Advanced Analysis and Optimization for Cybersecurity on Resource-Constrained Devices
This paper presents a hardware-efficient deep neural network (DNN), optimized through hardware-aware neural architecture search (HW-NAS); the DNN supports the classification of session-level encrypted traffic on resource-constrained Internet of Things (IoT) and edge devices. Thanks to HW-NAS, a 1D convolutional neural network (CNN) is tailored on the ISCX VPN-nonVPN dataset to meet strict memory and computational limits while achieving robust performance. The optimized model attains an accuracy…

Energy-Efficient Digital Design: A Comparative Study of Event-Driven and Clock-Driven Spiking Neurons
Filippo Marostica, Alessio Carpegna, Alessandro Savino, Stefano Di Carlo
https://arxiv.org/abs/2506.13268

Energy-Efficient Digital Design: A Comparative Study of Event-Driven and Clock-Driven Spiking Neurons
This paper presents a comprehensive evaluation of Spiking Neural Network (SNN) neuron models for hardware acceleration by comparing event driven and clock-driven implementations. We begin our investigation in software, rapidly prototyping and testing various SNN models based on different variants of the Leaky Integrate and Fire (LIF) neuron across multiple datasets. This phase enables controlled performance assessment and informs design refinement. Our subsequent hardware phase, implemented on …

Towards real-time additive-free dopamine detection at $10^{-8}$ mM with hardware accelerated platform integrated on camera
Ning Li, Qizhou Wang, Zhao He, Arturo Burguete-Lopez, Fei Xiang, Andrea Fratalocchi
https://arxiv.org/abs/2506.13447

Towards real-time additive-free dopamine detection at $10^{-8}$ mM with hardware accelerated platform integrated on camera
Tracing physiological neurotransmitters such as dopamine (DA) with detection limits down to $\mathrm{1\times10^{-8}}$ mM is a critical goal in neuroscience for studying brain functions and progressing the understanding of cerebral disease. Addressing this problem requires enhancing the current state-of-the-art additive-free electrochemical workstation methods by over two orders of magnitude. In this work, we implement an ultra-sensitive, additive-free platform exploiting suitably engineered lig…

Fault-Free Analog Computing with Imperfect Hardware
Zhicheng Xu, Jiawei Liu, Sitao Huang, Zefan Li, Shengbo Wang, Bo Wen, Ruibin Mao, Mingrui Jiang, Giacomo Pedretti, Jim Ignowski, Kaibin Huang, Can Li
https://arxiv.org/abs/2507.11134

Fault-Free Analog Computing with Imperfect Hardware
The growing demand for edge computing and AI drives research into analog in-memory computing using memristors, which overcome data movement bottlenecks by computing directly within memory. However, device failures and variations critically limit analog systems' precision and reliability. Existing fault-tolerance techniques, such as redundancy and retraining, are often inadequate for high-precision applications or scenarios requiring fixed matrices and privacy preservation. Here, we introduce an…

HyDRA: A Hybrid Dual-Mode Network for Closed- and Open-Set RFFI with Optimized VMD
Hanwen Liu, Yuhe Huang, Yifeng Gong, Yanjie Zhai, Jiaxuan Lu
https://arxiv.org/abs/2507.12133

HyDRA: A Hybrid Dual-Mode Network for Closed- and Open-Set RFFI with Optimized VMD
Device recognition is vital for security in wireless communication systems, particularly for applications like access control. Radio Frequency Fingerprint Identification (RFFI) offers a non-cryptographic solution by exploiting hardware-induced signal distortions. This paper proposes HyDRA, a Hybrid Dual-mode RF Architecture that integrates an optimized Variational Mode Decomposition (VMD) with a novel architecture based on the fusion of Convolutional Neural Networks (CNNs), Transformers, and Ma…

Towards Depth Foundation Model: Recent Trends in Vision-Based Depth Estimation
Zhen Xu, Hongyu Zhou, Sida Peng, Haotong Lin, Haoyu Guo, Jiahao Shao, Peishan Yang, Qinglin Yang, Sheng Miao, Xingyi He, Yifan Wang, Yue Wang, Ruizhen Hu, Yiyi Liao, Xiaowei Zhou, Hujun Bao
https://arxiv.org/abs/2507.11540

Towards Depth Foundation Model: Recent Trends in Vision-Based Depth Estimation
Depth estimation is a fundamental task in 3D computer vision, crucial for applications such as 3D reconstruction, free-viewpoint rendering, robotics, autonomous driving, and AR/VR technologies. Traditional methods relying on hardware sensors like LiDAR are often limited by high costs, low resolution, and environmental sensitivity, limiting their applicability in real-world scenarios. Recent advances in vision-based methods offer a promising alternative, yet they face challenges in generalizatio…

Replaced article(s) found for cs.PL. https://arxiv.org/list/cs.PL/new
[1/1]:
QPanda3: A High-Performance Software-Hardware Collaborative Framework for Large-Scale Quantum-Cla...

Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization
Prashanth Vijayaraghavan, Apoorva Nitsure, Charles Mackin, Luyao Shi, Stefano Ambrogio, Arvind Haran, Viresh Paruthi, Ali Elzein, Dan Coops, David Beymer, Tyler Baldwin, Ehsan Degan
https://arxiv.org/abs/2507.12308

Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization
Large Language Models (LLMs) have become widely used across diverse NLP tasks and domains, demonstrating their adaptability and effectiveness. In the realm of Electronic Design Automation (EDA), LLMs show promise for tasks like Register-Transfer Level (RTL) code generation and summarization. However, despite the proliferation of LLMs for general code-related tasks, there's a dearth of research focused on evaluating and refining these models for hardware description languages (HDLs), notably VHD…

EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos
Ruihan Yang, Qinxi Yu, Yecheng Wu, Rui Yan, Borui Li, An-Chieh Cheng, Xueyan Zou, Yunhao Fang, Hongxu Yin, Sifei Liu, Song Han, Yao Lu, Xiaolong Wang
https://arxiv.org/abs/2507.12440

EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos
Real robot data collection for imitation learning has led to significant advancements in robotic manipulation. However, the requirement for robot hardware in the process fundamentally constrains the scale of the data. In this paper, we explore training Vision-Language-Action (VLA) models using egocentric human videos. The benefit of using human videos is not only for their scale but more importantly for the richness of scenes and tasks. With a VLA trained on human video that predicts human wris…

Surrogate Quantum Circuit Design for the Lattice Boltzmann Collision Operator
Monica L\u{a}c\u{a}tu\c{s}, Matthias M\"oller
https://arxiv.org/abs/2507.12256

Surrogate Quantum Circuit Design for the Lattice Boltzmann Collision Operator
Direct numerical simulation of turbulent flows at high Reynolds numbers remains a major challenge for traditional computational fluid dynamics (CFD) tools running on classical computer hardware. This has motivated growing interest in quantum algorithms for CFD to enable flow simulations on quantum computers. The reason being that these computers are expected to deliver potential speed-ups for certain problems. One promising quantum CFD approach is a fully quantum implementation of the lattice B…

There are two main reasons I'm not using GrapheneOS. The first is that I've had two Pixels die on me from hardware flaws, and so I think their hardware is complete trash. The second is that every time I see them talking, they're trashing some other free software project or (openish) hardware. Only _their_ platform is secure. I'm getting strong Theo De Raadt vibes from them, which is not the kind of thing I'd want to deal with.

Watermarking Quantum Neural Networks Based on Sample Grouped and Paired Training
Limengnan Zhou, Hanzhou Wu
https://arxiv.org/abs/2506.12675 https://

Watermarking Quantum Neural Networks Based on Sample Grouped and Paired Training
Quantum neural networks (QNNs) leverage quantum computing to create powerful and efficient artificial intelligence models capable of solving complex problems significantly faster than traditional computers. With the fast development of quantum hardware technology, such as superconducting qubits, trapped ions, and integrated photonics, quantum computers may become reality, accelerating the applications of QNNs. However, preparing quantum circuits and optimizing parameters for QNNs require quantu…

An Efficient Hardware Implementation of Elliptic Curve Point Multiplication over $GF(2^m)$ on FPGA
Ruby Kumari, Tapas Rout, Babul Saini, Jai Gopal Pandey, Abhijit Karmakar
https://arxiv.org/abs/2506.12359

An Efficient Hardware Implementation of Elliptic Curve Point Multiplication over $GF(2^m)$ on FPGA
Elliptic Curve Cryptography (ECC) is widely accepted for ensuring secure data exchange between resource-limited IoT devices. The National Institute of Standards and Technology (NIST) recommended implementation, such as B-163, is particularly well-suited for Internet of Things (IoT) applications. Here, Elliptic Curve Point Multiplication (ECPM) is the most time-critical and resource-intensive operation due to the finite field multiplier. This paper proposes a new implementation method of finite …

This https://arxiv.org/abs/2504.16251 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csOS_…

Adaptive and Efficient Dynamic Memory Management for Hardware Enclaves
The second version of Intel Software Guard Extensions (Intel SGX), or SGX2, adds dynamic management of enclave memory and threads. The first version required the address space and thread counts to be fixed before execution. The Enclave Dynamic Memory Management (EDMM) feature of SGX2 has the potential to lower launch times and overall execution time. Despite reducing the enclave loading time by 28--93%, straightforward EDMM adoption strategies actually slow execution time down by as much as 58%…

heise übernimmt Hardware-Händler #Mindfactory
https://www.heise.de/news/heise-uebernimmt-Hardware-Haendl…

This session has a plot twist at the end that qualifies as a cinematic masterpiece of the year:
https://developer.apple.com/videos/play/wwdc2025/308

Optimize CPU performance with Instruments - WWDC25 - Videos - Apple Developer
Learn how to optimize your app for Apple silicon with two new hardware-assisted tools in Instruments. We'll start by covering how to...

oh ha ha i kind of chuckled when i read the first paragraph of an abstract from 30 years ago
"The continuing miniaturization of computer hardware has made mobile computing increasingly popular, and it is a hit with researchers and programmers at CITI. Part of the attraction is the vast need for operating system hacking on these 80x86-based computers -- laptop manufacturers apparently encourage their customers to run MS-DOS and its derivatives!"

I$^2$S-TFCKD: Intra-Inter Set Knowledge Distillation with Time-Frequency Calibration for Speech Enhancement
Jiaming Cheng, Ruiyu Liang, Chao Xu, Ye Ni, Wei Zhou, Bj\"orn W. Schuller, Xiaoshuai Hao
https://arxiv.org/abs/2506.13127

I$^2$S-TFCKD: Intra-Inter Set Knowledge Distillation with Time-Frequency Calibration for Speech Enhancement
In recent years, complexity compression of neural network (NN)-based speech enhancement (SE) models has gradually attracted the attention of researchers, especially in scenarios with limited hardware resources or strict latency requirements. The main difficulties and challenges lie in achieving a balance between complexity and performance according to the characteristics of the task. In this paper, we propose an intra-inter set knowledge distillation (KD) framework with time-frequency calibrati…

We're launching the embedded-cal project: Providing access to hardware accelerated and formally proven cryptographic algorithms on #embedded systems in #RustLang. For this, I'm teaming up with @…

Learning to Quantize and Precode in Massive MIMO Systems for Energy Reduction: a Graph Neural Network Approach
Thomas Feys, Liesbet Van der Perre, Fran\c{c}ois Rottenberg
https://arxiv.org/abs/2507.10634

Learning to Quantize and Precode in Massive MIMO Systems for Energy Reduction: a Graph Neural Network Approach
Massive MIMO systems are moving toward increased numbers of radio frequency chains, higher carrier frequencies and larger bandwidths. As such, digital-to-analog converters (DACs) are becoming a bottleneck in terms of hardware complexity and power consumption. In this work, non-linear precoding for coarsely quantized downlink massive MIMO is studied. Given the NP-hard nature of this problem, a graph neural network (GNN) is proposed that directly outputs the precoded quantized vector based on the…

#European #Cloud Modules
https://berthub.eu/articles/posts/european-cloud-modules/…

Saw some wild messaging from Apple in the Software Update app on an old MacBook — in fact the system was *not* up-to-date. Surfaced via a Google Chrome EOL message.
Got them switched over to the latest version of Firefox just fine 👀
The web should be for everyone (and not just on new hardware)

Studie: Apple Watch soll mit KI versteckte Krankheiten aufdecken
Apples Computeruhr kommt mit diversen Sensoren und relativ flotter Hardware. Mit einem neuen KI-Modell sollen diese besser ausgewertet werden.

Soon, I’ll be throwing away all my desktop computers as well, though I’m keeping my Lenovo Thinkpad around. I hate computers, yet I use them.
To me, computers are just junk nobody asked for. They’re glowing traps that keep us hooked, scrolling and clicking away our time for endless feeds. No matter the OS or hardware, it’s all distraction from reality.
Yes, Linux can free us and all that, and even the hardware can be part of that freedom. But the computers themselves remain a cir…

Selective Quantization Tuning for ONNX Models
Nikolaos Louloudakis, Ajitha Rajan
https://arxiv.org/abs/2507.12196 https://arxiv.org/p…

Selective Quantization Tuning for ONNX Models
Quantization is a process that reduces the precision of deep neural network models to lower model size and computational demands, often at the cost of accuracy. However, fully quantized models may exhibit sub-optimal performance below acceptable levels and face deployment challenges on low-end hardware accelerators due to practical constraints. To address these issues, quantization can be selectively applied to only a subset of layers, but selecting which layers to exclude is non-trivial. To th…

Modal Analysis of Multimode Waveguides Based on Large Step Size AdaMax from Far-Field Amplitudes
Jingtong Li, Dongting Huang, Minhui Xiong, Mingzhi Li
https://arxiv.org/abs/2507.12299

Modal Analysis of Multimode Waveguides Based on Large Step Size AdaMax from Far-Field Amplitudes
Optimizing multimode waveguide performance depends on modal analysis; however, current approaches focus predominantly on modal power distribution and, limited by experimental hardware and conditions, exhibit low accuracy, poor adaptability, and high computational cost. In this work, under a power-normalization constraint, we employ the AdaMax optimizer with a large-step-size strategy to perform modal analysis of multimode waveguides from far-field amplitude measurements. Our method retrieves bo…

Fascinating how so many people in the retrocomputing community seem butthurt about those new Commodore products.
Just don’t buy them if you don’t like it—but for the love of Jack Tramiel stop with the shit-flinging.
Don’t you want more people to join the hobby? See more modern games and software for old platforms? More spare parts and mods for both old hardware and new?
What’s with this weird gatekeeping?

Efficient Multi-Camera Tokenization with Triplanes for End-to-End Driving
Boris Ivanovic, Cristiano Saltori, Yurong You, Yan Wang, Wenjie Luo, Marco Pavone
https://arxiv.org/abs/2506.12251

Efficient Multi-Camera Tokenization with Triplanes for End-to-End Driving
Autoregressive Transformers are increasingly being deployed as end-to-end robot and autonomous vehicle (AV) policy architectures, owing to their scalability and potential to leverage internet-scale pretraining for generalization. Accordingly, tokenizing sensor data efficiently is paramount to ensuring the real-time feasibility of such architectures on embedded hardware. To this end, we present an efficient triplane-based multi-camera tokenization strategy that leverages recent advances in 3D ne…

When you realize that extra NUC isn't fundamentally solving the lack of hardware in the room... The sweet spot is 5 setups and I'll only get to 4 right now 😭
Selling the laptop for a good price doesn't cover the price of digi-starvation 😆

SAP-Chef Klein erklärt die #DigitaleSouveränität Europas für gelöst, Die Kontrolle über Daten sei längst Realität, entscheidend sei nicht mehr die Hardware, sondern wer den Schlüssel besitzt. Die eigentliche Herausforderung sieht er im Mangel an klugen Köpfen, nicht an Serverfarmen. Sein Appell: Weniger Infrastrukturträume, mehr Fokus auf Bildung und Innovation. Europas Zu…

SAP-Chef Christian Klein sieht Problem der Digitalen Souveränität gelöst
US-Hyperscaler spielen für die Digitale Souveränität Europas keine Rolle. Es gehe vielmehr um den KI-Einsatz, Use Cases und einen neuen Umgang mit Regulierung, sagt SAP-CEO Christian Klein.

@… Have you tried putting #nixbook on 32-bit hardware? I have an Asus eeePC r11cx laying around that I loved at the time and would like to revive. But last time I tried compiling a 32-bit

FractalSync: Lightweight Scalable Global Synchronization of Massive Bulk Synchronous Parallel AI Accelerators
Victor Isachi, Alessandro Nadalini, Riccardo Fiorani Gallotta, Angelo Garofalo, Francesco Conti, Davide Rossi
https://arxiv.org/abs/2506.11668

FractalSync: Lightweight Scalable Global Synchronization of Massive Bulk Synchronous Parallel AI Accelerators
The slow-down of technology scaling and the emergence of Artificial Intelligence (AI) workloads have led computer architects to increasingly exploit parallelization coupled with hardware acceleration to keep pushing the performance envelope. However, this solution comes with the challenge of synchronization of processing elements (PEs) in massive heterogeneous many-core platforms. To address this challenge, we propose FractalSync, a hardware accelerated synchronization mechanism for Bulk Synchr…

Design Automation in Quantum Error Correction
Archisman Ghosh, Avimita Chatterjee, Swaroop Ghosh
https://arxiv.org/abs/2507.12253 https://

Design Automation in Quantum Error Correction
Quantum error correction (QEC) underpins practical fault-tolerant quantum computing (FTQC) by addressing the fragility of quantum states and mitigating decoherence-induced errors. As quantum devices scale, integrating robust QEC protocols is imperative to suppress logical error rates below threshold and ensure reliable operation, though current frameworks suffer from substantial qubit overheads and hardware inefficiencies. Design automation in the QEC flow is thus critical, enabling automated s…

Design and Development of an Automated Contact Angle Tester (ACAT) for Surface Wettability Measurement
Connor Burgess, Kyle Douin, Amir Kordijazi
https://arxiv.org/abs/2507.12431 …

Design and Development of an Automated Contact Angle Tester (ACAT) for Surface Wettability Measurement
The Automated Contact Angle Tester (ACAT) is a fully integrated robotic work cell developed to automate the measurement of surface wettability on 3D-printed materials. Designed for precision, repeatability, and safety, ACAT addresses the limitations of manual contact angle testing by combining programmable robotics, precise liquid dispensing, and a modular software-hardware architecture. The system is composed of three core subsystems: (1) an electrical system including power, control, and safe…

Computational Attestations of Polynomial Integrity Towards Verifiable Machine-Learning
Dustin Ray, Caroline El Jazmi
https://arxiv.org/abs/2506.11458 https…

Computational Attestations of Polynomial Integrity Towards Verifiable Machine-Learning
Machine-learning systems continue to advance at a rapid pace, demonstrating remarkable utility in various fields and disciplines. As these systems continue to grow in size and complexity, a nascent industry is emerging which aims to bring machine-learning-as-a-service (MLaaS) to market. Outsourcing the operation and training of these systems to powerful hardware carries numerous advantages, but challenges arise when privacy and the correctness of work carried out must be ensured. Recent advance…

All this time their computers have been running Win95...
FAA To Eliminate Floppy Disks Used In Air Traffic Control Systems - Slashdot
https://hardware.slashdot.org/story/25/06/09/2249232/faa-to-eliminate-floppy-disks-used-in-air-traffic-control-systems

"If the world followed the Tao, Apple would make the hardware, Microsoft would make the developer tools, and everything would run under QNX. Alas, QNX has been bought by BlackBerry, Microsoft makes operating systems and Apple makes developer tools."
https://akos.ma/blog/the-tao-of-swift/…

The Tao of Swift
I gave this talk in September 2014, in Zürich, the same day Apple announced the Apple Watch.

Ok so this piece of proprietary abandoned bricked hardware has a fucking sd card hidden inside it but no UART? Damn :(

Apple TV: Neues Modell noch in diesem Jahr?
Apple plant vermutlich noch in diesem Jahr eine frische Multimediabox. Es könnte dieses Mal neue Hardware-Elemente geben.
https://www.heise.de/news/Apple-T…

Serving Large Language Models on Huawei CloudMatrix384
Pengfei Zuo, Huimin Lin, Junbo Deng, Nan Zou, Xingkun Yang, Yingyu Diao, Weifeng Gao, Ke Xu, Zhangyu Chen, Shirui Lu, Zhao Qiu, Peiyang Li, Xianyu Chang, Zhengzhong Yu, Fangzheng Miao, Jia Zheng, Ying Li, Yuan Feng, Bei Wang, Zaijian Zong, Mosong Zhou, Wenli Zhou, Houjiang Chen, Xingyu Liao, Yipeng Li, Wenxiao Zhang, Ping Zhu, Yinggang Wang, Chuanjie Xiao, Depeng Liang, Dong Cao, Juncheng Liu, Yongqiang Yang, Xiaolong Bai, Yi Li, H…

Serving Large Language Models on Huawei CloudMatrix384
The rapid evolution of large language models (LLMs), driven by growing parameter scales, adoption of mixture-of-experts (MoE) architectures, and expanding context lengths, imposes unprecedented demands on AI infrastructure. Traditional AI clusters face limitations in compute intensity, memory bandwidth, inter-chip communication, and latency, compounded by variable workloads and strict service-level objectives. Addressing these issues requires fundamentally redesigned hardware-software integrati…

HP unveils Dimension, the first hardware built with Google's 3D video conferencing tech, featuring a 65-inch light field display, launching in 2025 for $25,000 (Emma Roth/The Verge)
https://www.theverge.com/news/684859/hp-dimension-google-b…

HP reveals $24,999 hardware created just for Google Beam
HP has revealed the first third-party hardware built using Google’s 3D video conferencing technology, Beam. The HP Dimension costs $24,999 and features a 65-inch light field display to create a “true-to-life” 3D video of your caller.

my annoying engineering trait is that i don't like hardware abstraction layers
they're usually irritating to write code for, and equally irritating to reverse-engineer whenever i need to. i mostly end up reverse-engineering these days

SFATTI: Spiking FPGA Accelerator for Temporal Task-driven Inference -- A Case Study on MNIST
Alessio Caviglia, Filippo Marostica, Alessio Carpegna, Alessandro Savino, Stefano Di Carlo
https://arxiv.org/abs/2507.10561

SFATTI: Spiking FPGA Accelerator for Temporal Task-driven Inference -- A Case Study on MNIST
Hardware accelerators are essential for achieving low-latency, energy-efficient inference in edge applications like image recognition. Spiking Neural Networks (SNNs) are particularly promising due to their event-driven and temporally sparse nature, making them well-suited for low-power Field Programmable Gate Array (FPGA)-based deployment. This paper explores using the open-source Spiker+ framework to generate optimized SNNs accelerators for handwritten digit recognition on the MNIST dataset. S…

Status der Reparaturen von vor meiner Tour:
- neuer Umwerfer wirft hervorragend um
- Begrenzungen sollte ich nochmals genau checken
- neuer Schaltzug schaltet einwandfrei
- Begrenzungen sollte ich nochmal checken
- Lenkerband wird irgendwann im Sommer fällig (Ersatz liegt da)
- Reifen rollen sehr gut (wenn genug Luft)
Bin mit der Hardware noch immer extrem zufrieden.

Cell Sensing: Traffic detection
Sa\'ul Fenollosa
https://arxiv.org/abs/2507.12211 https://arxiv.org/pdf/2507.12211

Cell Sensing: Traffic detection
This work presents a passive sensing system for traffic monitoring using ambient Long Term Evolution (LTE) signals as a non-intrusive and scalable alternative to traditional surveillance methods. The approach employs a dual-receiver architecture analyzing Channel State Information (CSI) to isolate differential Doppler shifts induced by moving targets, effectively mitigating hardware-induced phase impairments. Implemented with a Software Defined Radio (SDR) platform and srsRAN software, the syst…

Topology-Aware Virtualization over Inter-Core Connected Neural Processing Units
Dahu Feng, Erhu Feng, Dong Du, Pinjie Xu, Yubin Xia, Haibo Chen, Rong Zhao
https://arxiv.org/abs/2506.11446

Topology-Aware Virtualization over Inter-Core Connected Neural Processing Units
With the rapid development of artificial intelligence (AI) applications, an emerging class of AI accelerators, termed Inter-core Connected Neural Processing Units (NPU), has been adopted in both cloud and edge computing environments, like Graphcore IPU, Tenstorrent, etc. Despite their innovative design, these NPUs often demand substantial hardware resources, leading to suboptimal resource utilization due to the imbalance of hardware requirements across various tasks. To address this issue, prio…

heise übernimmt Hardware-Händler Mindfactory
Mit Mindfactory wechselt einer der größten deutschen Hardware-Händler den Besitzer. Nur noch das Kartellamt muss zustimmen.
https://www.h…

Experimental Verification of a Time-Domain Load Identification Method for Single-Phase Circuits
Francisco M. Arrabal-Campos, Francisco G. Montoya, Jorge Ventura, Santiago S\'anchez-Acevedo, Raymundo E. Torres-Olguin, Francisco de Le\'on
https://arxiv.org/abs/2506.12593

Experimental Verification of a Time-Domain Load Identification Method for Single-Phase Circuits
This paper presents experimental validation of a time-domain load parameter determination method for single-phase circuits. The verification is performed in a state-of-the-art smart grid laboratory equipped with power hardware and real-time emulators. The proposed method enables the identification of circuit parameters using only instantaneous voltage and current measurements at the point of common coupling. The experimental setup includes a range of test cases covering linear and non-sinusoida…

The move to Windows 11 isn’t just about security updates.
It increases dependence on Microsoft through aggressive cloud integration,
forcing users to adopt Microsoft accounts and services.
It also leads to higher costs due to subscription and licensing models,
and reduces control over how your computer works and how your data is managed.
Furthermore, new hardware requirements will render millions of perfectly good PCs obsolete.
This is a turning point.

The end of Windows 10 is approaching, so it's time to consider Linux and LibreOffice - The Document Foundation Blog
The Document Foundation and LibreOffice support the international campaign @endof10 https://endof10.org/ The countdown has begun. On 14 October 2025, Microsoft will end support for Windows 10. This will leave millions of users and organisations with a difficult choice: should they upgrade to Windows 11, or completely rethink their work environment? The good news? You don’t […]

Enabling Syscall Intercept for RISC-V
Petar Andri\'c, Aaron Call, Ramon Nou
https://arxiv.org/abs/2505.10217 https://arxiv.org/pd…

Enabling Syscall Intercept for RISC-V
The European Union technological sovereignty strategy centers around the RISC-V Instruction Set Architecture, with the European Processor Initiative leading efforts to build production-ready processors. Focusing on realizing a functional RISC-V ecosystem, the BZL initiative (www.bzl.es) is making an effort to create a software stack along with the hardware. In this work, we detail the efforts made in porting a widely used syscall interception library, mainly used on AdHocFS (i.e., DAOS, GekkoFS…

Dually Hierarchical Drift Adaptation for Online Configuration Performance Learning
Zezhen Xiang, Jingzhi Gong, Tao Chen
https://arxiv.org/abs/2507.08730 ht…

Dually Hierarchical Drift Adaptation for Online Configuration Performance Learning
Modern configurable software systems need to learn models that correlate configuration and performance. However, when the system operates in dynamic environments, the workload variations, hardware changes, and system updates will inevitably introduce concept drifts at different levels - global drifts, which reshape the performance landscape of the entire configuration space; and local drifts, which only affect certain sub-regions of that space. As such, existing offline and transfer learning ap…

High-expressibility Quantum Neural Networks using only classical resources
Marco Maronese, Francesco Ferrari, Matteo Vandelli, Daniele Dragoni
https://arxiv.org/abs/2506.13605

High-expressibility Quantum Neural Networks using only classical resources
Quantum neural networks (QNNs), as currently formulated, are near-term quantum machine learning architectures that leverage parameterized quantum circuits with the aim of improving upon the performance of their classical counterparts. In this work, we show that some desired properties attributed to these models can be efficiently reproduced without necessarily resorting to quantum hardware. We indeed study the expressibility of parametrized quantum circuit commonly used in QNN applications and …

Multi-angle precession electron diffraction (MAPED): a versatile approach to 4D-STEM precession
Stephanie M. Ribet, Rohan Dhall, Colin Ophus, Karen C. Bustillo
https://arxiv.org/abs/2506.11327

Multi-angle precession electron diffraction (MAPED): a versatile approach to 4D-STEM precession
Precession of a converged beam during acquisition of a 4D-STEM dataset improves strain, orientation, and phase mapping accuracy by averaging over continuous angles of illumination. Precession experiments usually rely on integrated systems, where automatic alignments lead to fast, high-quality results. The dependence of these experiments on specific hardware and software is evident even when switching to non-integrated detectors on a precession tool, as experimental set-up becomes challenging an…

Replaced article(s) found for cs.ET. https://arxiv.org/list/cs.ET/new
[1/1]:
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning

from my link log —
CHERIoT: the last ten years.
https://cheriot.org/cheri/history/2025/05/16/last-ten-years.html
saved 2025-05-17

Replaced article(s) found for cs.AR. https://arxiv.org/list/cs.AR/new
[1/1]:
- ProtocolLLM: RTL Benchmark for SystemVerilog Generation of Communication Protocols
Arnav Sheth, Ivaxi Sheth, Mario Fritz

visionOS-Support für Sony Sense-Controller: Ja, aber...
Apple unterstützt bereits Playstation- und Xbox-Controller mit der Vision Pro. Nun wird auch Sonys VR-Hardware folgen. Wäre da nicht ein kleines Problem.

KeyDroid: A Large-Scale Analysis of Secure Key Storage in Android Apps
Jenny Blessing, Ross J. Anderson, Alastair R. Beresford
https://arxiv.org/abs/2507.07927

KeyDroid: A Large-Scale Analysis of Secure Key Storage in Android Apps
Most contemporary mobile devices offer hardware-backed storage for cryptographic keys, user data, and other sensitive credentials. Such hardware protects credentials from extraction by an adversary who has compromised the main operating system, such as a malicious third-party app. Since 2011, Android app developers can access trusted hardware via the Android Keystore API. In this work, we conduct the first comprehensive survey of hardware-backed key storage in Android devices. We analyze 490 11…

Replaced article(s) found for cs.AR. https://arxiv.org/list/cs.AR/new
[1/1]:
Reconfigurable Stream Network Architecture
https://

Einige der zuletzt hier besonders häufig geteilten #News:
heise übernimmt Hardware-Händler Mindfactory
https://www.

"The border is no longer the focus. Now, the White House wants you to believe that the crisis extends to nail salons, hardware stores, farms, and restaurants across the country."
Trump is escalating an immigration crisis he promised to resolve
https://reason.com/2025/06/11/the-trump-administration-is-escalating-an-immigration-crisis-it-promised-to-resolve/

Advances on Affordable Hardware Platforms for Human Demonstration Acquisition in Agricultural Applications
Alberto San-Miguel-Tello, Gennaro Scarati, Alejandro Hern\'andez, Mario Cavero-Vidal, Aakash Maroti, N\'estor Garc\'ia
https://arxiv.org/abs/2506.09494

Advances on Affordable Hardware Platforms for Human Demonstration Acquisition in Agricultural Applications
This paper presents advances on the Universal Manipulation Interface (UMI), a low-cost hand-held gripper for robot Learning from Demonstration (LfD), for complex in-the-wild scenarios found in agricultural settings. The focus is on improving the acquisition of suitable samples with minimal additional setup. Firstly, idle times and user's cognitive load are reduced through the extraction of individual samples from a continuous demonstration considering task events. Secondly, reliability on the g…

Hardware-Aware Feature Extraction Quantisation for Real-Time Visual Odometry on FPGA Platforms
Mateusz Wasala, Mateusz Smolarczyk, Michal Danilowicz, Tomasz Kryjak
https://arxiv.org/abs/2507.07903

Hardware-Aware Feature Extraction Quantisation for Real-Time Visual Odometry on FPGA Platforms
Accurate position estimation is essential for modern navigation systems deployed in autonomous platforms, including ground vehicles, marine vessels, and aerial drones. In this context, Visual Simultaneous Localisation and Mapping (VSLAM) - which includes Visual Odometry - relies heavily on the reliable extraction of salient feature points from the visual input data. In this work, we propose an embedded implementation of an unsupervised architecture capable of detecting and describing feature po…

from my link log —
SIMD in Rust: you do not need multithreading to do more than one thing at a time.
https://sander.saares.eu/2024/12/31/you-do-not-need-multithreading-to-do-more-than-one-thing-at-a-time/

You do not need multithreading to do more than one thing at a time
As hardware gets faster and more capable, software keeps getting slower. It is remarkable how inefficiently typical apps use the capabilities of modern processors! Often this means an app is doing …

Bit-Flip Fault Attack: Crushing Graph Neural Networks via Gradual Bit Search
Sanaz Kazemi Abharian, Sai Manoj Pudukotai Dinakarrao
https://arxiv.org/abs/2507.05531

Bit-Flip Fault Attack: Crushing Graph Neural Networks via Gradual Bit Search
Graph Neural Networks (GNNs) have emerged as a powerful machine learning method for graph-structured data. A plethora of hardware accelerators has been introduced to meet the performance demands of GNNs in real-world applications. However, security challenges of hardware-based attacks have been generally overlooked. In this paper, we investigate the vulnerability of GNN models to hardware-based fault attack, wherein an attacker attempts to misclassify output by modifying trained weight paramete…

Hardware Limitations and Optimization Approach in 1-Bit RIS Design at 28 GHz
Hossein Rezaei, Mehmet Emin Arslan, George Yammine, Niels Neumann, Norman Franchi
https://arxiv.org/abs/2506.08930

Hardware Limitations and Optimization Approach in 1-Bit RIS Design at 28 GHz
Reconfigurable intelligent surfaces (RIS) have emerged as a transformative technology for electromagnetic (EM) wave manipulation, offering unprecedented control over wave reflections compared to traditional metallic reflectors. By utilizing an array of tunable elements, RIS can steer and shape electromagnetic waves to enhance signal quality in wireless communication and radar systems. However, practical implementations face significant challenges due to hardware limitations and phase quantizati…

Adaptive Job Scheduling in Quantum Clouds Using Reinforcement Learning
Waylon Luo (Kent State University), Jiapeng Zhao (Cisco), Tong Zhan (Meta), Qiang Guan (Kent State University)
https://arxiv.org/abs/2506.10889

Adaptive Job Scheduling in Quantum Clouds Using Reinforcement Learning
Present-day quantum systems face critical bottlenecks, including limited qubit counts, brief coherence intervals, and high susceptibility to errors-all of which obstruct the execution of large and complex circuits. The advancement of quantum algorithms has outpaced the capabilities of existing quantum hardware, making it difficult to scale computations effectively. Additionally, inconsistencies in hardware performance and pervasive quantum noise undermine system stability and computational accu…

[2025-07-16 Wed (UTC), 8 new articles found for cs.AR Hardware Architecture]
toXiv_bot_toot

AMD unveils its new MI350X and MI355X GPUs for AI workloads, claiming up to 4x AI compute performance and 35x inference gains over the prior-gen MI300X (Paul Alcorn/Tom's Hardware)
https://www.to…

AMD announces MI350X and MI355X AI GPUs, claims up to 4X generational performance gain, 35X faster inference
More power consumption equals lower TCO.

Fast and Efficient Merge of Sorted Input Lists in Hardware Using List Offset Merge Sorters
Robert B. Kent, Marios S. Pattichis
https://arxiv.org/abs/2507.08658

Fast and Efficient Merge of Sorted Input Lists in Hardware Using List Offset Merge Sorters
A new set of hardware merge sort devices are introduced here, which merge multiple sorted input lists into a single sorted output list in a fast and efficient manner. In each merge sorter, the values from the sorted input lists are arranged in an input 2-D setup array, but with the order of each sorted input list offset from the order of each of the other sorted input lists. In these new devices, called List Offset Merge Sorters (LOMS), a minimal set of column sort stages alternating with row s…

Poland's Clean Energy Usage Overtakes Coal For First Time - Slashdot
https://hardware.slashdot.org/story/25/07/07/1524200/polands-clean-energy-usage-overtakes-coal-for-first-time

[2025-06-16 Mon (UTC), 6 new articles found for cs.AR Hardware Architecture]
toXiv_bot_toot

Deutschland hat die Marke von einer Million Balkonkraftwerken geknackt! 🌞
Zum Artikel: https://heise.de/-1043959?wt_mc=sm.red.ho.mastodon.mastodon.md_beitraege.md_beitraege&utm_source=mastodon

[2025-06-17 Tue (UTC), 6 new articles found for cs.AR Hardware Architecture]
toXiv_bot_toot

Nintendo says it sold 3.5M Switch 2 consoles globally in its first four days, a record for any of its hardware; Nintendo aims to sell 15M units by March 2026 (Takashi Mochizuki/Bloomberg)
https://www.bloomberg.com/news/articles/20

Design and Implementation of Washing Machine HUD Using FPGAs
Norman Stites, D. G. Perera
https://arxiv.org/abs/2506.11287 https://arx…

Design and Implementation of Washing Machine HUD Using FPGAs
In contemporary digital design education, practical field programmable gate array (FPGA) projects are indispensable for bridging theoretical concepts with real-world applications. This project focuses on developing a hardware-based simulation of a domestic washing machine controller using the Xilinx Spartan-3E development board. A critical component of the design is the graphical heads-up display (HUD), which renders real-time information about the machine's operational state and cycle selectio…

Real-World Deployment of a Lane Change Prediction Architecture Based on Knowledge Graph Embeddings and Bayesian Inference
M. Manzour, Catherine M. Elias, Omar M. Shehata, R. Izquierdo, M. A. Sotelo
https://arxiv.org/abs/2506.11925

Real-World Deployment of a Lane Change Prediction Architecture Based on Knowledge Graph Embeddings and Bayesian Inference
Research on lane change prediction has gained a lot of momentum in the last couple of years. However, most research is confined to simulation or results obtained from datasets, leaving a gap between algorithmic advances and on-road deployment. This work closes that gap by demonstrating, on real hardware, a lane-change prediction system based on Knowledge Graph Embeddings (KGEs) and Bayesian inference. Moreover, the ego-vehicle employs a longitudinal braking action to ensure the safety of both i…

heise | Entspannter klicken: Vier ergonomische Mäuse im Test
Vertikale Mäuse sollen die Handgelenke schonen. Davon profitieren Sie bei der Büroarbeit – dank moderner Hardware mitunter aber auch beim Spielen.

Reconfigurable Digital RRAM Logic Enables In-Situ Pruning and Learning for Edge AI
Songqi Wang, Yue Zhang, Jia Chen, Xinyuan Zhang, Yi Li, Ning Lin, Yangu He, Jichang Yang, Yingjie Yu, Yi Li, Zhongrui Wang, Xiaojuan Qi, Han Wang
https://arxiv.org/abs/2506.13151

Reconfigurable Digital RRAM Logic Enables In-Situ Pruning and Learning for Edge AI
The human brain simultaneously optimizes synaptic weights and topology by growing, pruning, and strengthening synapses while performing all computation entirely in memory. In contrast, modern artificial-intelligence systems separate weight optimization from topology optimization and depend on energy-intensive von Neumann architectures. Here, we present a software-hardware co-design that bridges this gap. On the algorithmic side, we introduce a real-time dynamic weight-pruning strategy that moni…

CCSS: Hardware-Accelerated RTL Simulation with Fast Combinational Logic Computing and Sequential Logic Synchronization
Weigang Feng, Yijia Zhang, Zekun Wang, Zhengyang Wang, Yi Wang, Peijun Ma, Ningyi Xu
https://arxiv.org/abs/2507.08406

CCSS: Hardware-Accelerated RTL Simulation with Fast Combinational Logic Computing and Sequential Logic Synchronization
As transistor counts in a single chip exceed tens of billions, the complexity of RTL-level simulation and verification has grown exponentially, often extending simulation campaigns to several months. In industry practice, RTL simulation is divided into two phases: functional debug and system validation. While system validation demands high simulation speed and is typically accelerated using FPGAs, functional debug relies on rapid compilation-rendering multi-core CPUs the primary choice. However…

Towards LLM-based Root Cause Analysis of Hardware Design Failures
Siyu Qiu, Muzhi Wang, Raheel Afsharmazayejani, Mohammad Moradi Shahmiri, Benjamin Tan, Hammond Pearce
https://arxiv.org/abs/2507.06512

Towards LLM-based Root Cause Analysis of Hardware Design Failures
With advances in large language models (LLMs), new opportunities have emerged to develop tools that support the digital hardware design process. In this work, we explore how LLMs can assist with explaining the root cause of design issues and bugs that are revealed during synthesis and simulation, a necessary milestone on the pathway towards widespread use of LLMs in the hardware design process and for hardware security analysis. We find promising results: for our corpus of 34 different buggy sc…

STI-SNN: A 0.14 GOPS/W/PE Single-Timestep Inference FPGA-based SNN Accelerator with Algorithm and Hardware Co-Design
Kainan Wang, Chengyi Yang, Chengting Yu, Yee Sin Ang, Bo Wang, Aili Wang
https://arxiv.org/abs/2506.08842

STI-SNN: A 0.14 GOPS/W/PE Single-Timestep Inference FPGA-based SNN Accelerator with Algorithm and Hardware Co-Design
Brain-inspired Spiking Neural Networks (SNNs) have attracted attention for their event-driven characteristics and high energy efficiency. However, the temporal dependency and irregularity of spikes present significant challenges for hardware parallel processing and data reuse, leading to some existing accelerators falling short in processing latency and energy efficiency. To overcome these challenges, we introduce the STI-SNN accelerator, designed for resource-constrained applications with high…

Replaced article(s) found for cs.AR. https://arxiv.org/list/cs.AR/new
[1/1]:
- GNN-ACLP: Graph Neural Networks Based Analog Circuit Link Prediction
Pan, Zhou, Ma, Wang, Zhao, Li, Lin, Lio, Wang

HLStrans: Dataset for LLM-Driven C-to-HLS Hardware Code Synthesis
Qingyun Zou, Nuo Chen, Yao Chen, Bingsheng He, WengFei Wong
https://arxiv.org/abs/2507.04315

HLStrans: Dataset for LLM-Driven C-to-HLS Hardware Code Synthesis
High-level synthesis (HLS) enables software developers to describe and implement hardware at a higher level of abstraction by using C/C++ instead of traditional hardware description languages to automatically generate FPGA-ready designs. However, generating HLS code significantly differs from standard C/C++: it disallows certain coding idioms, relies on specialized libraries, and critically requires fine-grained transformations and the insertion of optimization directives (pragmas) to achieve h…

VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Code
Raghu Vamshi Hemadri, Jitendra Bhandari, Johann Knechtel, Badri P Gopalan, Ramesh Narayanaswamy, Ramesh Karri, Siddharth Garg
https://arxiv.org/abs/2506.07239

VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Code
Modern chip design is complex, and there is a crucial need for early-stage prediction of key design-quality metrics like timing and routing congestion directly from Verilog code (a commonly used programming language for hardware design). It is especially important yet complex to predict individual lines of code that cause timing violations or downstream routing congestion. Prior works have tried approaches like converting Verilog into an intermediate graph representation and using LLM embedding…