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The Fused Multiply-Add and Global Atmospheric Models: A Distributional Investigation into a Surprising Correctness Scenario 24

The Fused Multiply-Add and Global Atmospheric Models: A Dist...

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proceedings of the SC '24 Workshops of the International Conference on High Performance computing, Network, Storage, and analysis

作者： Teo Price-Broncucia Allison H. Baker Michael Duda Department of Computer Science University of Colorado Boulder CO Computational and Information Systems Lab NSF National Center for Atmospheric Research Boulder CO Mesoscale and Microscale Meteorology Lab NSF National Center for Atmospheric Research Boulder CO

ISBN: (纸本)9798350355543

In a series of related works developing an ensemble consistency testing approach for multiple popular global climate models (GCMs), one test scenario has repeatedly stood out. Why does the use of the Fused Multiply-Add (FMA) operation result in model configurations getting flagged as failures, while changes to compiler choice, optimization level, processor type and number, etc. are passed as expected? This work explores the impacts of FMA on GCM simulation output from a distributional perspective and provides directions for future work to enable model developers and users to use numerical optimization techniques with confidence.

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UbiComp/ISWC 2021 - Adjunct proceedings of the 2021 acm International Joint Conference on Pervasive and Ubiquitous computing and proceedings of the 2021 acm International Symposium on Wearable Computers

UbiComp/ISWC 2021 - Adjunct Proceedings of the 2021 ACM Inte...

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2021 acm International Joint Conference on Pervasive and Ubiquitous computing and the 2021 acm International Symposium on Wearable Computers, UbiComp/ISWC 2021

ISBN: (纸本)9781450384612

The proceedings contain 154 papers. The topics discussed include: opportune moments for the multi-stage notification responding process: a preliminary investigation;occurrence and triggers of mobile news exposure: a screenshot-based ESM study;killing-time detection from smartphone screenshots;TechLifeProbe: a technology prototype to probe how data sharing with adolescentsâ€™ parents improves their technology abuse through mobile phones;detecting single-hand riding with integrated accelerometer and gyroscope of smartphone;vision-based scene analysis toward dangerous cycling behavior detection using smartphones;on the predictability of parking preferences;challenges and opportunities in developing systems to assist patients in recovering from gambling addiction;exploring user contexts and needs for context-aware smartphone distraction management;estimating patient independence with sleep sensors;and a participatory workshop to design vibrothermal haptics of a smart fidget surface for remote workers.

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A Systematic Comparison of Large Language Models Performance for Intrusion Detection

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proceedings of the acm on Networking 2024年第CONEXT4期2卷 1-23页

作者： Minh-Thanh Bui Matteo Boffa Rodolfo Vieira Valentim Jose Manuel Navarro Fuxing Chen Xiaosheng Bao Zied Ben Houidi Dario Rossi Huawei Technologies Co. Ltd. Boulogne-Billancourt France Politecnico di Torino & Huawei Technologies Co. Ltd. Turin Italy Università di Torino & Huawei Technologies Co. Ltd. Turin Italy

We explore the capabilities of Large Language Models (LLMs) to assist or substitute devices (i.e., firewalls) and humans (i.e., security experts) respectively in the detection and analysis of security incidents. We leverage transformer-based technologies, from relatively small to foundational sizes, to address the problem of correctly identifying the attack severity (and accessorily identifying and explaining the attack type). We contrast a broad range of LLM techniques (prompting, retrieval augmented generation, and fine-tuning of several models) using state-of-the-art machine learning models as a baseline. Using proprietary data from commercial deployment, our study provides an unbiased picture of the strengths and weaknesses of LLM for intrusion detection.

关键词： computing methodologies firewalls intrusion detection systems machine learning natural language processing security and privacy

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Toxicity in the Decentralized Web and the Potential for Model Sharing 22

Toxicity in the Decentralized Web and the Potential for Mode...

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2022 acm SIGMETRICS/IFIP PERFORMANCE Joint International Conference on measurement and Modeling of Computer systems, SIGMETRICS/PERFORMANCE 2022

作者： Bin Zia, Haris Raman, Aravindh Castro, Ignacio Hassan Anaobi, Ishaku De Cristofaro, Emiliano Sastry, Nishanth Tyson, Gareth Queen Mary University of London London United Kingdom Telefonica Research Barcelona Spain University College London London United Kingdom University of Surrey Surrey United Kingdom Hong Kong University of Science & Technology Hong Kong Hong Kong

ISBN: (纸本)9781450391412

The "Decentralised Web"(DW) is an evolving concept, which encompasses technologies aimed at providing greater transparency and openness on the web. The DW relies on independent servers (aka instances) that mesh together in a peer-to-peer fashion to deliver a range of services (e.g. micro-blogs, image sharing, video streaming). However, toxic content moderation in this decentralised context is challenging. This is because there is no central entity that can define toxicity, nor a large central pool of data that can be used to build universal classifiers. It is therefore unsurprising that there have been several high-profile cases of the DW being misused to coordinate and disseminate harmful material. Using a dataset of 9.9M posts from 117K users on Pleroma (a popular DW microblogging service), we quantify the presence of toxic content. We find that toxic content is prevalent and spreads rapidly between instances. We show that automating per-instance content moderation is challenging due to the lack of sufficient training data available and the effort required in labelling. We therefore propose and evaluate ModPair, a model sharing system that effectively detects toxic content, gaining an average per-instance macro-F1 score 0.89. © 2022 Owner/Author.

关键词： decentralised web toxicity analysis content moderation pleroma

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proceedings of PEHC 2021: Workshop on Programming Environments for Heterogeneous computing, Held in conjunction with SC 2021: The International Conference for High Performance computing, Networking, Storage and analysis

Proceedings of PEHC 2021: Workshop on Programming Environmen...

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2021 IEEE/acm Workshop on Programming Environments for Heterogeneous computing, PEHC 2021

ISBN: (纸本)9781728186764

The proceedings contain 6 papers. The topics discussed include: GenMAT: a general-purpose machine learning-driven auto-tuner for heterogeneous platforms;OSCAR parallelizing and power reducing compiler and API for heterogeneous multicores;a python-based high-level programming flow for CPU-FPGA heterogeneous systems;a holistic systems approach to leveraging heterogeneity;survival of the fittest amidst the Cambrian explosion of processor architectures for artificial intelligence;and designing heterogeneous systems: large scale architectural exploration via simulation.

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Sequential Task Flow Runtime Model Improvements and Limitations 12

Sequential Task Flow Runtime Model Improvements and Limitati...

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12th IEEE/acm International Workshop on Runtime and Operating systems for Supercomputers, ROSS 2022

作者： Pei, Yu Bosilca, George Dongarra, Jack University of Tennessee Innovative Computing Laboratory United States

ISBN: (纸本)9781665475662

The sequential task flow (STF) model is the main-stream approach for interacting with task-based runtime systems, with StarPU and the Dynamic task discovery (DTD) in PaRSEC being two implementations of this model. Compared with other approaches of submitting tasks into a runtime system, STF has interesting advantages centered around an easy-to-use API, that allows users to expressed algorithms as a sequence of tasks (much like in OpenMP), while allowing the runtime to automatically identify and analyze the task dependencies and scheduling. In this paper, we focus on the DTD interface in PaRSEC, highlight some of its lesser known limitations and implemented two optimization techniques for DTD: support for user level graph trimming, and a new API for broadcast read-only data to remote tasks. We then analyze the benefits and limitations of these optimizations with benchmarks as well as on two common matrix factorization kernels Cholesky and QR, on two different systems Shaheen II from KAUST and Fugaku from RIKEN. We point out some potential for further improvements, and provided valuable insights into the strength and weakness of STF model. hoping to guide the future developments of task-based runtime systems. © 2022 IEEE.

关键词： Application programming interfaces (API)

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Evaluating ISO C++ Parallel Algorithms on Heterogeneous HPC systems 13

Evaluating ISO C++ Parallel Algorithms on Heterogeneous HPC ...

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13th IEEE/acm International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer systems, PMBS 2022

作者： Lin, Wei-Chen Deakin, Tom McIntosh-Smith, Simon University of Bristol Department of Computer Science Bristol United Kingdom

ISBN: (纸本)9781665451857

Recent revisions to the ISO C++ standard have added specifications for parallel algorithms. These additions cover common use-cases, including sequence traversal, reduction, and even sorting, many of which are highly applicable in HPC, and thus represent a potential for increased performance and *** study evaluates the state of the art for implementing heterogeneous HPC applications using the latest built-in ISO C++17 parallel algorithms. We implement C++17 ports of representative HPC mini-apps that cover both compute-bound and memory bandwidth-bound applications. We then conduct benchmarks on CPUs and GPUs, comparing our ports to other widely-available parallel programming models, such as OpenMP, CUDA, and ***, we show that C++17 parallel algorithms are able to achieve competitive performance across multiple mini-apps on many platforms, with some notable exceptions. We also discuss several key topics, including portability, and describe workarounds for a number of remaining issues, including index-based traversal and accelerator device/memory management. © 2022 IEEE.

关键词： Application programming interfaces (API)

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Federated Learning Aggregation based on Weight Distribution analysis

Federated Learning Aggregation based on Weight Distribution ...

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2023 IEEE International Conference on Imaging systems and Techniques, IST 2023

作者： Chatzikonstantinou, Christos Konstantinidis, Dimitrios Dimitropoulos, Kosmas Daras, Petros Centre for Research and Technology Hellas Visual Computing Lab Information Technologies Institute Greece

ISBN: (纸本)9798350330830

Federated learning has recently been proposed as a solution to the problem of using private or sensitive data for training a central deep model, without exchanging the local data. In federated learning, local models are trained on the client side using the available data, while a server is responsible for aggregating the weights of these models into a global model. However, the traditional weight averaging approach does not take into consideration the importance of the different weights for the performance of a model. To this end, this work proposes a novel federated learning weight aggregation method that estimates the statistical distance of each client's parameters from the Gaussianity, and weighs the contribution of each client to the global model accordingly so that the most significant information is retained and enhanced. To create an accurate global model, a complex weighted averaging of the parameters of clients' models at the layer level is performed, considering as low quality the parameters following the Gaussian distribution. The proposed method can be employed to both convolutional and linear layers and it is based on the notion that parameters following a Gaussian distribution do not significantly affect the output of a model. Experiments with different network architectures and a comparison with a plethora of state-of-the-art approaches on three well-known image classification datasets demonstrate the superiority of the proposed method for federated learning weight aggregation. © 2023 IEEE.

关键词： Image classification

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Design Exploration and Scalability analysis of a CMOS-Integrated, Polymorphic, Nanophotonic Arithmetic-Logic Unit 21

Design Exploration and Scalability Analysis of a CMOS-Integr...

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19th acm Conference on Embedded Networked Sensor systems, SenSys 2021

作者： Karempudi, Venkata Sai Praneeth Datta, Shreyan Thakkar, Ishan G University of Kentucky Kentucky Lexington United States National Institute of Technology Durgapur India

ISBN: (纸本)9781450390972

Over the past two decades, the clock speed, and hence, the singlecore performance of microprocessors has already stagnated. Following this, the recent faltering of Moore's law due to the CMOS fabrication technology reaching its unavoidable physical limit has presaged daunting challenges for designing power-efficient and ultrafast microprocessors. To overcome these challenges, vigorous efforts have been made to develop new more-than-Moore technologies and architectures for computing. Among these, nanophotonic integrated circuits based computing architectures have shown revolutionary potential. Among recent demonstrations of nanophotonic circuits for computing, a polymorphic, nanophotonic ALU (PoN-ALU) carries a notable importance since it has shown very high flexibility, high speed, and low power consumption for computing. In this paper, we carry out a design space exploration of this PoN-ALU to derive new design guidelines that can help scale the speed and energy efficiency of PoNALU even further. © 2021 acm.

关键词： Computation theory

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On the Skolem Problem and the Skolem Conjecture 22

On the Skolem Problem and the Skolem Conjecture

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37th Annual acm/IEEE Symposium on Logic in Computer Science, LICS 2022

作者： Lipton, Richard J. Luca, Florian Nieuwveld, Joris Ouaknine, Joël Purser, David Worrell, James Department of Computer Science Georgia Institute of Technology United States School of Mathematics University of the Witwatersrand South Africa Max Planck Institute for Software Systems Germany Department of Computer Science University of Oxford United Kingdom

ISBN: (纸本)9781450393515

It is a longstanding open problem whether there is an algorithm to decide the Skolem Problem for linear recurrence sequences (LRS) over the integers, namely whether a given such sequence un n8=0 has a zero term (i.e., whether un = 0 for some n). A major breakthrough in the early 1980s established decidability for LRS of order 4 or less, i.e., for LRS in which every new term depends linearly on the previous four (or fewer) terms. The Skolem Problem for LRS of order 5 or more, in particular, remains a major open challenge to this day. Our main contributions in this paper are as follows: First, we show that the Skolem Problem is decidable for reversible LRS of order 7 or less. (An integer LRS (un)n8=0 is reversible if its unique extension to a bi-infnite LRS (un)n8=-8 also takes exclusively integer values;a typical example is the classical Fibonacci sequence, whose bi-infnite extension is (. . . , 5, -3, 2, -1, 1, 0, 1, 1, 2, 3, 5, . . .) Second, assuming the Skolem Conjecture (a central hypothesis in Diophantine analysis, also known as the Exponential Local-Global Principle), we show that the Skolem Problem for LRS of order 5 is decidable, and exhibit a concrete procedure for solving it. © 2022 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Computability and decidability

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