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检索条件"任意字段=5th International Symposium on Code Generation and Optimization"

共 251 条记录，以下是1-10 订阅

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Proceedings of the 10th Workshop on optimizations for DSP and Embedded Systems, ODES 2013 - In Conjunction with international symposium on code generation and optimization, CGO 2013

Proceedings of the 10th Workshop on Optimizations for DSP an...

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10th Workshop on optimizations for DSP and Embedded Systems, ODES 2013 - In Conjunction with international symposium on code generation and optimization, CGO 2013

ISBN: (纸本)9781450319058

the proceedings contain 5 papers. the topics discussed include: IR-level versus machine-level if-conversion for predicated architectures;code generation for an application-specific VLIW processor with clustered, addressable register files;towards a performance- and energy-efficient data filter cache;power devil: tool for power gating strategy selection*;and application task and data placement in embedded many-core NUMA architectures.

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Proceedings of the 11th Workshop on optimizations for DSP and Embedded Systems, ODES 2014 - In Conjunction with international symposium on code generation and optimization, CGO 2014

Proceedings of the 11th Workshop on Optimizations for DSP an...

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11th Workshop on optimizations for DSP and Embedded Systems, ODES 2014 - In Conjunction with international symposium on code generation and optimization, CGO 2014

ISBN: (纸本)9781450325950

the proceedings contain 5 papers. the topics discussed include: refresh-aware DDR3 barrel memory controller with deterministic functionality;evaluating and estimating the WCET criticality metric;BCIBench: a benchmarking suite for EEG-based brain computer interface;integrated modulo scheduling and cluster assignment for TI TMS320C64x+ architecture;and preliminary results for neuroevolutionary optimization phase order generation for static compilation.

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CGO 2020 - Proceedings of the 18th ACM/IEEE international symposium on code generation and optimization

CGO 2020 - Proceedings of the 18th ACM/IEEE International Sy...

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18th ACM/IEEE international symposium on code generation and optimization, CGO 2020

ISBN: (纸本)9781450370479

the proceedings contain 25 papers. the topics discussed include: AN5D: automated stencil framework for high-degree temporal blocking on GPUs;efficient nursery sizing for managed languages on multi-core processors with shared caches;type freezing: exploiting attribute type monomorphism in tracing JIT compilers;low-cost prediction-based fault protection strategy;secure automatic bounds checking: prevention is simpler than cure;aloe: verifying reliability of approximate programs in the presence of recovery mechanisms;interactive debugging of concurrent programs under relaxed memory models;testing static analyses for precision and soundness;and efficient and scalable cross-isa virtualization of hardware transactional memory.

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Empowering Students: Leveraging No-code and Training Models with Google Machine Learning for Accessible App Development 5th

Empowering Students: Leveraging No-Code and Training Models ...

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5th international symposium on Intelligent Computing Systems

作者： Paul, Sujni Higher Coll Technol Dubai Acad City Fac Dubai U Arab Emirates

ISBN: (纸本)9783031829307;9783031829314

the rapid advancement of technology has created a demand for tools that enable individuals without a computer science background to develop applications. this research focuses on leveraging no-code and low-code platforms, integrated with Google's machine learning technologies, to empower non-computer science students to create functional and innovative applications. the goal is to democratize app development by providing accessible tools that allow students from various disciplines to harness the power of machine learning without extensive programming knowledge. No-code and low-code platforms offer intuitive development environments where users can design and deploy applications using drag-and-drop interfaces, pre-built components, and minimal coding. By incorporating Google's machine learning capabilities, such as natural language processing, image recognition, and predictive analytics, these platforms enable students to create intelligent applications that solve real-world problems. this integration enhances learning experiences, fosters creativity, and broadens skill sets. the study examines the potential of these platforms in educational settings, exploring their ability to facilitate technically sophisticated yet easy-to-create applications. It also investigates the challenges and opportunities of teaching non-computer science students to use these tools, including the need for tailored instructional materials and support systems. through case studies and user testing, the research evaluates the impact of no-code and low-code app development on student engagement, creativity, and integration of machine learning into diverse academic projects. By contributing to accessible technology education, this paper highlights how these platforms, combined with Google's machine learning, can foster a new generation of developers from non-traditional backgrounds.

关键词： Predictive analytics

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5th international Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2024

5th International Conference on Recent Trends in Machine Lea...

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5th international Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2024

ISBN: (纸本)9789819788644

the proceedings contain 41 papers. the special focus in this conference is on Recent Trends in Machine Learning. the topics include: Video Enhancement by Progressive Use of Denoising and Super-Resolution;Integrating GPS Technology and Smart Payment Systems for Enhanced Public Transportation Efficiency in India;a Machine Learning-Driven Approach for Early Leaf Disease Detection and Classification: A Survey;software Defect code Analyzer Using Cosine Similarity;unleashing Agricultural Precision: A Deep Learning Paradigm for Papaya (Carica Papaya L.) Variety Discrimination and Yield optimization;Fish Farm Monitoring and Controlled System Using LoRaWAN Network;Deep Neuro-Fuzzy Imaging: Enhanced 3D Brain Reconstruction from MRI Scans Using ANFIS and Deep Learning;analysis of Different Machine Learning Techniques in Troll Data Detection;comparative Analysis of Machine Learning Algorithms for Prostate Cancer;breaking Barriers in Communication Using Long Short-Term Memory Networks for Sign Language Recognition;data Transmission and Reception with Error Detection Circuitry;An Amphibious Surface Cleaning Robot with GVM Wireless Control and Automatic Waste Segregation;Automatic Speech Recognition (ASR) Elevator;integrated Smart Water Management System for Urban Sustainability;a Simplified Deep Learning Approach for Diabetic Macular Edema Detection;innovative Rumor Detection on Social Media Text: A Comprehensive Study of Dual Co-Attention Ensemble Based Voting Approach;artificial Intelligence for Glaucoma and Diabetic Retinopathy: A Review;query-Based Text Summarization: A Comparative Investigation and TextRank Implementation;An Acoustic Method for Inspection of CNC Cutting Operations;Enhancing Question Answer generation from PDFs: A Fusion of BERT, RAKE, T5 and DistilBERT with RQUGE Evaluation;Detecting Fundus Lesions for Diabetic Retinopathy (DR) Analysis.

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5th international Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2024

5th International Conference on Recent Trends in Machine Lea...

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5th international Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2024

ISBN: (纸本)9789819788606

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Evaluating the Effectiveness of Large Language Models in Automated Unit Test generation

Evaluating the Effectiveness of Large Language Models in Aut...

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Advanced Research in Computing (ICARC), international Conference on

作者： tharindu Godage Sivaraj Nimishan Shanmuganathan Vasanthapriyan Vigneshwaran Palanisamy Charles Joseph Selvarajah thuseethan Sabaragamuwa University of Sri Lanka Sri Lanka University of Peradeniya Sri Lanka Charles Darwin University Australia University of Southern Queensland Australia

ISBN: (数字)9798331530983

ISBN: (纸本)9798331530990

the increasing use of Artificial Intelligence (AI) in software development underscores the need to select suitable Large Language Models (LLMs) for automating software unit test generation. No prior work has been conducted to evaluate the performance of LLM in this domain. To address this gap, this study evaluates the effectiveness of four prominent LLMs—GPT-4, Claude 3.5, Command-R-08-2024 and Llama 3.1—in generating unit test cases. this study particularly aims to evaluate the performance of these models in real-world testing scenarios. Hence, 106 test cases from 23 test suites based on interviews with software experts and QA engineers are used to ensure relevance and comprehensiveness. these test cases are analyzed using JavaScript Engines Specification Tester (JEST) for code coverage and Stryker for mutation testing while adopting both quantitative and qualitative analysis. the findings reveal that Claude 3.5 consistently outperforms the other models against test success rate, statement coverage, and mutation score with the achieved accuracy of 93.33%, 98.01%, and 89.23% respectively. the results also provide insights into the capabilities of LLMs for automated unit test generation and their integration into the continuous software integration pipeline. Further, the findings authenticated the importance of systematically comparing LLMs for test case generation.

关键词： Measurement Accuracy Large language models Pipelines Software Test pattern generators Standards optimization Testing Software development management

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code compaction of an operating system kernel

Code compaction of an operating system kernel

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5th international symposium on code generation and optimization

作者： He, Haifeng Trimble, John Perianayagam, Somu Debray, Saumya Andrews, Gregory Univ Arizona Dept Comp Sci Tucson AZ 85721 USA

ISBN: (纸本)9780769527642

General-purpose operating systems, such as Linux, are increasingly being used in embedded systems. Computational resources are usually limited, and embedded processors often have a limited amount of memory. this makes code size especially important. this paper describes techniques for automatically reducing the memory footprint of general-purpose operating systems on embedded platforms. the problem is complicated by the fact that kernel code tends to be quite different from ordinary application code, including the presence of a significant amount of hand-written assembly code, multiple entry points, implicit control flow paths involving interrupt handlers, and frequent indirect control flow via function pointers. We use a novel "approximate decompilation" technique to apply source-level program analysis to hand-written assembly code. A prototype implementation of our ideas on an Intel x86 platform, applied to a Linux kernel that has been configured to exclude unnecessary code, obtains a code size reduction of close to 24%.

关键词： Computer operating systems

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Iterative optimization in the polyhedral model: Part I, one-dimensional time 07

Iterative optimization in the polyhedral model: Part I, one-...

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5th international symposium on code generation and optimization

作者： Pouchet, Louis-Noel Bastoul, Cedric Cohen, Albert Vasilache, Nicolas Univ Paris Sud INRIA FUTURS ALCHEMY Grp Paris France

ISBN: (纸本)9780769527642

Emerging microprocessors offer unprecedented parallel computing capabilities and deeper memory hierarchies, increasing the importance of loop transformations in optimizing compilers. Because compiler heuristics rely on simplistic performance models, and because they are bound to a limited set of transformations sequences, they only uncover a fraction of the peak performance on typical benchmarks. Iterative optimization is a maturing framework to address these limitations, but so far, it was not successfully applied complex loop transformation sequences because of the combinatorics of the optimization search space. We focus on the class of loop transformation which can be expressed as one-dimensional affine schedules. We define a systematic exploration method to enumerate the space of all legal, distinct transformations in this class. this method is based on an upstream characterization, as opposed to state-of-the-art downstream filtering approaches. Our results demonstrate orders of magnitude improvements in the size of the search space and in the convergence speed of a dedicated iterative optimization heuristic.

关键词： Optimizing compilers Law Legal factors Mathematical model Predictive models Filtering Space exploration Buildings Machine learning Microprocessors

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Loop optimization using hierarchical compilation and kernel decomposition 07

Loop optimization using hierarchical compilation and kernel ...

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5th international symposium on code generation and optimization

作者： Barthou, Denis Donadio, Sebastien Carribault, Patrick Duchateau, Alexandre Jalby, William Univ Versailles PRiSM Lab F-78000 Versailles France Bull SA Les Clayes Sous Bois France Univ Versailles LRC ITACA CEA DAM Versailles France

ISBN: (纸本)9780769527642

the increasing complexity of hardware features for recent processors makes high performance code generation very challenging. In particular, several optimization targets have to be pursued simultaneously (minimizing L1/L2/L3/TLB misses and maximizing instruction level parallelism). Very often, these optimization goals impose different and contradictory constraints on the transformations to be applied. We propose a new hierarchical compilation approach for the generation of high performance code relying on the use of state-of-the-art compilers. this approach is not application-dependent and do not require any assembly hand-coding. It relies on the decomposition of the original loop nest into simpler kernels, typically 1D to 2D loops, much simpler to optimize. We successfully applied this approach to optimize dense matrix muliply primitives (not only for the square case but to the more general rectangular cases) and convolution. the performance of the optimized codes on Itanium 2 and Pentium 4 architectures outperforms ATLAS and in most cases, matches hand-tuned vendor libraries (e.g. MKL).

关键词： Kernel Tiles Optimizing compilers Libraries Hardware Costs Phased arrays Laboratories Constraint optimization Assembly

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