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Development of an Integrated Multidiagnostic to Assess the High-Z Impurity Fluxes in the Metallic Environment of WEST Using IMAS

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IEEE TRANSACTIONS ON PLASMA SCIENCE 2022年第11期50卷 4251-4256页

作者： Grosjean, Alex Radenac, T. Fedorczak, N. Donovan, D. C. Guillemaut, C. Johnson, C. A. Gunn, J. P. Ardizzone, P. L. Clairet, F. Easley, D. C. Gil, C. Klepper, C. C. Kosslow, S. R. Unterberg, E. A. Team, West Univ Tennessee Dept Nucl Engn Knoxville TN 37996 USA CEA Inst Res Fus Magnet Confinement F-13108 St Paul Les Durance France Oak Ridge Natl Lab Oak Ridge TN 37831 USA

WEST is an actively cooled, long-pulse tokamak with nearly all plasma-facing components (PFC) made of tungsten. One of the aims of WEST is to study plasma operations with tungsten PFCs in preparation for long-pulse operations on high-Z divertor devices, such as ITER. For long-pulse operation, the high-Z impurity content and transport to the core plasma are critical concerns that require further measurement and interpretation to improve plasma performance and PFC durability. This work details the impurity influxes in WEST during a series of discharges in which the lower hybrid (LH) injected power was incrementally increased. An analysis has been performed of measurements collected from an array of edge diagnostics. Visible spectroscopy was utilized to measure the spectral radiances generated by fuel particles (D) and impurities (W , O, and C) at the divertor and at the antennas with a newly developed spectral peak-fitting tool used to analyze the data in WEST. The scrape-off layer (SOL) plasma conditions (n(e) and T-e) measured at the divertor target with flush Langmuir probes and near the outer mid-plane (OMP) using reciprocating Langmuir probes (RCPs) are used to evaluate the number of ionizations per photons (S/XB) coefficients required to estimate the impurity fluxes obtained with the collisional-radiative model ColRadPy. The array of edge diagnostics discussed in this work, coupled with SOL plasma modeling tools, represents a multidiagnostic interpretative modeling workflow that will continue to be applied to upcoming experimental campaigns on the WEST experiment to assess high-Z impurity transport.

关键词： Impurities Plasmas Spectroscopy Plasma measurements Magnetic separation Probes Bars data flow analysis diagnostic expert systems fusion reactors impurities spectroscopy tokamaks tungsten

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Virtual Power Plant Interactive communication simulation based on OPNET 7

Virtual Power Plant Interactive communication simulation bas...

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7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Fan, Huicong Geng, Shaobo Su, Han Zhao, Jianhua Li, Wenxiao State Grid Hebei Economic Research Institute Hebei China State Grid Hebei Electric Power Co. Ltd Hebei China

ISBN: (纸本)9798350339161

In recent years, distributed new energy represented by photovoltaic technology has been increasingly widely used, and the scale of grid connection is increasing. In response to the increasingly urgent demand for distributed photovoltaic interactive communication, this article analyzes the model of distributed photovoltaic interactive data flow, builds a distributed photovoltaic user interactive communication model based on OPNET software, and builds a small simulation network that includes photovoltaic users and aggregators, verifying the practicality of the model. © 2024 IEEE.

关键词： data flow analysis

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ThreadFuser: A SIMT analysis Framework for MIMD Programs 57

ThreadFuser: A SIMT Analysis Framework for MIMD Programs

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57th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2024

作者： Alawneh, Ahmad Kang, Ni Khairy, Mahmoud Rogers, Timothy G. Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN United States

ISBN: (纸本)9798350350579

The broad usage of accelerators, such as GPUs, faces two important challenges. Developing code for a new accelerator is expensive and unpredictable. Porting large parallel programs from Multiple Instruction Multiple data (MIMD) CPUs to Single Instruction Multiple Thread (SIMT) GPUs involves significant effort that may or may not result in improved performance versus the CPU. This high activation energy to create new workloads introduces the second challenge: Architects and systems researchers lack a diverse SIMT codebase to study new designs. To tackle these challenges, we introduce ThreadFuser, an analysis framework that efficiently and accurately predicts the performance of any pre-written MIMD program on SIMT hardware. ThreadFuser conducts thorough control and data flow analysis on dynamic CPU program traces, determining the impact of lock-step execution on CPU binaries. Thread-Fuser efficiently delivers accurate reports on a MIMD program's divergence and synchronization characteristics. Moreover, ThreadFuser seamlessly integrates with state-of-The-Art GPU simulators to conduct detailed analyses and produce fine-grained performance measurements. We evaluate ThreadFuser on a diverse set of 36 CPU workloads, demonstrating the potential and challenges of executing MIMD code on a SIMT machine. We demonstrate ThreadFuser's potential to inform software development decisions and open new areas to explore in data-parallel hardware design. © 2024 IEEE.

关键词： data flow analysis

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Fast and Precise Interval analysis on Industry code 35

Fast and Precise Interval Analysis on Industry code

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35th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2024

作者： Chimdyalwar, Bharti Tcs Research India

ISBN: (纸本)9798350367041

This paper introduces an algorithm for data-flow analysis using functional approach to solve infinite-height analyses, such as interval analysis. The algorithm utilizes function summaries and employs a combination of one bottom-up and multiple top-down traversals over the call graph, referred to as OneBMultiT. The OneBMultiT approach is further extended to enable incremental analysis for code changes by selectively analysing only affected functions, referred to as ONEBMULTITincr. We have implemented the interval analysis and incrementalized it using the proposed algorithms in our proprietary static analysis tool. The analysis results of interval analysis are used to validate properties such as array index within bounds, non-zero division, and the prevention of arithmetic overflow/underflow on real-life applications. Our evaluation shows that 93% properties on four automotive applications are successfully validated. Additionally, ONEBMULTITincr approach yields up to 83% reduction in analysis time and a significant reduction in reported alarms in comparison to whole program analysis, demonstrating its practical benefit on real-world evolving applications. © 2024 IEEE.

关键词： data flow analysis

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Increasing the Thoroughness of data flow Testing with the Required k-Use Chains 24

Increasing the Thoroughness of Data Flow Testing with the Re...

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10th International Conference on Computer Technology Applications, ICCTA 2024

作者： Kolchyn, Oleksandr V Potiyenko, Stepan V V.M. Glushkov Institute of Cybernetics Nas of Ukraine Kyiv Ukraine

ISBN: (纸本)9798400716386

The required k-use chain is a new data flow coverage criterion designed to provide deeper analysis of possible refinements of constraints on program behavior paths. Such refinements represent a feasible chain of usages of the same variable without intermediate redefinitions. The SAT/SMT-based chains selection procedure finds more ranges of values to test and keeps the number of test targets manageable. The criterion strongly increases the level of thoroughness of a test suite compared to the all-uses and demonstrates qualitative improvement of a test suite when used as a test goal in automatic tests generation. This paper describes motivation examples, our experience, and an empirical evaluation of the proposed data flow testing method. © 2024 ACM.

关键词： data flow analysis

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AN ATTEMPT TO UTILIZE FUNCTIONAL MODELING FOR ENHANCED APPLICATION CODE analysis 14

AN ATTEMPT TO UTILIZE FUNCTIONAL MODELING FOR ENHANCED APPLI...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2024

作者： Wei, Zhenwen Wang, Jipu Xu, Yunfei Chen, Sijuan Li, Jin Yang, Ming Liang, Hao Cao, Zufeng Shenzhen Key Laboratory of Nuclear and Radiation Safety Institute for Advanced Study in Nuclear Energy & Safety College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen China Institute of Material Research China Academy of Engineering Physics Mianyang China Nuclear Engineering & Radiological Sciences Bonisteel Blvd Ann ArborMI2355 United States

ISBN: (纸本)9781837242672

Due to the complex and highly interdependent relationships among parameters in system programs, anomalies can lead to abnormal propagation, thereby degrading system performance and potentially inducing measurement or execution errors within the control system. Such errors can adversely affect the stability and safety of a nuclear reactor. To address this issue, this study introduces a function modeling-based analysis method for data anomaly traceback and parameter tuning assistance. This method enables root cause inference of anomalies when program outputs significantly deviate from expected values, facilitating further investigation. For parameter tuning, the method simplifies the direct model of the program through functional combinations, elucidating the data flow of critical parameters. This enhances and accelerates parameter-tuning efforts. Using a radiation dose calculation program as a case study, this paper demonstrates that the proposed method effectively identifies potential root causes of anomalies, simplifies the direct model, clarifies the interrelations among critical parameters, facilitates parameter tuning, and reduces risks associated with human error. © The Institution of Engineering & Technology 2024.

关键词： data flow analysis

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InterArch: Video Transformer Acceleration via Inter-Feature Deduplication with Cube-based dataflow 24

InterArch: Video Transformer Acceleration via Inter-Feature ...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Wang, Xuhang Song, Zhuoran Liang, Xiaoyao Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798400706011

In the realm of video-oriented tasks, Video Transformer models (VidT), an evolution from vision Transformers (ViT), have demonstrated considerable success. However, their widespread application is constrained by substantial computational demands and high energy consumption. Addressing these limitations and thus improving VidT efficiency has become a hot topic. Current methodologies solve this challenge by dividing a video into several features and applying intra-feature sparsity. However, they neglect the crucial point of inter-feature redundancy and often entail prolonged latency in fine-tuning phases. In response, this paper introduces InterArch, a tailored framework designed to significantly enhance VidT efficiency. We first design a novel inter-feature sparsity algorithm consisting of hierarchical deduplication and recovery. The deduplication phase capitalizes on temporal similarities at both block and element levels, enabling the elimination of redundant computations across features in both coarse-grained and fine-grained manners. To prevent long-latency fine-tuning, we employ a lightweight recovery mechanism that constructs approximate features for the sparsified data. Furthermore, InterArch incorporates a regular dataflow strategy, which consolidates sparse features and effectively translates sparse computations into dense ones. Complementing this, we develop a spatial array architecture equipped with augmented processing elements (PEs), specifically optimized for our proposed dataflow. Extensive experiment results demonstrate that InterArch can achieve satisfactory performance speedups and energy saving. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： data flow analysis

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Two Sparsification Strategies for Accelerating Demand-Driven Pointer analysis

Two Sparsification Strategies for Accelerating Demand-Driven...

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2024 Software Engineering, SE 2024

作者： Karakaya, Kadiray Bodden, Eric Paderborn University Heinz Nixdorf Institute Fürstenallee 11 Paderborn33102 Germany Fraunhofer IEM Zukunftsmeile 1 Paderborn33102 Germany

ISBN: (纸本)9783885797371

This work has been published as a full paper at ICST’23 [KB23]. In the context of real-world static program analysis, precise data-flow analyses rely on pointer analysis to resolve aliasing. Demand-driven pointer analysis aims to improve the scalability, by computing information only for variables on which a demand is raised, through a points-to or alias query. Yet, research has shown that when applied to large-scale programs even demand-driven analyses can become expensive regarding memory and runtime. This paper thus investigates to what extent demand-driven pointer analysis can be accelerated further if being executed over a sparse control-flow graph (CFG), specialized to those queries. We investigate two designs: First, type-aware sparsification, in which the resulting CFG only consists of statements containing variables that are type-compatible with the query variable. Second, alias-aware sparsification, where the resulting CFG consists of the def-use chains of the query variable and all its intra-procedural aliases. We implement both designs in SparseBoomerang by extending Boomerang, a pointer analysis framework based on push-down systems. We evaluate SparseBoomerang by comparing it to Boomerang in terms of precision and performance. On the PointerBench micro-benchmark suite for alias analysis, SparseBoomerang maintains the precision of Boomerang, in both designs. We evaluate the runtime and memory performance of SparseBoomerang by using flowDroid as a taint analysis client on real-world apps. Compared to the baseline Boomerang, on average SparseBoomerang solves alias queries 2.4x faster when using the type-aware sparsification strategy, and 2.8x faster when using the alias-aware variant with negligible memory overhead. © 2024 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： data flow analysis

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OpenCML: An Open Customizable Modeling Language for Directed Acyclic Graphs 22

OpenCML: An Open Customizable Modeling Language for Directed...

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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Wei, Zhenjie Xing, Weiwei Liu, Weibin Zou, Zhiyuan Chen, Genxiang Beijing Jiaotong University School of Software Engineering Beijing China Beijing Jiaotong University Institute of Information Science Beijing China Beijing Information Science and Technology University Computer School Beijing China Minzu University of China College of Science Beijing China

ISBN: (纸本)9798331509712

Directed Acyclic Graphs (DAGs) are widely utilized across various domains for tasks such as graph algorithms, data flow analysis, program optimization, and machine learning. Representing DAGs using General-purpose Programming Languages (GPLs) or data Serialization Formats (DSFs) can lead to complex and obscure expressions, making it challenging to comprehend and manage the codebase. Domain-Specific Languages (DSLs) offer a more tailored approach, but come with limitations and development overhead. This paper introduces the Open Customizable Modeling Language (OpenCML), a universal DAG modeling language specification that aims to provide a standardized and customizable framework for modeling and scripting DAGs. Evaluations demonstrate that OpenCML offers expressive power, customizability, and interoperability, simplifying the learning process and providing a powerful solution for DAG modeling and scripting. © 2024 IEEE.

关键词： data flow analysis

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Partial Redundancy Elimination in Two Iterative data flow Analyses 38

Partial Redundancy Elimination in Two Iterative Data Flow An...

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38th European Conference on Object-Oriented Programming, ECOOP 2024

作者： Roy, Reshma Sreekala, S. Paleri, Vineeth National Institute of Technology Calicut India

ISBN: (纸本)9783959773416

Partial Redundancy Elimination (PRE) is a powerful and well-known code optimization. The idea to combine Common Subexpression Elimination and Loop Invariant Code Motion optimizations into a single optimization was originally conceived by Morel and Renvoise. Their algorithm is bidirectional in nature and was not complete and optimal. Later, Knoop et al. proposed the first complete and optimal algorithm, Lazy Code Motion (LCM), which takes four unidirectional data flow analyses. In a recent paper, Roy et al. proposed an algorithm for PRE that uses three iterative data flow analyses. Here, we propose an efficient algorithm for PRE, which takes only two iterative data flow analyses followed by two computation passes over the program. The algorithm is both computationally and lifetime optimal. The proposed algorithm computes the information required for performing the transformation in two passes over the program without considering safety. The two iterative data flow analyses are required for making the transformation safe. The use of well-known data flow analyses, i.e., available expressions analysis and anticipated expressions analysis, makes the algorithm simple to understand and easy to prove its correctness. The proposed algorithm is more efficient than the existing algorithms since it takes only two iterative data flow analyses. The efficiency of the proposed algorithm is demonstrated by implementing it in LLVM Compiler Infrastructure and comparing the time taken with other selected best-known algorithms. © Reshma Roy, Sreekala S, and Vineeth Paleri

关键词： data flow analysis

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