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An On-the-Fly Method to Exchange Vector Clocks in distributed-Memory Programs 36

An On-the-Fly Method to Exchange Vector Clocks in Distribute...

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36th ieee international parallel and distributed processing symposium (ieee IPDPS)

作者： Schwitanski, Simon Tomski, Felix Protze, Joachim Terboven, Christian Mueller, Matthias S. Rhein Westfal TH Aachen IT Ctr Aachen Germany

ISBN: (纸本)9781665497473

Vector clocks are logical timestamps used in correctness tools to analyze the happened-before relation between events in parallel program executions. In particular, race detectors use them to find concurrent conflicting memory accesses, and replay tools use them to reproduce or find alternative execution paths. To record the happened-before relation with vector clocks, tool developers have to consider the different synchronization concepts of a programming model, e.g., barriers, locks, or message exchanges. Especially in distributed-memory programs, various concepts result in explicit and implicit synchronization between processes. Previously implemented vector clock exchanges are often specific to a single programming model, and a translation to other programming models is not trivial. Consequently, analyses relying on the vector clock exchange remain model-specific. This paper proposes an abstraction layer for on-the-fly vector clock exchanges for distributed-memory programs. Based on the programming models MPI, OpenSHMEM, and GASPI, we define common synchronization primitives and explain how model-specific procedures map to our model-agnostic abstraction layer. The exchange model is general enough also to support synchronization concepts of other parallel programming models. We present our implementation of the vector clock abstraction layer based on the Generic Tool Infrastructure with translators for MPI and OpenSHMEM. In an overhead study using the SPEC MPI 2007 benchmarks, the slowdown of the implemented vector clock exchange ranges from 1.1x to 12.6x for runs with up to 768 processes.

关键词： Vector clock distributed memory synchronization correctness tools MPI OpenSHMEM GASPI

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Shared-Memory parallel Dynamic Louvain Algorithm for Community Detection

Shared-Memory Parallel Dynamic Louvain Algorithm for Communi...

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1st international Conference on Smart Energy Systems and Artificial Intelligence (SESAI)

作者： Sahu, Subhajit Kothapalli, Kishore Banerjee, Dip Sankar Int Inst Informat Technol Hyderabad Hyderabad 500032 India Indian Inst Tehnol Jodhpur Surpura Bypass Rd Karwar 342030 Rajasthan India

ISBN: (纸本)9798350364613;9798350364606

Community detection refers to the identification of coherent partitions in networks. In this poster, we present a parallel dynamic Louvain algorithm that finds conummities in rapidly evolving graphs. Given a batch update of edge deletions or insertions, our algorithm identifies an approximate set of affected vertices in the graph with minimal overhead and updates the community membership of each vertex. This process repeats until convergence. Our approach achieves a mean speedup of 7.3 x, compared to our parallel and optimized implementation of Delta-screening combined with Louvain, a recently proposed stateof-the-art approach.

关键词： Population dynamics

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Automated Calibration of parallel and distributed Computing Simulators: A Case Study

Automated Calibration of Parallel and Distributed Computing ...

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1st international Conference on Smart Energy Systems and Artificial Intelligence (SESAI)

作者： McDonald, Jesse Horzela, Maximilian Suter, Frederic Casanova, Henri Univ Hawaii Manoa Honolulu HI 96822 USA Karlsruhe Inst Technol Karlsruhe Germany Oak Ridge Natl Lab Oak Ridge TN USA

ISBN: (纸本)9798350364613;9798350364606

Many parallel and distributed computing research results are obtained in simulation, using simulators that mimic real-world executions on some target system. Each such simulator is configured by picking values for parameters that define the behavior of the underlying simulation models it implements. The main concern for a simulator is accuracy: simulated behaviors should be as close as possible to those observed in the real-world target system. This requires that values for each of the simulator's parameters be carefully picked, or "calibrated," based on ground truth real-world executions. Examining the current state of the art shows that simulator calibration, at least in the field of parallel and distributed computing, is often undocumented (and thus perhaps often not performed) and, when documented, is described as a labor-intensive, manual process. In this work we evaluate the benefit of automating simulation calibration using simple algorithms. Specifically, we use a real-world case study from the field of High Energy Physics and compare automated calibration to calibration performed by a domain scientist. Our main finding is that automated calibration is on par with or significantly outperforms the calibration performed by the domain scientist. Furthermore, automated calibration makes it straightforward to operate desirable trade-offs between simulation accuracy and simulation speed.

关键词： Simulation of distributed computing platforms and applications Simulation accuracy and scalability Simulation calibration

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Low-Depth Spatial Tree Algorithms 38

Low-Depth Spatial Tree Algorithms

引用

international parallel and distributed processing symposium (IPDPS)

作者： Baumann, Yves Ben-Nun, Tal Besta, Maciej Gianinazzi, Lukas Hoefler, Torsten Luczynski, Piotr Swiss Fed Inst Technol Zurich Switzerland

ISBN: (纸本)9798350387117;9798350387124

Contemporary accelerator designs exhibit a high degree of spatial localization, wherein two-dimensional physical distance determines communication costs between processing elements. This situation presents considerable algorithmic challenges, particularly when managing sparse data, a pivotal component in progressing data science. The spatial computer model quantifies communication locality by weighting processor communication costs by distance, introducing a term named energy. Moreover, it integrates depth, a widely-utilized metric, to promote high parallelism. We propose and analyze a framework for efficient spatial tree algorithms within the spatial computer model. Our primary method constructs a spatial tree layout that optimizes the locality of the neighbors in the compute grid. This approach thereby enables locality-optimized messaging within the tree. Our layout achieves a polynomial factor improvement in energy compared to utilizing a PRAM approach. Using this layout, we develop energy-efficient treefix sum and lowest common ancestor algorithms, which are both fundamental building blocks for other graph algorithms. With high probability, our algorithms exhibit near-linear energy and poly-logarithmic depth. Our contributions augment a growing body of work demonstrating that computations can have both high spatial locality and low depth. Moreover, our work constitutes an advancement in the spatial layout of irregular and sparse computations.

关键词： Graph algorithms parallel algorithms Trees Routing and layout distributed data structures Dataflow architectures Adaptable architectures

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Compiler -Driven SWAR parallelism for High -Performance Bitboard Algorithms

Compiler -Driven SWAR Parallelism for High -Performance Bitb...

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1st international Conference on Smart Energy Systems and Artificial Intelligence (SESAI)

作者： Fey, Florian Gorlatch, Sergei Univ Munster Munster Germany

ISBN: (纸本)9798350364613;9798350364606

parallel high-performance computing relies on cache -efficient, branch-free algorithms that are often expressed as imperative computations over multi-dimensional arrays. Numerous problem domains, spanning from image processing to graph analytics, and from state space exploration in combinatorial optimization to computer Chess, require carefully crafted algorithms that capitalize on patterns inherent in the underlying problem structure. A renowned technique, SIMD-Within-A-Register (SWAR), harnesses integer arithmetic to attain significant hardware parallelism. However, this approach typically demands labor-intensive efforts from domain experts with specialized knowledge of the underlying hardware architecture. We therefore present a compiler-driven approach that automates the transformation of conventional array -based C-code into highly tuned integer arithmetic, exploiting SWAR parallelism without the requirement of tedious manual optimization efforts. Our approach achieves substantial performance improvements, exhibiting an average speedup of 30x compared to conventional array-based implementations.

关键词： High-Performance Computing Cache-Efficient Algorithms parallel Computing SWAR SIMD-parallelism Compiler-Driven Optimization

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A Streaming System for Large-scale Temporal Graph Mining of Reddit Data 36

A Streaming System for Large-scale Temporal Graph Mining of ...

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36th ieee international parallel and distributed processing symposium (ieee IPDPS)

作者： Huber, Andreas Schroeder, Daniel Thilo Pogorelov, Konstantin Griwodz, Carsten Langguth, Johannes Univ Oslo Simula Res Lab Oslo Norway Simula Res Lab Oslo Norway Univ Oslo Oslo Norway BI Norwegian Business Sch Simula Res Lab Oslo Norway

ISBN: (纸本)9781665497473

The study of online social networks has become a major topic of research within the last decade, and many aspects of the networks and the behavior of their users have been investigated. The majority of research efforts has been directed at Twitter, which grants limited data accesses to researchers and provides detailed information. However, recently, important social and economic phenomena such as WallStreetBets or Antiwork have originated on Reddit, which has thus become an important field of investigation in its own right, and, due to its open nature, all Reddit data is available to study. As a consequence, in contrast to Twitter, where it is difficult to obtain large amounts of data, the main challenge of researching Reddit is to handle the vast amounts of data that are freely available. Here, we present the Reddit Dataset Stream Pipeline (RDSP), a simple and efficient parallel system based on Akka Streams that is capable of processing the entire Reddit dataset. We demonstrate how to build massive temporal graphs between subreddits from a parallel streamed dataset. We investigate the generated graphs and present experimental results. Moreover, we publish both the datasets as well as the codebase in order to invite researchers from different fields to contribute and profit from this work.

关键词： Reddit Stream processing parallel processing Computational Social Science

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Synchronous parallel multisplitting method with convergence acceleration using a local Krylov-based minimization for solving linear systems 36

Synchronous parallel multisplitting method with convergence ...

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36th ieee international parallel and distributed processing symposium (ieee IPDPS)

作者： Tchakorom, Medane A. Couturier, Raphael Charr, Jean-Claude Univ Bourgogne Franche Comte UBFC CNRS FEMTO ST Inst Belfort France

ISBN: (纸本)9781665497473

Computer simulations of physical phenomena, such as heat transfer, often require the solution of linear equations. These linear equations occur in the form Ax = b, where A is a matrix, b is a vector, and x is the vector of unknowns. Iterative methods are the most adapted to solve large linear systems because they can be easily parallelized. This paper presents a variant of the multisplitting iterative method with convergence acceleration using the Krylov-based minimization method. This paper particularly focuses on improving the convergence speed of the method with an implementation based on the PETSc (Portable Extensible Toolkit for Scientific Computation) library. This was achieved by reducing the need for synchronization - data exchange - during the minimization process and adding a preconditioner before the multisplitting method. All experiments were performed either over one or two sites of the Grid5000 platform and up to 128 cores were used. The results for solving a 2D Laplacian problem of size 1024(2) components, show a speed up of up to 23X and 86X when respectively compared to the algorithm in [8] and to the general multisplitting implementation.

关键词： Iterative methods Krylov methods Multisplitting Linear Solvers PETSc MPI

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Accelerating Lossy and Lossless Compression on Emerging BlueField DPU Architectures 38

Accelerating Lossy and Lossless Compression on Emerging Blue...

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international parallel and distributed processing symposium (IPDPS)

作者： Li, Yuke Kashyap, Arjun Chen, Weicong Guo, Yanfei Lu, Xiaoyi Univ Calif Merced Merced CA 95343 USA Argonne Natl Lab Lemont IL USA

ISBN: (纸本)9798350387117;9798350387124

Data compression has become a crucial technique in addressing performance bottlenecks caused by increasing data volumes in High-Performance Computing (HPC), Big Data, and Deep Learning (DL). Despite its potential to boost system performance, recent studies have identified significant challenges with existing compression methods, mainly due to their high computational demands amidst continuously growing data sizes. Concurrently, the advent of Data processing Units (DPUs), equipped with programmable System-on-Chip (SoC) and specialized compression accelerators, offers a promising opportunity to alter the landscape of data compression. This paper explores the complexities and potential of leveraging NVIDIA BlueField DPUs to accelerate lossy and lossless compression. Towards this, we introduce PEDAL, an innovative library that leverages the hardware capabilities of DPUs to unify and optimize data compression designs. Moreover, we seamlessly co-design PEDAL with the popular MPICH MPI library, demonstrating up to 101x speedup in compression time and 88x decrease in communication latency. Drawing on these achievements, we share our experience with various research communities about accelerating data compression on DPUs in communication-oriented HPC scenarios.

关键词： Data processing Unit (DPU) BlueField DPU Lossy Compression Lossless Compression

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MAAD: A distributed Anomaly Detection Architecture for Microservices Systems 38

MAAD: A Distributed Anomaly Detection Architecture for Micro...

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international parallel and distributed processing symposium (IPDPS)

作者： Tan, Rongyuan Li, Zhuozhao Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen Peoples R China Southern Univ Sci & Technol Res Inst Trustworthy Autonomous Syst Shenzhen Peoples R China

ISBN: (纸本)9798350387117;9798350387124

Anomaly detection plays a critical role in microservices systems by enabling system administrators to promptly detect and respond to anomalies. However, existing anomaly detection systems often necessitate the centralization of log and trace data from diverse system components and rely on resource-intensive statistical methods or deep learning models for analysis. This approach impedes real-time anomaly detection and requires a significant demand on computing resources. In this paper, we design a multi-agent-based, distributed anomaly detection architecture called MAAD to address the limitations. MAAD consists of a collection of agents that cooperate together to identify abnormal behaviors in a distributed manner. Each agent is deployed along with a single service and applies lightweight machine learning techniques to perform local anomaly detection based on its own logs, local context, and information extracted from its parent span service. To preserve the graph information in a microservices request, an agent can communicate essential features with each other, taking into account the collective patterns learned from the prior services. We evaluate the effectiveness of MAAD on two microservices datasets, TrainTicket and MicroSS, and show that MAAD achieved high precision (up to 95.8%) and recall (up to 99.6%), outperforming state-of-the-art centralized anomaly detection approaches. Compared to centralized approaches, MAAD reduces the amount of transferred data before anomaly detection by approximately 88%, facilitating real-time anomaly detection. Furthermore, the lightweight nature of MAAD allows for rapid anomaly detection with minimal impact on microservices systems. Compared to DeepLog, MAAD saves approximately 92% detection time without using GPU accelerators.

关键词： anomaly detection Microservices system multi-agent

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distributed Algorithms for the Graph Biconnectivity and Least Common Ancestor Problems 36

Distributed Algorithms for the Graph Biconnectivity and Leas...

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36th ieee international parallel and distributed processing symposium (ieee IPDPS)

作者： Bogle, Ian Slota, George M. Rensselaer Polytech Inst Comp Sci Dept Troy NY 12180 USA

ISBN: (纸本)9781665497473

Graph connectivity analysis is one of the primary ways to analyze the topological structure of social networks. Graph biconnectivity decompositions are of particular interest due to how they identify cut vertices and cut edges in a network. We present the first, to our knowledge, implementation of a distributed-memory parallel biconnectivity algorithm. As part of our algorithm, we also require the computation of least common ancestors (LCAs) of non-tree edge endpoints in a BFS tree. As such, we also propose a novel distributed algorithm for the LCA problem. Using our implementations, we observe up to a 14.8 x speedup from 1 to 128 MPI ranks for computing a biconnectivity decomposition.

关键词： distributed processing Social networking (online) Conferences distributed algorithms

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