Proceedings of the 47th International Conference on Parallel Processing最新文献_第3页

The Case for Semi-Permanent Cache Occupancy: Understanding the Impact of Data Locality on Network Processing 半永久缓存占用的案例:理解数据局部性对网络处理的影响

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225130

Matthew G. F. Dosanjh, S. M. Ghazimirsaeed, Ryan E. Grant, W. Schonbein, M. Levenhagen, P. Bridges, A. Afsahi

引用次数: 8

Reference-distance Eviction and Prefetching for Cache Management in Spark Spark中缓存管理的引用距离提取和预取

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225087

T. B. G. Perez, Xiaobo Zhou, Dazhao Cheng

{"title":"Reference-distance Eviction and Prefetching for Cache Management in Spark","authors":"T. B. G. Perez, Xiaobo Zhou, Dazhao Cheng","doi":"10.1145/3225058.3225087","DOIUrl":"https://doi.org/10.1145/3225058.3225087","url":null,"abstract":"Optimizing memory cache usage is vital for performance of in-memory data-parallel frameworks such as Spark. Current data-analytic frameworks utilize the popular Least Recently Used (LRU) policy, which does not take advantage of data dependency information available in the application's directed acyclic graph (DAG). Recent research in dependency-aware caching, notably MemTune and Least Reference Count (LRC), have made important improvements to close this gap. But they do not fully leverage the DAG structure, which imparts information such as the time-spatial distribution of data references across the workflow, to further improve cache hit ratio and application runtime. In this paper, we propose and develop a new cache management policy, Most Reference Distance (MRD) that utilizes DAG information to optimize both eviction and prefetching of data to improve cache management. MRD takes into account the relative stage distance of each data block reference in the application workflow, effectively evicting the furthest and least likely data in the cache to be used, while aggressively prefetching the nearest and most likely data that will be needed, and in doing so, better overlapping computation with I/O time. Our experiments with a Spark implementation, utilizing popular benchmarking workloads show that, MRD has low overhead and improves performance by an average of 53% compared to LRU, and up to 68% and 45% when compared to MemTune and LRC respectively. It works best for I/O-intensive workloads.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"5 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132934145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 19

MPI-Vector-IO: Parallel I/O and Partitioning for Geospatial Vector Data MPI-Vector-IO:地理空间矢量数据的并行I/O和分区

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225105

S. Puri, Anmol Paudel, S. Prasad

{"title":"MPI-Vector-IO: Parallel I/O and Partitioning for Geospatial Vector Data","authors":"S. Puri, Anmol Paudel, S. Prasad","doi":"10.1145/3225058.3225105","DOIUrl":"https://doi.org/10.1145/3225058.3225105","url":null,"abstract":"In recent times, geospatial datasets are growing in terms of size, complexity and heterogeneity. High performance systems are needed to analyze such data to produce actionable insights in an efficient manner. For polygonal a.k.a vector datasets, operations such as I/O, data partitioning, communication, and load balancing becomes challenging in a cluster environment. In this work, we present MPI-Vector-IO 1, a parallel I/O library that we have designed using MPI-IO specifically for partitioning and reading irregular vector data formats such as Well Known Text. It makes MPI aware of spatial data, spatial primitives and provides support for spatial data types embedded within collective computation and communication using MPI message-passing library. These abstractions along with parallel I/O support are useful for parallel Geographic Information System (GIS) application development on HPC platforms. Performance evaluation is done on Lustre and GPFS filesystems. MPI-Vector-IO scales well with MPI processes and file size and achieves bandwidth up to 22 GB/s for common spatial data access patterns. We observed that independent file read functions performed better than collective functions in MPI-IO for contiguous access pattern on Lustre. In general, the I/O is improved by one to two orders of magnitude over real-world datasets using up to 1152 CPU cores. Spatial Join query is used as an exemplar to demonstrate an end-to-end application using MPI-Vector-IO.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114595428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

A Framework for Auto-Parallelization and Code Generation: An Integrative Case Study with Legacy FORTRAN Codes 自动并行化和代码生成框架:遗留FORTRAN代码的综合案例研究

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225143

K. Krommydas, P. Sathre, Ruchira Sasanka, Wu-chun Feng

{"title":"A Framework for Auto-Parallelization and Code Generation: An Integrative Case Study with Legacy FORTRAN Codes","authors":"K. Krommydas, P. Sathre, Ruchira Sasanka, Wu-chun Feng","doi":"10.1145/3225058.3225143","DOIUrl":"https://doi.org/10.1145/3225058.3225143","url":null,"abstract":"GLAF, short for Grid-based Language and Auto-parallelization Framework, is a programming framework that seeks to democratize parallel programming by facilitating better productivity in parallel computing via an intuitive graphical programming interface (GPI) that automatically parallelizes and generates code in many languages. Originally, GLAF addressed program development from scratch via the GPI; but this unduly restricted GLAF's utility to creating new codes only. Thus, this paper extends GLAF by enabling program development from pre-existing kernels of interest, which can then be easily and transparently integrated into existing legacy codes. Specifically, we address the theoretical and practical limitations of integration and interoperability of auto-generated parallel code within existing FORTRAN codes; enhance GLAF to overcome these limitations; and present an integrative case study and evaluation of the enhanced GLAF via the implementation of important kernels in two NASA codes: (1) the Synoptic Surface & Atmospheric Radiation Budget (SARB), part of the Clouds and the Earth's Radiant Energy System (CERES), and (2) the Fully Unstructured Navier-Stokes (FUN3D) suite for computational fluid dynamics.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129014390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Parallelizing Pruning-based Graph Structural Clustering 并行化基于剪枝的图结构聚类

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225063

Yulin Che, Shixuan Sun, Qiong Luo

{"title":"Parallelizing Pruning-based Graph Structural Clustering","authors":"Yulin Che, Shixuan Sun, Qiong Luo","doi":"10.1145/3225058.3225063","DOIUrl":"https://doi.org/10.1145/3225058.3225063","url":null,"abstract":"A common class of graph structural clustering algorithms, pioneered by SCAN (Structural Clustering Algorithm for Networks), not only find clusters among vertices but also classify vertices as cores, hubs and outliers. However, these algorithms suffer from efficiency issues due to the great amount of computation required on structural similarity among vertices. Pruning-based SCAN algorithms improve efficiency by reducing the amount of computation. Nevertheless, this structural similarity computation is still the performance bottleneck, especially on big graphs of billions of edges. In this paper, we propose to parallelize pruning-based SCAN algorithms on multi-core CPUs and Intel Xeon Phi Processors (KNL) with multiple threads and vectorized instructions. Specifically, we design ppSCAN, a multi-phase vertex computation based parallel algorithm, to avoid redundant computation and achieve scalability. Moreover, we propose a pivot-based vectorized set intersection algorithm for structural similarity computation. Experimental results show that ppSCAN is scalable on both CPU and KNL with respect to the number of threads. On the 1.8 billion-edge graph friendster, our ppSCAN completes within 65 seconds on KNL (64 physical cores with hyper-threading). This performance is 100x-130x faster than our single-threaded version, and up to 250x faster than pSCAN, the state-of-the-art sequential algorithm, on the same platform.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128721343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

PRIONN

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225091

Michael R. Wyatt, Stephen Herbein, T. Gamblin, A. Moody, D. Ahn, M. Taufer

{"title":"PRIONN","authors":"Michael R. Wyatt, Stephen Herbein, T. Gamblin, A. Moody, D. Ahn, M. Taufer","doi":"10.1145/3225058.3225091","DOIUrl":"https://doi.org/10.1145/3225058.3225091","url":null,"abstract":"For job allocation decision, current batch schedulers have access to and use only information on the number of nodes and runtime because it is readily available at submission time from user job scripts. User-provided runtimes are typically inaccurate because users overestimate or lack understanding of job resource requirements. Beyond the number of nodes and runtime, other system resources, including IO and network, are not available but play a key role in system performance. There is the need for automatic, general, and scalable tools that provide accurate resource usage information to schedulers so that, by becoming resource-aware, they can better manage system resources. We tackle this need by presenting a tool for Predicting Runtime and IO using Neural Networks (PRIONN). PRIONN automates prediction of per-job runtime and IO resource usage, enabling IO-aware scheduling on HPC systems. The novelty of our tool is the input of whole job scripts into deep learning models that allows complete automation of runtime and IO resource predictions. We demonstrate the power of PRIONN with runtime and IO resource predictions applied to IO-aware scheduling for real HPC data. Specifically, we achieve over 75% mean and 98% median accuracy for runtime and IO predictions across 300,000 jobs from a real HPC machine. We combine our per-job runtime and IO predictions with queue and system simulations to predict future system IO usage accurately. We predict over 50% of IO bursts in advance on a real HPC system.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127415461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 31

Load-Balanced Slim Fly Networks 负载均衡瘦蝇网络

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225081

Md. Shafayat Rahman, Md Atiqul Mollah, Peyman Faizian, Xin Yuan

{"title":"Load-Balanced Slim Fly Networks","authors":"Md. Shafayat Rahman, Md Atiqul Mollah, Peyman Faizian, Xin Yuan","doi":"10.1145/3225058.3225081","DOIUrl":"https://doi.org/10.1145/3225058.3225081","url":null,"abstract":"The Slim Fly topology has recently been proposed for the future generation supercomputers. It has small diameter and relies on the Universal Globally Adaptive Load-balanced (UGAL) routing, which adapts the routes between minimal (MIN) routing and Valiant Load-Balancing (VLB) routing to exploit the network capacity. In this work, we show that the current Slim Fly is not load-balanced for both MIN routing and VLB routing, in that certain links in the network have a significantly higher probability to carry traffic than others. As such, hot spots are more likely to form on such links. We propose two approaches to address this problem and to make Slim Fly load-balanced: (1) modifying the topology by selectively increasing the bandwidth of the potential hot-spot links so that the original routing becomes load-balanced, and (2) modifying the routing scheme by using a weighted VLB routing to distribute the traffic in a more load balanced fashion than the original VLB routing on the original Slim Fly. The results of our performance analysis and simulation demonstrate that both approaches result in more effective Slim Fly than its current form.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"4 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113981447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

A Comprehensive Study on Bugs in Actor Systems Actor系统中bug的综合研究

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225139

Brandon Hedden, Xinghui Zhao

引用次数: 5

Partitioning and Communication Strategies for Sparse Non-negative Matrix Factorization 稀疏非负矩阵分解的划分和通信策略

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225127

O. Kaya, R. Kannan, Grey Ballard

引用次数: 7

Improving MPI Multi-threaded RMA Communication Performance 改进MPI多线程RMA通信性能

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225114

N. Hjelm, Matthew G. F. Dosanjh, Ryan E. Grant, Taylor L. Groves, P. Bridges, D. Arnold

{"title":"Improving MPI Multi-threaded RMA Communication Performance","authors":"N. Hjelm, Matthew G. F. Dosanjh, Ryan E. Grant, Taylor L. Groves, P. Bridges, D. Arnold","doi":"10.1145/3225058.3225114","DOIUrl":"https://doi.org/10.1145/3225058.3225114","url":null,"abstract":"One-sided communication is crucial to enabling communication concurrency. As core counts have increased, particularly with many-core architectures, one-sided (RMA) communication has been proposed to address the ever increasing contention at the network interface. The difficulty in using one-sided (RMA) communication with MPI is that the performance of MPI implementations using RMA with multiple concurrent threads is not well understood. Past studies have been done using MPI RMA in combination with multi-threading (RMA-MT) but they have been performed on older MPI implementations lacking RMA-MT optimizations. In addition prior work has only been done at smaller scale (<=512 cores). In this paper, we describe a new RMA implementation for Open MPI. The implementation targets scalability and multi-threaded performance. We describe the design and implementation of our RMA improvements and offer an evaluation that demonstrates scaling to 524,288 cores, the full size of a leading supercomputer installation. In contrast, the previous implementation failed to scale past approximately 4,096 cores. To evaluate this approach, we then compare against a vendor optimized MPI RMA-MT implementation with microbenchmarks, a mini-application, and a full astrophysics code at large scale on a many-core architecture. This is the first time that an evaluation at large scale on many-core architectures has been done for MPI RMA-MT (524,288 cores) and the first large scale application performance comparison between two different RMA-MT optimized MPI implementations. The results show a 8.6% benefit to our optimized open source MPI for a full application code running on 512K cores.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121693253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17