Proceedings of the 47th International Conference on Parallel Processing最新文献_第2页

Nemo

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225123

Mohamed Mohamedin, Sebastiano Peluso, Masoomeh Javidi Kishi, Ahmed Hassan, R. Palmieri

引用次数: 5

A Write-efficient and Consistent Hashing Scheme for Non-Volatile Memory 非易失性存储器的写效率和一致性哈希方案

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225109

Xiaoyi Zhang, D. Feng, Yu Hua, Jianxi Chen, Mandi Fu

{"title":"A Write-efficient and Consistent Hashing Scheme for Non-Volatile Memory","authors":"Xiaoyi Zhang, D. Feng, Yu Hua, Jianxi Chen, Mandi Fu","doi":"10.1145/3225058.3225109","DOIUrl":"https://doi.org/10.1145/3225058.3225109","url":null,"abstract":"The development of non-volatile memory technologies (NVMs) has attracted interest in designing data structures that are efficiently adapted to NVMs. In this context, several NVM-friendly hashing schemes have been proposed to reduce extra writes to NVMs, which have asymmetric properties of reads and writes and limited write endurance compared with traditional DRAM. However, these works neither consider the cost of cacheline flush and memory fence nor provide mechanisms to maintain data consistency in case of unexpected system failures. In this paper, we propose a write-efficient and consistent hashing scheme, called group hashing. The basic idea behind group hashing is to reduce the consistency cost while guaranteeing data consistency in case of unexpected system failures. Our group hashing consists of two major contributions: (1) We use 8-byte failure-atomic write to guarantee the data consistency, which eliminates the duplicate copy writes to NVMs, thus reducing the consistency cost of the hash table structure. (2) In order to improve CPU cache efficiency, our group hashing leverages a novel technique, i.e., group sharing, which divides the hash table into groups and deploys a contiguous memory space in each group to deal with hash collisions, thus reducing CPU cache misses to obtain higher performance in terms of request latency. We have implemented group hashing and evaluated the performance by using three real-world traces. Extensive experimental results demonstrate that our group hashing achieves low request latency as well as high CPU cache efficiency, compared with state-of-the-art NVM-based hashing schemes.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"32 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":"116253878","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: 4

Characterizing the Impact of Soft Errors Affecting Floating-point ALUs using RTL-Ievel Fault Injection 用rtl级故障注入表征软错误对浮点alu的影响

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225089

Omer Subasi, Chun-Kai Chang, M. Erez, S. Krishnamoorthy

{"title":"Characterizing the Impact of Soft Errors Affecting Floating-point ALUs using RTL-Ievel Fault Injection","authors":"Omer Subasi, Chun-Kai Chang, M. Erez, S. Krishnamoorthy","doi":"10.1145/3225058.3225089","DOIUrl":"https://doi.org/10.1145/3225058.3225089","url":null,"abstract":"Strategies to detect, correct, or mitigate the impact of soft errors rely on errors injection experiments. For efficient evaluation, these experiments typically inject errors in software by sampling errors from a candidate distribution. Most often, these strategies randomly select and flip one bit in the output of an instruction. While single-bit flips may constitute a meaningful model for errors affecting hardware, the appropriateness of this model for software-based errors has not been studied. In this paper, we examine the manifestation of errors in the output registers due to errors affecting candidate instructions executed by floating-point arithmetic logic units (ALUs). We inject single-bit flips into the register-transfer level descriptions of floating-point ALUs and analyze the differences between anticipated and observed outputs when executing floating-point addition, subtraction, multiplication, and division. We choose the operands for these instructions randomly and from operands observed in five benchmarks. We observe a rich distribution of errors in the output and analyze their implications for software-based fault injection campaigns.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"476 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":"128331482","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: 4

Massively Scaling the Metal Microscopic Damage Simulation on Sunway TaihuLight Supercomputer 在神威太湖之光超级计算机上大规模扩展金属微观损伤模拟

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225064

Shigang Li, Baodong Wu, Yunquan Zhang, Xianmeng Wang, Jianjiang Li, Changjun Hu, Jue Wang, Yangde Feng, Ningming Nie

引用次数: 17

H2Cloud

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225083

Minghao Zhao, Zhenhua Li, Ennan Zhai, Gareth Tyson, Chen Qian, Zhenyu Li, Leiyu Zhao

{"title":"H2Cloud","authors":"Minghao Zhao, Zhenhua Li, Ennan Zhai, Gareth Tyson, Chen Qian, Zhenyu Li, Leiyu Zhao","doi":"10.1145/3225058.3225083","DOIUrl":"https://doi.org/10.1145/3225058.3225083","url":null,"abstract":"Object storage clouds (e.g., Amazon S3) have become extremely popular due to their highly usable interface and cost-effectiveness. They are, therefore, widely used by various applications (e.g., Dropbox) to host user data. However, because object storage clouds are flat and lack the concept of a directory, it becomes necessary to maintain file meta-data and directory structure in a separate index cloud. This paper investigates the possibility of using a single object storage cloud to efficiently host the whole filesystem for users, including both the file content and directories, while avoiding meta-data loss caused by index cloud failures. We design a novel data structure, Hierarchical Hash (or H2), to natively enable the efficient mapping from filesystem operations to object-level operations. Based on H2, we implement a prototype system, H2Cloud, that can maintain large filesystems of users in an object storage cloud and support fast directory operations. Both theoretical analysis and real-world experiments confirm the efficacy of our solution: H2Cloud achieves faster directory operations than OpenStack Swift by orders of magnitude, and has similar performance to Dropbox but yet does not need a separate index cloud.","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":"122368735","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: 4

Communication-Avoiding for Dynamical Core of Atmospheric General Circulation Model 大气环流模式动力核心的通信避免

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225140

Junmin Xiao, Shigang Li, Baodong Wu, He Zhang, Kun Li, Erlin Yao, Yunquan Zhang, Guangming Tan

{"title":"Communication-Avoiding for Dynamical Core of Atmospheric General Circulation Model","authors":"Junmin Xiao, Shigang Li, Baodong Wu, He Zhang, Kun Li, Erlin Yao, Yunquan Zhang, Guangming Tan","doi":"10.1145/3225058.3225140","DOIUrl":"https://doi.org/10.1145/3225058.3225140","url":null,"abstract":"Dynamical core is one of the most time-consuming parts in the global atmospheric general circulation model, which is widely used for the numerical simulation of the dynamic evolution process of global atmosphere. Due to its complicated calculation procedures and the non-uniformity of latitude-longitude mesh, the parallelization suffers from high communication overhead. In this paper, we deduce the operator form of the calculating flow in the dynamical core. Furthermore, it is abstracted out that the stencil and collection alternate action is the basic operation in the dynamic core. Based on the operator form of the calculation flow, we propose the corresponding optimization strategy for each operator. In the end, we develop a communication-avoiding algorithm to reduce communication overhead in the dynamic core. Our experiments show that the communication-avoiding algorithm reduces the total runtime by 54% at most for a 50 km resolution model running 10 years. Especially for communication reduction, the new algorithm achieves 1.4x speedup on average for the collective communication and 3.9x speedup on average for the communication involved in the stencil computation.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"22 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":"126941709","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: 9

Combining Task-based Parallelism and Adaptive Mesh Refinement Techniques in Molecular Dynamics Simulations 结合基于任务的并行和自适应网格细化技术在分子动力学模拟中的应用

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225085

R. Prat, L. Colombet, R. Namyst

引用次数: 9

Scalable Solutions for Automated Single Pulse Identification and Classification in Radio Astronomy 射电天文学中自动单脉冲识别和分类的可扩展解决方案

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225101

Thomas R. Devine, K. Goseva-Popstojanova, Di Pang

{"title":"Scalable Solutions for Automated Single Pulse Identification and Classification in Radio Astronomy","authors":"Thomas R. Devine, K. Goseva-Popstojanova, Di Pang","doi":"10.1145/3225058.3225101","DOIUrl":"https://doi.org/10.1145/3225058.3225101","url":null,"abstract":"Data collection for scientific applications is increasing exponentially and is forecasted to soon reach peta- and exabyte scales. Applications which process and analyze scientific data must be scalable and focus on execution performance to keep pace. In the field of radio astronomy, in addition to increasingly large datasets, tasks such as the identification of transient radio signals from extrasolar sources are computationally expensive. We present a scalable approach to radio pulsar detection written in Scala that parallelizes candidate identification to take advantage of in-memory task processing using Apache Spark on a YARN distributed system. Furthermore, we introduce a novel automated multiclass supervised machine learning technique that we combine with feature selection to reduce the time required for candidate classification. Experimental testing on a Beowulf cluster with 15 data nodes shows that the parallel implementation of the identification algorithm offers a speedup of up to 5X that of a similar multithreaded implementation. Further, we show that the combination of automated multiclass classification and feature selection speeds up the execution performance of the RandomForest machine learning algorithm by an average of 54% with less than a 2% average reduction in the algorithm's ability to correctly classify pulsars. The generalizability of these results is demonstrated by using two real-world radio astronomy data sets.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"7 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":"125603174","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: 4

Massively Parallel Huffman Decoding on GPUs gpu上的大规模并行霍夫曼解码

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225076

André Weißenberger, B. Schmidt

{"title":"Massively Parallel Huffman Decoding on GPUs","authors":"André Weißenberger, B. Schmidt","doi":"10.1145/3225058.3225076","DOIUrl":"https://doi.org/10.1145/3225058.3225076","url":null,"abstract":"Data compression is a fundamental building block in a wide range of applications. Besides its intended purpose to save valuable storage on hard disks, compression can be utilized to increase the effective bandwidth to attached storage as realized by state-of-the-art file systems. In the foreseeing future, on-the-fly compression and decompression will gain utmost importance for the processing of data-intensive applications such as streamed Deep Learning tasks or Next Generation Sequencing pipelines, which establishes the need for fast parallel implementations. Huffman coding is an integral part of a number of compression methods. However, efficient parallel implementation of Huffman decompression is difficult due to inherent data dependencies (i.e. the location of a decoded symbol depends on its predecessors). In this paper, we present the first massively parallel decoder implementation that is compatible with Huffman's original method by taking advantage of the self-synchronization property of Huffman codes. Our performance evaluation on three different CUDA-enabled GPUs (TITAN V, TITAN XP, GTX 1080) demonstrates speedups of over one order-of-magnitude compared to the state-of-art CPU-based Zstandard Huffman decoder. Our implementation is available at https://github.com/weissenberger/gpuhd.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"5 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":"126234517","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: 23

Less Provisioning: A Fine-grained Resource Scaling Engine for Long-running Services with Tail Latency Guarantees 少供应:具有尾部延迟保证的长时间运行服务的细粒度资源扩展引擎

Proceedings of the 47th International Conference on Parallel Processing Pub Date : 2018-08-13 DOI: 10.1145/3225058.3225113

Binlei Cai, Rongqi Zhang, Laiping Zhao, Keqiu Li

{"title":"Less Provisioning: A Fine-grained Resource Scaling Engine for Long-running Services with Tail Latency Guarantees","authors":"Binlei Cai, Rongqi Zhang, Laiping Zhao, Keqiu Li","doi":"10.1145/3225058.3225113","DOIUrl":"https://doi.org/10.1145/3225058.3225113","url":null,"abstract":"Modern resource management frameworks guarantee low tail latency for long-running services using the resource over-provisioning method, resulting in serious waste of resource and increasing the service costs greatly. To reduce the over-provisioning cost, we present EFRA, an elastic and fine-grained resource allocator that enables much more efficient resource provisioning while guaranteeing the tail latency Service Level Objective (SLO). EFRA achieves this through the cooperation of three key components running on a containerized platform: The period detector identifies the period features of the workload through a convolution-based time series analysis. The resource reservation component estimates the just-right amount of resources based on the period analysis through a top-K based collaborative filtering approach. The online reprovisioning component dynamically adjusts the resources for further enforcing the tail latency SLO. Testbed experiments show that EFRA is able to increase the average resource utilization to 43%, and save up to 66% resources while guaranteeing the same tail latency objective.","PeriodicalId":307809,"journal":{"name":"Proceedings of the 47th International Conference on Parallel Processing","volume":"112 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":"120994074","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: 9