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FlashWalker: An In-Storage Accelerator for Graph Random Walks

FlashWalker: An In-Storage Accelerator for Graph Random Walk...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Fuping Niu Jianhui Yue Jiangqiu Shen Xiaofei Liao Haikun Liu Hai Jin National Engineering Research Center for Big Data Technology and System/Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Department of Computer Science Michigan Technological University Houghton Michigan USA

Graph random walk is widely used in the graph processing as it is a fundamental component in graph analysis, ranging from vertices ranking to the graph embedding. Different from traditional graph processing workload, random walk features massive processing parallelisms and poor graph data reuse, being limited by low I/O efficiency. Prior designs for random walk mitigate slow I/O operations. However, the state-of-the-art random walk processing systems are bounded by slow disk I/O bandwidth, which is confirmed by our experiments with real-world graphs. To address this issue, we propose FlashWalker, an in-storage accelerator for random walk that moves walk updating close to graph data stored in flash memory, by exploiting significant parallelisms inside SSD. Featuring a heterogeneous and parallel processing system, FlashWalker includes a board-level accelerator, channel-level accelerators, and chip-level accelerators. To address challenges posed by the tight resource constraints for processing large-scale graphs, we propose novel designs: storing a few popular subgraphs in accelerators, the pre-walking for dense walks, two optimizations to search the subgraph mapping table, and a subgraph scheduling algorithm. We implement FlashWalker in RTL, showing small circuit area overhead. Our evaluation shows FlashWalker reduces the execution time of random walk algorithms by up to 660.50×, compared with GraphWalker, which is the state-of-the-art system for random walk algorithms.

关键词： distributed processing Scheduling algorithms Bandwidth parallel processing Distance measurement Flash memories Optimization

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Quantifying Composable Data Center Utilization

Quantifying Composable Data Center Utilization

引用

IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Marc Taubenblatt Asser Tantawi IBM Thomas J. Watson Research Center Yorktown Heights NY USA

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

Composable data centers have been a strong topic of research interest, with potential benefits including higher resource utilization, faster and independent refresh cycles, flex-ible/optimum resource allocation and better capital and oper-ational costs. In this paper we use a discrete event simulation model to provide a quantitative assessment of the utilization ben-efits for a composable system versus conventional. We consider a simple multi-server loss queue situation as well as two more realistic scenarios: a mixed memory size demand and a mixed ratio CPU-GPU demand. In all these scenarios, composable systems can provide many tens of percent utilization advantage over more conventional hardware deployments. We also explore the impact of size of the composable resource pool on utilization.

关键词： Data centers distributed processing Analytical models Conferences Memory management Hardware Discrete event simulation

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MetaWBC: POSIX-Compliant Metadata Write-Back Caching for distributed File systems

MetaWBC: POSIX-Compliant Metadata Write-Back Caching for Dis...

引用

Supercomputing Conference

作者： Yingjin Qian Wen Cheng Lingfang Zeng Marc-André Vef Oleg Drokin Andreas Dilger Shuichi Ihara Wusheng Zhang Yang Wang André Brinkmann Data Direct Networks (DDN) China Huazhong University of Science and Technology (HUST) China Zhejiang Lab China Johannes Gutenberg University Mainz Germany Whamcloud Inc USA Data Direct Networks (DDN) Japan Tsinghua University China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China

ISBN: (纸本)9781665454452

In parallel and distributed file systems, caching can improve data performance and metadata operations. Currently, most distributed file systems adopt a write-back data cache for performance and a write-through metadata cache for simplifying consistency. However, with modern file systems scales and workloads, write-through metadata caching can impact overall file system performance, e.g., through lock contention and heavy RPC loads required for namespace synchronization and transaction serialization. This paper proposes a novel metadata write-back caching (MetaWBC) mechanism to improve the performance of metadata operations in distributed environments. To achieve extreme metadata performance, we developed a fast, lightweight, and POSIXcompatible memory file system as a metadata cache. Further, we designed a file caching state machine and included other performance optimizations. We coupled MetaWbc with Lustre and evaluated that MetaWbc can outperform the native parallel file system by up to 8x for metadata-intensive benchmarks, and up to 7x for realistic workloads in throughput.

关键词： File systems High performance computing distributed databases Metadata Benchmark testing Throughput Synchronization

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Excavating the Potential of Graph Workload on RDMA-based Far Memory Architecture

Excavating the Potential of Graph Workload on RDMA-based Far...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Jing Wang Chao Li Taolei Wang Lu Zhang Pengyu Wang Junyi Mei Minyi Guo Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Shanghai Qi Zhi Institute Shanghai China

Disaggregated architecture brings new opportunities to memory -consuming applications like graph processing. It allows one to outspread memory access pressure from local to far memory, providing an attractive alternative to disk-based processing. Although existing works on general-purpose far mem-ory platforms show great potentials for application expansion, it is unclear how graph processing applications could benefit from disaggregated architecture, and how different optimization methods influence the overall performance. In this paper, we take the first step to analyze the impact of graph processing workload on disaggregated architecture by extending the GridGraph framework on top of the RDMA-based far memory system. We design Fargraph, a far memory coordi-nation strategy for enhancing graph processing workload. Specif-ically, Fargraph reduces the overall data movement through a well-crafted, graph-aware data segment offloading mechanism. In addition, we use optimal data segment splitting and asynchronous data buffering to achieve graph iteration-friendly far memory access. We show that Fargraph achieves near-oracle performance for typical in-local-memory graph processing systems. Fargraph shows up to 8.3 x speedup compared to Fastswap, the state-of-the-art, general-purpose far memory platform.

关键词： distributed processing Memory architecture Optimization methods

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Applying distributed application global states monitoring to speculative query processing in RDBMS 19

Applying distributed application global states monitoring to...

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19th international symposium on parallel and distributed Computing (ISPDC)

作者： Sasak-Okon, Anna Tudruj, Marek Univ Maria Curie Sklodowska Lublin Poland Polish Acad Sci Inst Comp Sci Polish Japanese Acad Informat Technol Warsaw Poland

ISBN: (纸本)9781728189468

The paper is concerned with the methodology for speculative query execution support in distributed Relational Database Management systems (RDBMS). The proposed approach is based on the analysis of the multigraph representations of the stream of input queries arriving to a RDBMS. As a result, the optimized set of speculative queries is found to support execution of current queries. The speculative query results are used to speed-up execution of the query input stream. The paper presents how the proposed speculative query execution approach can be implemented inside a novel distributed program design framework PEGASUS DA in which program execution decisions are taken based on the system-supported monitoring of the distributed application global states. The paper shows the architecture of the speculative support provided by such framework for the distributed RDBMS and the assumed speculation approach. The implementation issues of the multi-threaded distributed support based on the RDBMS SQLite engines are discussed. distributed data synchronization and speculative query execution strategy as well as speculation results distribution are discussed. The proposed approach to distributed implementation of the speculative support to RDBMSs using the PEGASUS DA framework is illustrated on the example of the modifying query handling in a RDBMS facing the presented speculative query support for query execution.

关键词： speculative query execution global states monitoring distributed database

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Performance Evaluation of Data Transfer API for Rank Level Approximate Computing on HPC systems

Performance Evaluation of Data Transfer API for Rank Level A...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Yoshiyuki Morie Yasutaka Wada Ryohei Kobayashi Ryuichi Sakamoto Faculty of Fukuoka Medical Technology Teikyo University Fukuoka JAPAN School of Information Science Meisei University Tokyo JAPAN Center for Computational Sciences University of Tsukuba Ibaraki JAPAN Global Scientific Information and Computing Center Tokyo Institute of Technology Tokyo JAPAN

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

Approximate computing (AC) has attracted much attention to optimize tradeoffs among performance, power con-sumption, and computation results accuracy by adjusting data precision in applications. Even on HPC systems, AC is demanded to maximize performance under the limited power budget and hardware resources. To apply AC for HPC applications, we need to consider the character of each MPI rank in an application and optimize it with its appropriate data precision. However, we also need to perform data transfer while converting the precision of the target data. This paper proposes data pack/unpack APIs, which are applicable for standard MPI programs for HPC systems, for converting the data precision of the target data, and shows its performance evaluation. We can express data transfer among ranks with different data precision with the proposed APIs. The performance evaluation reveals the break-even point to apply AC for HPC applications from the perspective of data transfer volume.

关键词： Performance evaluation distributed processing Conferences Approximate computing Data transfer Hardware Standards

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parallel State Machine Replication from Generalized Consensus 39

Parallel State Machine Replication from Generalized Consensu...

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39th international symposium on Reliable distributed systems (SRDS)

作者： Ceolin Junior, Tarcisio Dotti, Fernando Pedone, Fernando Pontificia Univ Catolica Rio Grande do Sul Escola Politecn Porto Alegre RS Brazil Univ Fed Santa Maria Santa Maria RS Brazil Univ Svizzera Italiana Lugano Switzerland

ISBN: (纸本)9781728176260

State machine replication (SMR) is a established approach to building fault-tolerant services. In search for high SMR throughput, approaches that exploit semantic information in the ordering and execution of commands have emerged. Generalized consensus and parallel state machine replication are two representative examples, respectively. Although both approaches have been proved effective in isolation, no study in the literature has considered their integration. In this paper, we investigate the integration of generalized consensus and parallel SMR. We derive algorithms to parallelize the execution of commands based on the ordering of commands provided by consensus. As a prototype, we extended Egalitarian Paxos and conducted many experiments varying conflict rates, command computational costs, and number of cores at replicas. Compared to Egalitarian Paxos, the integrated approach (a) results in important throughput gains, as command independency and computational cost increase, and (b) converges to the same performance with high conflict rates or reduced number of cores.

关键词： State Machine Replication Generalized Consensus distributed Algorithms

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Workshop on Resource Arbitration for Dynamic Runtimes (RADR)

Workshop on Resource Arbitration for Dynamic Runtimes (RADR)

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Pete Beckman Emmanuel Jeannot Swann Perarnau Argonne National Laboratory Northwestern University Argonne IL USA TADaaM Team Inria Talence France Argonne National Laboratory Argonne IL USA

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

The question of efficient dynamic allocation of compute-node resources, such as cores, by independent libraries or runtime systems can be a nightmare. Scientists writing application components have no way to efficiently specify and compose resource-hungry components. As application software stacks become deeper and the interaction of multiple runtime layers compete for resources from the operating system, it has become clear that intelligent cooperation is needed. Resources such as compute cores, in-package memory, and even electrical power must be orchestrated dynamically across application components, with the ability to query each other and respond appropriately. A more integrated solution would reduce intra-application resource competition and improve performance. Furthermore, application runtime systems could request and allocate specific hardware assets and adjust runtime tuning parameters up and down the software stack. The goal of this workshop is to gather and share the latest scholarly research from the community working on these issues, at all levels of the HPC software stack. This includes thread allocation, resource arbitration and management, containers, and so on, from runtime-system designers to compilers. We will also use panel sessions and keynote talks to discuss these issues, share visions, and present solutions.

关键词： distributed processing Runtime Conferences Operating systems Instruction sets Dynamic scheduling Libraries

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RVTN: Recommender system for vehicle routing in transportation network

RVTN: Recommender system for vehicle routing in transportati...

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international Conference on parallel distributed and Grid Computing (PDGC)

作者： Righa Tandon Ajay Verma P. K. Gupta Department of Computer Science and Engineering Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science and Engineering Jaypee University of Information Technology Solan India

ISBN: (纸本)9781665454025

The recommender system predicts the future paths based on the vehicle interactions in a vehicular environment. As the data is ubiquitous, we have a number of options available to make a selection for finding the path in the vehicular network. This is the scenario where the recommender system plays its role by narrowing the available options and make the selection process easy and effective. In this paper, we have proposed a sequential recommender system that considers the vehicle’s interactions along with the paths in sequential order and map the sequences dynamically in which the weight-age is given to current preferences and recent choices as explored by the vehicle of the network. A detailed comparison of the proposed sequential recommender system with the commonly used matrix factorization model has also provided. The proposed recommender system is based on sequential dependencies and responds equally well to the vehicle routing problem. The obtained results using vehicle routing dataset reveals that the proposed recommender system is much faster with higher Mean reciprocal rank (MRR) value.

关键词： Delay effects Vehicle routing Transportation distributed databases Grid computing Data models Recommender systems

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Base Station-Assisted Cooperative Network Coding for Cellular systems with Link Constraints

Base Station-Assisted Cooperative Network Coding for Cellula...

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IEEE international symposium on Information Theory

作者： Suayb S. Arslan Massoud Pourmandi Elif Haytaoglu MEF University Maslak Istanbul Turkey Bo&#x011F azi&#x00E7 i University Bebek Istanbul Turkey Pamukkale University Denizli Turkey

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

We consider a novel distributed data storage/caching scenario in a cellular network, where multiple nodes may fail/depart simultaneously To meet reliability, we allow cooperative regeneration of lost nodes with the help of base stations allocated in a set of hierarchical layers 1 . Due to this layered structure, a symbol download from each base station has a different cost, while the link capacities between the nodes of the cellular system and the base stations are also constrained. Under such a setting, we formulate the fundamental trade-off with closed form expressions between repair bandwidth cost and the storage space per node. Particularly, the minimum storage as well as bandwidth cost points are formulated. Finally, we provide an explicit optimal code construction for the minimum storage regeneration point for a special set of system parameters.

关键词： Base stations Costs Codes Symbols distributed databases Bandwidth Cooperative systems

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