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Scheduling the I/O of HPC applications under congestion 29

Scheduling the I/O of HPC applications under congestion

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29th IEEE international parallel and distributed processing Symposium (IPDPS)

作者： Gainaru, Ana Aupy, Guillaume Benoit, Anne Cappello, Franck Robert, Yves Snir, Marc Univ Illinois Champaign IL 61820 USA Ecole Normale Super Lyon Lyon France INRIA Le Chesnay France Argonne Natl Lab Argonne IL 60439 USA Univ Tennessee Knoxville Knoxville TN USA

ISBN: (纸本)9781479986484

A significant percentage of the computing capacity of large-scale platforms is wasted because of interferences incurred by multiple applications that access a shared parallel file system concurrently. One solution to handling I/O bursts in large-scale HPC systems is to absorb them at an intermediate storage layer consisting of burst buffers. However, our analysis of the Argonne's Mira system shows that burst buffers cannot prevent congestion at all times. Consequently, I/O performance is dramatically degraded, showing in some cases a decrease in I/O throughput of 67%. In this paper, we analyze the effects of interference on application I/O bandwidth and propose several scheduling techniques to mitigate congestion. We show through extensive experiments that our global I/O scheduler is able to reduce the effects of congestion, even on systems where burst buffers are used, and can increase the overall system throughput up to 56%. We also show that it outperforms current Mira I/O schedulers.

关键词： HPC application performance I/O congestion I/O scheduler burst buffers

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FRAME: Fair Resource Allocation in Multi-process Environments 21

FRAME: Fair Resource Allocation in Multi-process Environment...

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21st IEEE international conference on parallel and distributed Systems ICPADS

作者： Mohtasham, Amin Filipe, Ricardo Barreto, Joao Univ Lisbon Inst Super Tecn INESC ID Lisboa P-1699 Lisbon Portugal

ISBN: (纸本)9780769557854

As the technology trend moves toward manufacturing many-core systems with hundreds of processing cores, the problem of efficiently managing multiple parallel jobs on such massively parallel systems becomes increasingly important. With traditional time-sharing each process assumes it is the only running process. This assumption can easily lead to system oversubscription and thereby, losing overall performance due to frequent context switches. Space-sharing techniques allocate a certain number of hardware cores to each process and by that malleable processes can set their parallelism level to their allocated number of cores, hence avoiding oversubscription. However, finding the optimal spatial allocation is not a trivial task. In this paper we propose FRAME, a resource allocation technique to maximize a system's overall utility and fairness, running multiple malleable processes with CPU-bound workloads. First, we formalize the resource allocation problem as an NP-hard problem. Then, we use approximation techniques and convex optimization theory to find the optimal solution to the formulated problem, in pseudo-polynomial time. Our evaluation results show that our method is very fast and efficient in finding the optimal solution to the resource allocation problem. Also, the results suggests that the found solution increases the system's overall utility by 48%, in average, with regard to the best alternative allocation policy.

关键词： parallel programming oversubscription resource management space-sharing convex optimization

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Hierarchical block Jacobi on a cluster of multi-core Intel processors

Hierarchical block Jacobi on a cluster of multi-core Intel p...

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Japan-Egypt international conference on Electronics, Communications and Computers (JEC-ECC)

作者： Mostafa I. Soliman Fatma S. Ahmed Electrical Engineering Department Aswan Aswan University Aswan Egypt

Nowadays, it is widely accepted that exploiting all forms of parallelism is the only way to significantly improve performance. The three major forms of parallelism on a modern processor are ILP, DLP, and TLP, which are not mutually exclusive. To gain further performance improvements, MPI can be used on a cluster of computers. This paper exploits the capabilities of distributed multi-core Intel processors for accelerating the well-known singular value decomposition (SVD) based on Jacobi's algorithm. On a cluster of Fujitsu Siemens CELSIUS R550 with quad-core Intel Xeon E5410 processor running at 2.33 GHz, hierarchical block Jacobi is implemented and evaluated. On eight nodes, our results show a performance of 184.56 double-precision GFLOPS by exploiting multi-threading, SIMD, and memory hierarchy techniques. Moreover, on large matrix size, the speedups of the hierarchical block Jacobi algorithm over sequential one-sided Jacobi improve from 17.33 using superscalar implementation to 30.46, 62.94, and 86.55, by exploiting the SIMD, multi-threading, and multi-threading SIMD techniques, respectively.

关键词： Computers Program processors parallel processing Jacobian matrices Clustering algorithms Acceleration Partitioning algorithms

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Performance Evaluation of parallel HEVC Strategies 23

Performance Evaluation of Parallel HEVC Strategies

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23rd Euromicro international conference on parallel, distributed, and Network-Based processing (PDP)

作者： Georgakarakos, Georgios Tsiopoulos, Leonidas Lillius, Johan Haldin, Joakim Falk, Ulf Abo Akad Univ Joukahaisenkatu 3-5 FIN-20520 Turku Finland Oy LM Ericsson AB FIN-02420 Jorvas Finland

ISBN: (纸本)9781479984909

parallel video coding has emerged from the need to map video algorithms in many/multi-core architectures and achieve ever-growing performance goals in video-based applications. Several parallelization methods have been proposed around H. 264 algorithm but it was only until the new HEVC video standard that two parallelization strategies - Tiles and Wavefront parallel processing (WPP) - became part of the specification. Effective selection and usage of Tiles or WPP is an open issue. In this paper we evaluate the performance of both strategies in terms of video decoding speed-up including their correlation with additional optimization possibilities like parallel filtering and low-level SIMD operations.

关键词： H.265 HEVC Video coding parallel programming Tile WPP Many-core systems Multi-core systems

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Efficient Lock-Free Work-stealing Iterators for Data-parallel Collections 23

Efficient Lock-Free Work-stealing Iterators for Data-Paralle...

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23rd Euromicro international conference on parallel, distributed, and Network-Based processing (PDP)

作者： Prokopec, Aleksandar Petrashko, Dmitry Odersky, Martin Ecole Polytech Fed Lausanne LAMP CH-1015 Lausanne Switzerland

ISBN: (纸本)9781479984909

High-level data-structures are an important foundation for most applications. With the rise of multicores, there is a trend of supporting data-parallel collection operations in general purpose programming languages. However, these operations often incur high-level abstraction and scheduling penalties. We present a generic data-parallel collections design based on work-stealing for shared-memory architectures that overcomes abstraction penalties through callsite specialization of data-parallel operation instances. Moreover, we introduce work-stealing iterators that allow more fine-grained and efficient work-stealing. By eliminating abstraction penalties and making work-stealing data-structure-aware we achieve several dozen times better performance compared to existing JVM-based approaches.

关键词： data parallelism work-stealing collections callsite specialization domain-specific work-stealing

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DSLR: A distributed Schedule Length Reduction Algorithm for WSNs 29

DSLR: A Distributed Schedule Length Reduction Algorithm for ...

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29th IEEE international parallel and distributed processing Symposium (IPDPS)

作者： Bhatia, Ashutosh Hansdah, R. C. Indian Inst Sci Dept Comp Sci & Automat Bangalore Karnataka India

ISBN: (纸本)9781479986484

Wireless sensor networks (WSNs) benefit from the MAC protocols that reduce power consumption by avoiding frame collisions. Time Division Multiple Access (TDMA) method provides collision free channel access by employing a pre-defined schedule so that the nodes can transmit at their allotted time slots. Most of the existing distributed TDMA-scheduling techniques for WSNs either try to improve the channel utilization by generating a compact schedule which usually takes longer time, or generate a schedule quickly, that may not be very efficient in terms of the schedule length. In this paper, we present a new approach to TDMA-scheduling for WSNs, that bridges the gap between these two extreme types of TDMA-scheduling techniques, by providing the flexibility to trade-off the schedule length with the time required to generate the schedule, as per the requirements of the underlying applications and channel conditions. The idea is to generate a TDMA-schedule quickly using any of the existing algorithms, and then progressively reduce the TDMA-schedule length. In this context, we provide a distributed schedule length reduction (DSLR) algorithm which can be terminated after the execution of arbitrary number of iterations, and still be left with a valid schedule. Additionally, unlike other TDMA-scheduling algorithms which use contention-based channel access, the DSLR algorithm uses TDMA-based channel access to perform the schedule reduction. The algorithm has been simulated using the Castalia simulator to compare its performance with those of others in terms of generated schedule length and the time required to generate the TDMA-schedule. Simulation results confirm the effectiveness of the approach, and show that the proposed algorithm generates a compact schedule in much less time in comparison to existing approaches.

关键词： Wireless Sensor Networks Media Access Control TDMA scheduling

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Scaling Data Intensive Physics applications to 10k Cores on Non-Dedicated Clusters with Lobster

Scaling Data Intensive Physics Applications to 10k Cores on ...

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IEEE international conference on Cluster Computing (CLUSTER)

作者： Woodard, Anna Wolf, Matthias Mueller, Charles Valls, Nil Tovar, Ben Donnelly, Patrick Ivie, Peter Anampa, Kenyi Hurtado Brenner, Paul Thain, Douglas Lannon, Kevin Hildreth, Michael Univ Notre Dame Dept Phys Notre Dame IN 46556 USA Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (纸本)9781467365987

The high energy physics (HEP) community relies upon a global network of computing and data centers to analyze data produced by multiple experiments at the Large Hadron Collider (LHC). However, this global network does not satisfy all research needs. Ambitious researchers often wish to harness computing resources that are not integrated into the global network, including private clusters, commercial clouds, and other production grids. To enable these use cases, we have constructed Lobster, a system for deploying data intensive high throughput applications on non-dedicated clusters. This requires solving multiple problems related to non-dedicated resources, including work decomposition, software delivery, concurrency management, data access, data merging, and performance troubleshooting. With these techniques, we demonstrate Lobster running effectively on 10k cores, producing throughput at a level comparable with some of the largest dedicated clusters in the LHC infrastructure.

关键词： distributed processing high energy physics instrumentation computing HEP LHC Large Hadron Collider Lobster system computing center concurrency management data access data centers data intensive physics applications data merging high energy physics performance troubleshooting software delivery work decomposition Chirp Physics Production Runtime Servers Software applications of parallel and distributed computing Data-intensive computing Resource management and scheduling including energy-aware techniques Large Hadron Collider high energy physics instrumentation computing Data Merging data center Particle physics DNLZ gene HEP tumour staging notation Access to Information information retrieval distributed processing Runtime Chirp modulation Servers Online resources Lobster

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The SABER system for window-based hybrid stream processing with GPGPUs: demo 16

The SABER system for window-based hybrid stream processing w...

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Proceedings of the 10th ACM international conference on distributed and Event-based Systems

作者： Alexandros Koliousis Matthias Weidlich Raul Castro Fernandez Alexander L. Wolf Paolo Costa Peter Pietzuch Imperial College London Imperial College London and Humboldt-Universität zu Berlin Microsoft Research

ISBN: (纸本)9781450340212

Heterogeneous architectures that combine multi-core CPUs with many-core GPGPUs have the potential to improve the performance of data-intensive stream processing applications. Yet, a stream processing engine must execute streaming SQL queries with sufficient data-parallelism to fully utilise the available heterogeneous processors, and decide how to use each processor in the most effective way. Addressing these challenges, we demonstrate Saber, a hybrid high-performance relational stream processing engine for CPUs and GPGPUs. Saber executes window-based streaming SQL queries in a data-parallel fashion and employs an adaptive scheduling strategy to balance the load on the different types of processors. To hide data movement costs, Saber pipelines the transfer of stream data between CPU and GPGPU memory. In this paper, we review the design principles of Saber in terms of its hybrid stream processing model and its architecture for query execution. We also present a web front-end that monitors processing throughput.

关键词： GPGPUs heterogeneous hardware stream processing

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System-level State Equality Detection for the Formal Dynamic Verification of Legacy distributed applications 23

System-level State Equality Detection for the Formal Dynamic...

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23rd Euromicro international conference on parallel, distributed, and Network-Based processing (PDP)

作者： Guthmuller, Marion Quinson, Martin Corona, Gabriel Univ Lorraine LORIA UMR 7503 Vandoeuvre Les Nancy France CNRS LORIA UMR 7503 Vandoeuvre Les Nancy France Inria AlGorille Project Team Villers Les Nancy France

ISBN: (纸本)9781479984909

The ever increasing complexity of distributed systems mandates to formally verify their design and implementation. Unfortunately, the common approaches and existing tools to formally establish the correctness of these systems remain hardly applicable to the kind of legacy applications that are commonly found in the HPC community. We present how system-level memory introspection can be achieved directly at runtime without relying on the source code analysis. We use this mechanism to detect the equality of the application's state at system level. As the storage of the system state may be memory expensive, we compact the memory by sharing unchanged memory pages between snapshots. This enables the automated verification of safety and liveness properties on legacy distributed applications written in Fortran or C/C++ using the MPI standard. We demonstrate the effectiveness of our approach on several programs from the MPICH3 test suite.

关键词： Formal Dynamic Verification Legacy applications SimGrid State equality Legacy Equality Source code Memory Memory Verification Computer Programming Languages Snapshots system level distributed Systems Runtime accuracy class legacy application Distribute

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NXgraph: An efficient graph processing system on a single machine

NXgraph: An efficient graph processing system on a single ma...

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international conference on Data Engineering

作者： Yuze Chi Guohao Dai Yu Wang Guangyu Sun Guoliang Li Huazhong Yang Tsinghua National Laboratory for Information Science and Technology Tsinghua University Center for Energy Efficient Computing and Applications Peking University

ISBN: (纸本)9781509020218

Recent studies show that graph processing systems on a single machine can achieve competitive performance compared with cluster-based graph processing systems. In this paper, we present NXgraph, an efficient graph processing system on a single machine. We propose the Destination-Sorted Sub-Shard (DSSS) structure to store a graph. To ensure graph data access locality and enable fine-grained scheduling, NXgraph divides vertices and edges into intervals and sub-shards. To reduce write conflicts among different threads and achieve a high degree of parallelism, NXgraph sorts edges within each sub-shard according to their destination vertices. Then, three updating strategies, i.e., Single-Phase Update (SPU), Double-Phase Update (DPU), and Mixed-Phase Update (MPU), are proposed in this paper. NXgraph can adaptively choose the fastest strategy for different graph problems according to the graph size and the available memory resources to fully utilize the memory space and reduce the amount of data transfer. All these three strategies exploit streamlined disk access patterns. Extensive experiments on three real-world graphs and five synthetic graphs show that NXgraph outperforms GraphChi, TurboGraph, VENUS, and GridGraph in various situations. Moreover, NXgraph, running on a single commodity PC, can finish an iteration of PageRank on the Twitter [1] graph with 1.5 billion edges in 2.05 seconds; while PowerGraph, a distributed graph processing system, needs 3.6s to finish the same task on a 64-node cluster.

关键词： Data transfer Computational modeling Spread spectrum communication Venus parallel processing Twitter Memory management

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