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LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment

LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment

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International symposium on parallel and distributed processing (IPDPS)

作者： Alberto Zeni Giulia Guidi Marquita Ellis Nan Ding Marco D. Santambrogio Steven Hofmeyr Aydın Buluç Leonid Oliker Katherine Yelick Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Milan Italy Department of Electrical Engineering and Computer Science University of California at Berkeley Berkeley CA USA Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA USA

ISBN: (数字)9781728168760

ISBN: (纸本)9781728168777

Pairwise sequence alignment is one of the most computationally intensive kernels in genomic data analysis, accounting for more than 90% of the runtime for key bioinformatics applications. This method is particularly expensive for third-generation sequences due to the high computational cost of analyzing sequences of length between 1Kb and 1Mb. Given the quadratic overhead of exact pairwise algorithms for long alignments, the community primarily relies on approximate algorithms that search only for high-quality alignments and stop early when one is not found. In this work, we present the first GPU optimization of the popular X-drop alignment algorithm, that we named LOGAN. Results show that our high-performance multi-GPU implementation achieves up to 181.6 GCUPS and speed-ups up to 6.6× and 30.7× using 1 and 6 NVIDIA Tesla V100, respectively, over the state-of-the-art software running on two IBM Power9 processors using 168 CPU threads, with equivalent accuracy. We also demonstrate a 2.3× LOGAN speed-up versus ksw2, a state-of-art vectorized algorithm for sequence alignment implemented in minimap2, a long-read mapping software. To highlight the impact of our work on a real-world application, we couple LOGAN with a many-to-many long-read alignment software called BELLA, and demonstrate that our implementation improves the overall BELLA runtime by up to 10.6×. Finally, we adapt the Roofline model for LOGAN and demonstrate that our implementation is near optimal on the NVIDIA Tesla V100s.

关键词： Graphics processing units Software algorithms Computer architecture Acceleration Heuristic algorithms parallel processing

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A parallel uncertain frequent itemset mining algorithm with spark 20

A parallel uncertain frequent itemset mining algorithm with ...

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20th International Conference on parallel and distributed Computing, Applications and Technologies, PDCAT 2019

作者： Ding, Jiaman Li, Haibin Wang, Yuanyuan Jia, Lianyin You, Jinguo Yang, Yang Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China College of Engineering and Computer Science Australian National University Canberra Australia

ISBN: (纸本)9781728126166

Frequent Itemset Mining (FIM) from large-scale databases has emerged as an important problem in the data mining and knowledge discovery research community. However, FIM suffers from three important limitations with the rapidly expanding of big data in all domains. First, it assumes that all items have the same importance. Second, it ignores the fact that data collected in a real-life environment is often inaccurate. third, it is also a data-intensive and computation-intensive process which makes the FIM algorithm very time-consuming over large datasets. To address these issues, we propose a parallel uncertain frequent itemset mining algorithm with spark (Pufim). Pufim firstly expresses item uncertainty by considering both the probability and weight, and calculates the maximum probability weight value of 1-items. Next, a distributed Pufim-tree structure is designed inspiring by FP-Tree for reducing the times of scanning the databases. Each node of Pufim-tree stores an item and its maximum probability weight value. Finally, experiments on publicly available UCI datasets demonstrate that Pufim achieves more prominent results than other related approaches across various metrics. In addition, the empirical study also shows Pufim has a good scalability. © 2019 ieee.

关键词： Data mining

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OO-VR: NUMA Friendly Object-Oriented VR Rendering Framework For Future NUMA-Based Multi-GPU Systems 19

OO-VR: NUMA Friendly Object-Oriented VR Rendering Framework ...

引用

46th International symposium on Computer Architecture (ISCA)

作者： Xie, Chenhao Xin, Fu Chen, Mingsong Song, Shuaiwen Leon Pacific Northwest Natl Lab Richland WA 99352 USA Univ Houston Houston TX 77004 USA Univ Houston ECE Dept ECMOS Lab Houston TX 77004 USA East China Normal Univ Sch Comp Sci & Software Engn Shanghai Peoples R China Univ Sydney Sydney NSW Australia

ISBN: (纸本)9781450366694

With the strong computation capability, NUMA-based multi-GPU system is a promising candidate to provide sustainable and scalable performance for Virtual Reality (VR) applications and deliver the excellent user experience. However, the entire multi-GPU system is viewed as a single GPU under the single programming model which greatly ignores the data locality among VR rendering tasks during the workload distribution, leading to tremendous remote memory accesses among GPU models (GPMs). The limited inter- GPM link bandwidth (e.g., 64GB/s for NVlink) becomes the major obstacle when executing VR applications in the multi-GPU system. By conducting comprehensive characterizations on different kinds of parallel rendering frameworks, we observe that distributing the rendering object along with its required data per GPM can reduce the inter-GPM memory accesses. However, this object-level rendering still faces two major challenges in NUMA-based multi- GPU system: (1) the large data locality between the left and right views of the same object and the data sharing among different objects and (2) the unbalanced workloads induced by the software- level distribution and composition mechanisms. To tackle these challenges, we propose object-oriented VR rendering framework (OO-VR) that conducts the software and hardware co-optimization to provide a NUMA friendly solution for VR multi-view rendering in NUMA-based multi-GPU systems. We first propose an object-oriented VR programming model to exploit the data sharing between two views of the same object and group objects into batches based on their texture sharing levels. Then, we design an object aware runtime batch distribution engine and distributed hardware composition unit to achieve the balanced workloads among GPMs and further improve the performance of VR rendering. Finally, evaluations on our VR featured simulator show that OO-VR provides 1.58x overall performance improvement and 76% inter-GPM memory traffic reduction over the s

关键词： graphics processing units multiprocessing systems object-oriented programming parallel processing rendering (computer graphics) virtual reality Variable reluctance Multiprocessing systems object oriented programming Rendering Graphics processing Unit locality data virtual reality parallel processing (COMPUTERS) Rendering (computer graphics) Nonunified memory architecture Remote Memory object orientation

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parallel AI and Systems for the Edge (PAISE)

Proceedings - 2019 IEEE 33rd International Parallel and Dist...

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proceedings - 2019 ieee 33rd International parallel and distributed processing symposium Workshops, IPDPSW 2019 2019年 874-875页

作者： Beckman, Pete Sankaran, Rajesh Mathematics and Computer Science Division Argonne National Laboratory United States

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Mutual Visibility for Robots with Lights Tolerating Light Faults 32

Mutual Visibility for Robots with Lights Tolerating Light Fa...

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32nd ieee International parallel and distributed processing symposium (IPDPS)

作者： Sharma, Gokarna Kent State Univ Dept Comp Sci Kent OH 44242 USA

ISBN: (纸本)9781538655559

We consider the distributed setting of N autonomous mobile robots that operate in Look-Compute-Move cycles and communicate with other robots using colored lights (the robots with lights model). We study the fundamental MUTUAL VISIBILITY problem of repositioning N robots on a plane so that each robot is visible to all others. We assume obstructed visibility under which a robot cannot see another robot if a third robot is positioned between them on the straight line connecting them. We are interested in light fault-tolerant algorithms;all existing algorithms for this problem are not tolerant to failures on the lights. Therefore, any algorithm for MUTUAL VISIBILITY is required to provide visibility to all N robots, independently of the behavior of the robots with faulty lights. We model light failures as crash faults in which each faulty agent is allowed to set its light to some color, and once the light is set to that color, that color will remain indefinitely thereafter for that agent. In this paper, we provide two algorithms, one tolerant against one faulty robot using 2 colors, which is optimal, and another against (up to) N - 2 faulty robots using 4 colors, in a system of N >= 3 robots.

关键词： distributed algorithms mobile agents lights visibility collisions obstruction crash faults convex hull

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Scalable Breadth-First Search on a GPU Cluster 32

Scalable Breadth-First Search on a GPU Cluster

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32nd ieee International parallel and distributed processing symposium (IPDPS)

作者： Pan, Yuechao Pearce, Roger Owens, John D. Univ Calif Davis Davis CA 95616 USA Lawrence Livermore Natl Lab Livermore CA USA

ISBN: (纸本)9781538643686

On a GPU cluster, the ratio of high computing power to communication bandwidth makes scaling breadth-first search (BFS) on a scale-free graph extremely challenging. By separating high and low out-degree vertices, we present an implementation with scalable computation and a model for scalable communication for BFS and direction-optimized BFS. Our communication model uses global reduction for high-degree vertices, and point-to-point transmission for low-degree vertices. Leveraging the characteristics of degree separation, we reduce the graph size to one third of the conventional edge list representation. With several other optimizations, we observe linear weak scaling as we increase the number of GPUs, and achieve 259.8 GTEPS on a scale-33 Graph500 RMAT graph with 124 GPUs on the latest CORAL early access system.

关键词： multi GPU distributed graph processing BFS

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distributed and automated machine learning in big data stream analytics 3

Distributed and automated machine learning in big data strea...

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3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019

作者： Alsahlee, Oraib H. Al-Zu’bi, Abdallah Alamro, Ibrahim I. Alwidian, Jaber Computer science Princess Sumaya university for technology Amman Jordan INFRASOFT Middle East /Big Data department United States

ISBN: (纸本)9781728137803

Distribution and automation of machine learning, a relatively new concepts occupying the scene of data science and its applications, in an era of massive data that it is growing by the second requiring complex processing and insight generation to feed the new industry of data-driven applications, utilizing the tools of machine learning and artificial intelligence built over big data infrastructures that support parallel and real-time computing, an approach that has fulfilled the requirements to a certain degree but yet requires much more optimization and a sense of autonomy to accommodate new developments and reduce human expertise dependency to achieve the bigger picture and fulfill the potential it has of revolutionizing the tech industry and overall scene. Here in this work we briefly investigate the components required to build such complex pipelines to fulfill autonomy and distribution requirements previously mentioned and propose some abstract concepts to integrate such components to achieve somewhat parallel machine learning pipeline that requires minimal human involvement. © 2019 ieee.

关键词： Machine learning

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15th International symposium on Applied Reconfigurable Computing, ARC 2019

15th International Symposium on Applied Reconfigurable Compu...

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15th International symposium on Applied Reconfigurable Computing, ARC 2019

ISBN: (纸本)9783030172268

The proceedings contain 28 papers. The special focus in this conference is on Applied Reconfigurable Computing. The topics include: Proof-Carrying Hardware Versus the Stealthy Malicious LUT Hardware Trojan;secure Local Configuration of Intellectual Property Without a Trusted third Party;HiFlipVX: An Open Source High-Level Synthesis FPGA Library for Image processing;Real-Time FPGA Implementation of Connected Component Labelling for a 4K Video Stream;A Scalable FPGA-Based Architecture for Depth Estimation in SLAM;Evaluating LULESH Kernels on OpenCL FPGA;The TaPaSCo Open-Source Toolflow for the Automated Composition of Task-Based parallel Reconfigurable Computing Systems;Graph-Based Code Restructuring Targeting HLS for FPGAs;UltraSynth: Integration of a CGRA into a Control Engineering Environment;exploiting Reconfigurable Vector processing for Energy-Efficient Computation in 3D-Stacked Memories;Optimizing CNN-Based Hyperspectral Image Classification on FPGAs;Automatic Toolflow for VCGRA Generation to Enable CGRA Evaluation for Arithmetic Algorithms;reM: A Reconfigurable Multipotent Cell for New distributed Reconfigurable Architectures;Update or Invalidate: Influence of Coherence Protocols on Configurable HW Accelerators;hybrid Prototyping for Manycore Design and Validation;Evaluation of FPGA Partitioning Schemes for Time and Space Sharing of Heterogeneous Tasks;third Party CAD Tools for FPGA Design—A Survey of the Current Landscape;Filter-Wise Pruning Approach to FPGA Implementation of Fully Convolutional Network for Semantic Segmentation;Exploring Data Size to Run Convolutional Neural Networks in Low Density FPGAs;Faster Convolutional Neural Networks in Low Density FPGAs Using Block Pruning;Supporting Columnar In-memory Formats on FPGA: The Hardware Design of Fletcher for Apache Arrow;A Novel Encoder for TDCs.

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Modular programming of synchronization and communication among tasks in parallel programs 32

Modular programming of synchronization and communication amo...

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32nd ieee International parallel and distributed processing symposium Workshops, IPDPSW 2018

作者： Van Veen, Bernie Jongmans, Sung-Shik Department of Computer Science Open University of the Netherlands Netherlands Department of Computing Imperial College London United Kingdom

ISBN: (纸本)9781538655559

Implementing synchronization and communication among tasks in parallel programs is a major challenge. We present a high-level DSL geared toward this challenge, by generalizing the existing protocol language Reo from supporting only a compile-time/statically set number of tasks (unsuitable for parallel programming), to supporting also a run-time/dynamically set number of tasks. Our contribution comprises new syntax, a new compilation/execution approach, and experimental results. Most surprisingly, the new approach can outperform the existing approach, even though the new approach requires more work to be done at run-time. © 2018 ieee.

关键词： Synchronization

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Complete Visitability for Autonomous Robots on Graphs 32

Complete Visitability for Autonomous Robots on Graphs

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32nd ieee International parallel and distributed processing symposium (IPDPS)

作者： Aljohani, Aisha Poudel, Pavan Sharma, Gokarna Kent State Univ Dept Comp Sci Kent OH 44242 USA

ISBN: (纸本)9781538643686

We consider the distributed setting of N autonomous mobile robots operating on graphs following Look-Compute-Move cycles and communicating with other robots using colored lights under the robots with lights model. We assume obstructed visibility under which a robot cannot see another robot if a third robot is positioned between them on the straight line connecting them. We introduce and study the fundamental problem of repositioning N robots on the nodes of a graph so that each robot has a path to all others without visiting an intermediate node that is occupied by any other robot (which we call the COMPLETE VISITABILITY problem). This problem is of interest due to its relationship to the problems of information collection, scattering, flocking, and dispersion on graphs. This problem generalizes the COMPLETE VISIBILITY problem studied in the literature, where the goal was to reposition the robots on a plane so that each robot sees all others. We have the following four results: We first show that it is impossible to solve COMPLETE VISITABILITY on arbitrary graphs, irrespective of the number of colors, time, and the robot activation setting (fully synchronous, semi-synchronous, or asynchronous). We then give an algorithm that solves COMPLETE VISITABILITY on grid graphs using 7 colors in the semi-synchronous setting. The algorithm uses 6 colors in the fully synchronous setting. The algorithm is collision-free. We then show that the total number of moves by any robot is O(h) and the runtime is O(h(2)) in our algorithm, where h denotes the number of layers of robots in the initial configuration. We also show that the number of moves bound is asymptotically tight and any COMPLETE VISITABILITY algorithm has runtime Omega(h) in grid graphs. We finally show that the algorithm and bounds for grid graphs extend to hexagonal tessellation graphs under chirality - robots agree on left and right directions.

关键词： distributed algorithms mobile agents lights graphs visibility collisions visitability obstruction

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