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Application Codesign of Near-Data processing for Similarity Search 32

Application Codesign of Near-Data Processing for Similarity ...

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27th international Heterogeneity in Computing Workshop in conjunction with 32nd IEEE international parallel and distributed processing symposium (IPDPS)

作者： Lee, Vincent T. Mazumdar, Amrita del Mundo, Carlo C. Alaghi, Armin Ceze, Luis Oskin, Mark Univ Washington Seattle WA 98195 USA

ISBN: (纸本)9781538643686

Similarity search is key to a variety of applications including content-based search for images and video, recommendation systems, data deduplication, natural language processing, computer vision, databases, computational biology, and computer graphics. At its core, similarity search manifests as k-nearest neighbors (kNN), a computationally simple primitive consisting of highly parallel distance calculations and a global top-k sort. However, kNN is poorly supported by today's architectures because of its high memory bandwidth requirements. This paper proposes an application codesign of a near-data processing accelerator for similarity search: the Similarity Search Associative Memory (SSAM). By instantiating compute units close to memory, SSAM benefits from the higher memory bandwidth and density exposed by emerging memory technologies. We evaluate the SSAM design down to layout on top of the Micron hybrid memory cube (HMC), and show that SSAM can achieve up to two orders of magnitude area-normalized throughput and energy efficiency improvement over multicore CPUs. We also show SSAM has higher throughput and is more energy efficient than competing GPUs and FPGAs.

关键词： similarity search k-nearest-neighbors near-data processing

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COMPI: Concolic Testing for MPI applications 32

COMPI: Concolic Testing for MPI Applications

引用

32nd IEEE international parallel and distributed processing symposium (IPDPS)

作者： Li, Hongbo Li, Sihuan Benavides, Zachary Chen, Zizhong Gupta, Rajiv Univ Calif Riverside Dept Comp Sci & Engn Riverside CA 92521 USA

ISBN: (纸本)9781538643686

MPI is widely used as the bedrock of HPC applications, but there are no effective systematic software testing techniques for MPI programs. In this paper we develop COMPI, the first practical concolic testing tool for MPI applications. COMPI tackles two major challenges. First, it provides an automated testing tool for MPI programs - it performs concolic execution on a single process and records branch coverage across all. Infusing MPI semantics such as MPI rank and MPI COMM WORLD into COMPI enables it to automatically direct testing with various processes' executions as well as automatically determine the total number of processes used in the testing. Second, COMPI employs three techniques to effectively control the cost of testing as too high a cost may prevent its adoption. By capping input values, COMPI is made practical as too large an input can make the testing extremely slow and sometimes even fail as memory needed could exceed the computing platform's memory limit. With two-way instrumentation, we reduce the unnecessary memory and I/O overhead of COMPI and the target program. With constraint set reduction, COMPI keeps significantly fewer constraints by removing redundant ones in the presence of loops so as to avoid redundant tests against these branches. Our evaluation of COMPI uncovered four new bugs in a complex application and achieved 69-86% branch coverage which far exceeds the 1.8-38% coverage achieved via random testing.

关键词： Testing Instruments Computer bugs Semantics Tools Standards Force"

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How well do CPU, GPU and Hybrid Graph processing Frameworks Perform? 32

How well do CPU, GPU and Hybrid Graph Processing Frameworks ...

引用

27th international Heterogeneity in Computing Workshop in conjunction with 32nd IEEE international parallel and distributed processing symposium (IPDPS)

作者： Aasawat, Tanuj Kr Reza, Tahsin Ripeanu, Matei Univ British Columbia Vancouver BC Canada

ISBN: (纸本)9781538655559

The importance of high-performance graph processing to solve big data problems targeting high-impact applications is greater than ever before. Recent graph processing frameworks target different hardware platforms (e.g., shared memory systems, accelerators such as GPUs, and distributed systems) and differ with respect to the programming model they adopt (e.g., based on linear algebra formulations of graph algorithms or enabling direct access to the graph structure). To better understand the impact of these choices, this paper, presents a comparative study of five state-of-the-art graph processing frameworks: two CPU-only frameworks - GraphMat and Galois, two GPU-based frameworks - Nvgraph and Gunrock;and Totem, a hybrid (CPU+GPU) framework. We use three popular graph algorithms (PageRank, Single Source Shortest Path, and Breadth-First Search), and massive scale graphs with up to billions of edges. Our evaluation focuses on three performance metrics: (i) execution time, (ii) scalability and (iii) energy consumption.

关键词： Graph processing CPU GPU Hybrid Systems Performance Evaluation PageRank SSSP BFS

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Teaching parallel Programming with Active Learning 32

Teaching Parallel Programming with Active Learning

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32nd IEEE international parallel and distributed processing symposium (IPDPS)

作者： Kuhail, Mohammad Amin Cook, Spencer Neustrom, Joshua W. Rao, Praveen Univ Missouri Sch Comp & Engn Kansas City MO 64110 USA

ISBN: (纸本)9781538655559

Today parallel computing is essential for the success of many real-world applications and software systems. Nonetheless, most computer science undergraduate courses teach students how to think and program sequentially. Further, software professionals have complained about the computer science curriculum's lag behind industry in their failing to cover modern programming technologies such as parallel programming. The emphasis on parallel programming has become even more important due to the increasing adoption of horizontal scaling approaches to cope with massive datasets. In order to help students coming from a serial curriculum comprehend parallel concepts, we used an innovative approach that utilized active learning, visualizations, examples, discussions, and practical exercises. Further, we conducted an experiment to examine the effect of active learning on students' understanding of parallel programming. Results indicate that the students that were actively engaged with the material performed better in terms of understanding parallel programming concepts than other students.

关键词： parallel programming teaching OpenMP data structures visualizations active learning

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A Migratory Heterogeneity-Aware Data Layout Scheme for parallel File Systems 32

A Migratory Heterogeneity-Aware Data Layout Scheme for Paral...

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32nd IEEE international parallel and distributed processing symposium (IPDPS)

作者： He, Shuibing Sun, Xian-He Wang, Yang Xu, Chengzhong Wuhan Univ Sch Comp Sci Wuhan 430072 Hubei Peoples R China IIT Dept Comp Sci Chicago IL 60616 USA Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China

ISBN: (纸本)9781538643686

parallel file systems (PFSs) are widely deployed to speed up the performance of high-performance computing (HPC) applications. In recent years, hybrid PFSs that consist of HDD-SSD servers, have attracted much attention in HPC community. However, existing data layout schemes do not well consider the characteristics of heterogeneous servers and heterogeneous access patterns, thus may experience considerable inefficiencies. In this study, we propose MHA, a migratory heterogeneity-aware data layout scheme to improve the data distribution of hybrid PFS. More specifically, to accommodate heterogeneous access patterns, MHA first migrates file data into several regions, each with similar access patterns. Then, by leveraging a data access cost model, MHA determines the appropriate stripe sizes on heterogeneous servers to get the best performance on each region. We have implemented MHA under MPI-IO library on top of OrangeFS file system. Experimental results show that MHA can significantly improve the hybrid PFS I/O system performance compared to existing data layout schemes.

关键词： parallel I/O System parallel File System Solid State Drive Data Layout

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An Entertaining Approach to parallel Programming Education 32

An Entertaining Approach to Parallel Programming Education

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32nd IEEE international parallel and distributed processing symposium (IPDPS)

作者： Buzek, Emanuel Krulis, Martin Charles Univ Prague Fac Math & Phys Parallel Architectures Applicat Algorithms Res Gr Prague Czech Republic

ISBN: (纸本)9781538655559

Despite the facts that multicore CPUs are present in virtually every personal computer or cell phone and distributed systems in the form of cloud services are steadily penetrating various domains of our lives, only a minority of programmers and computer science graduates are able to effectively design and develop parallel and distributed applications. Serial thinking is natural to all humans and it is also encouraged by many computer science curricula. Even though that leading educational institutions are attempting to rectify this trend by introducing parallel programming courses into their study programs, these courses are often dedicated for more experienced students in their fourth of fifth year since mastering modern parallel technologies like OpenMP or CUDA requires certain level of programming skills. It can be argued, that the parallel thinking should be taught much sooner, perhaps even before tertiary education. To this end, we have created an educational platform Parapple that aims to introduce parallelism and related problems like load balancing or synchronization to inexperienced programmers in an entertaining form. Our platform is web-based, so it can run in any modern browser on all operating systems without installation and the users are required to have only a very basic understanding of structural imperative programming.

关键词： parallel programming education simple visual web

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DM-HEOM: A Portable and Scalable Solver-Framework for the Hierarchical Equations of Motion 32

DM-HEOM: A Portable and Scalable Solver-Framework for the Hi...

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32nd IEEE international parallel and distributed processing symposium (IPDPS)

作者： Noack, Matthias Reinefeld, Alexander Kramer, Tobias Steinke, Thomas Zuse Inst Berlin Berlin Germany

ISBN: (纸本)9781538655559

Computing the Hierarchical Equations of Motion (HEOM) is by itself a challenging problem, and so is writing portable production code that runs efficiently on a variety of architectures while scaling from PCs to supercomputers. We combined both challenges to push the boundaries of simulating quantum systems, and to evaluate and improve methodologies for scientific software engineering. Our contributions are threefold: We present the first distributed memory implementation of the HEOM method (DM-HEOM), we describe an interdisciplinary development workflow, and we provide guidelines and experiences for designing distributed, performance-portable HPC applications with MPI3, OpenCL and other state-of-the-art programming models. We evaluated the resulting code on multi- and many-core CPUs as well as GPUs, and demonstrate scalability on a Cray XC40 supercomputer for the PS I molecular light harvesting complex.

关键词： parallel Programming Portability Portable Performance OpenCL MPI Scientific Computing HEOM

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System monitoring with lo2s: Power and runtime impact of c-state transitions 32

System monitoring with lo2s: Power and runtime impact of c-s...

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32nd IEEE international parallel and distributed processing symposium Workshops, IPDPSW 2018

作者： Ilsche, Thomas Schone, Robert Joram, Philipp Bielert, Mario Gocht, Andreas Technische Universität Dresden Dresden01062 Germany

ISBN: (纸本)9781538655559

In this paper, we present improvements to the low-overhead performance monitoring tool lo2s. We combine a detailed recording of system events with information from a high-resolution power measurement, to record the scheduling of applications and C-state transitions. These sub-millisecond transitions are difficult to observe with traditional approaches. Our methodology provides us with insights into the behavior of the system before, during, and after C-state transitions of processors cores. © 2018 IEEE.

关键词： Energy efficiency

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A Block Streaming Model for Irregular applications 32

A Block Streaming Model for Irregular Applications

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32nd IEEE international parallel and distributed processing symposium (IPDPS)

作者： Zope, Anup Luke, Edward Mississippi State Univ Ctr Adv Vehicular Syst Starkville MS 39762 USA Mississippi State Univ Dept Comp Sci & Engn Starkville MS USA

ISBN: (纸本)9781538655559

Due to worsening machine balance, a lightweight irregular application can utilize only a small fraction of the peak computational capacity on modern processors. Performance of such an application is also unpredictable due to the scattered data accesses. Even though some architectural features are commonly found in most of the modern processors (such as a cache system, hardware prefetchers etc.), their design parameters differ widely from one processor to another. Therefore, a performance improving programming technique still needs extensive tuning to gain maximum benefit on a target processor. In this scenario, achieving portable performance becomes difficult. This work proposes a block streaming machine model and hypothesizes that an algorithm based on the model has predictable execution time. To enable adaptation of this model for irregular applications, we also provide algorithmic transformations that can be used to replace the scattered accesses with streaming accesses in a cost predictable way. Further, we experimentally demonstrate usefulness of the model and the transformations for static lightweight irregular computations such as those performed by a numerical partial differential equation solver.

关键词： block streaming model performance predictability performance portability irregular applications

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Transferring Data from High-Performance Simulations to Extreme Scale Analysis applications in Real-Time 32

Transferring Data from High-Performance Simulations to Extre...

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32nd IEEE international parallel and distributed processing symposium (IPDPS)

作者： Marrinan, Thomas Rizzi, Silvio Insley, Joseph A. Toonen, Brian Allcock, William Papka, Michael E. Univ St Thomas St Paul MN 55105 USA Argonne Natl Lab Lemont IL 60439 USA Northern Illinois Univ De Kalb IL 60115 USA

ISBN: (纸本)9781538655559

Extreme scale analytics often requires distributed memory algorithms in order to process the volume of data output by high performance simulations. Traditionally, these analysis routines post-process data saved to disk after a simulation has completed. However, concurrently executing both simulation and analysis can yield great benefits reduce or eliminate disk I/O, increase output frequency to improve fidelity, and ultimately shorten time-to-discovery. One such method for concurrent simulation and analysis is in transit transferring data from the resource running the simulation to a separate resource running the analysis. In transit analysis can be beneficial since computational resources may not have certain resources needed for analysis (e.g. GPUs) and to reduce the impact of performing analysis tasks to the run time of the simulation. The work described in this paper compares three techniques for transferring data between distributed memory applications: 1) writing data to and reading data from a parallel file system, 2) copying data into and out of a network-accessed shared memory pool, and 3) streaming data in parallel from the processes in the simulation application to the processes in the analysis application. Our results show that using a shared memory pool and streaming data over high-bandwidth networks can both drastically increase I/O speeds and lead to quicker analysis.

关键词： in transit in situ high performance computing analysis

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