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High-level programming for heterogeneous and hierarchical parallel systems

INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2018年第6期32卷 804-806页

作者： Garcia-Blas, Javier Brown, Christopher Univ Carlos III Madrid Dept Comp Sci & Engn Madrid Spain Univ St Andrews Dept Comp Sci St Andrews Fife Scotland

High-Level Heterogeneous and Hierarchical Parallel Systems (HLPGPU) aims to bring together researchers and practitioners to present new results and ongoing work on those aspects of high-level programming relevant, or specific to general-purpose computing on graphics processing units (GPGPUs) and new architectures. The 2016 HLPGPU symposium was an event co-located with the HiPEAC conference in Prague, Czech Republic. HLPGPU is targeted at high-level parallel techniques, including programming models, libraries and languages, algorithmic skeletons, refactoring tools and techniques for parallel patterns, tools and systems to aid parallel programming, heterogeneous computing, timing analysis and statistical performance models.

关键词： GPGPU heterogeneous domain-specific parallel patterns performance programming models

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Concurrency-Aware Object-Oriented programming with Roles

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PROCEEDINGS OF THE ACM ON programming LANGUAGES-PACMPL 2018年第OOPSLA期2卷 1–30页

作者： Faes, Michael Gross, Thomas R. Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland

Object-oriented programming has been effective in reducing code complexity in sequential programs, but in current practice, concurrent programs still present a number of challenges. We present here a model of object-oriented programming that identifies concurrent tasks and the relationship between objects and tasks, effectively making objects concurrency-aware. This awareness is formalized in a parallel programming model where every object plays a role in every task (e.g., the READONLY role). When an object is shared with a new task, it adapts to the new sharing pattern by changing its roles, and therefore its behavior, i.e., the operations that can be performed with this object. This mechanism can be leveraged to prevent interfering accesses from concurrently executing tasks, and therefore makes parallel execution deterministic. To this end, we present a role-based programming language that includes several novel concepts (role transitions, guarding, slicing) to enable practical, object-oriented deterministic parallel programming. We show that this language can be used to safely implement programs with a range of different parallel patterns. The implementations to 8 widely used programming problems achieve substantial parallel speedups and demonstrate that this approach delivers performance roughly on par with manually synchronized implementations.

关键词： programming models concurrency parallelism determinism

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programming A D-WAVE ANNEALING-BASED QUANTUM COMPUTER: TOOLS AND TECHNIQUES

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QUANTUM INFORMATION & COMPUTATION 2019年第9-10期19卷 721-759页

作者： Pakin, Scott Reinhardt, Steven P. Los Alamos Natl Lab Comp Computat & Stat Sci Div Los Alamos NM 87545 USA Quantum Comp Inc Leesburg VA 20175 USA

Quantum annealing is a form of quantum computing that exploits quantum effects to probabilistically solve a specific, NP-hard problem: finding the ground state of a classical, Ising-model Hamiltonian. Because physical quantum annealers are already available, there exists the pressing question of how to program such systems. That is, how can one map a computational problem into the coefficients of an Ising-model Hamiltonian for solution by quantum-annealing hardware? In this article, we address that question primarily from a practical standpoint. We survey extant software tools intended for programming D-Wave annealing-based quantum processors and examine the programming model and solution technique promoted by each tool in an attempt to showcase the variety of contemporary approaches to solving computationally challenging problems on an existing annealing-based quantum computer.

关键词： D-Wave quantum computing quantum annealing programming models development tools

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Structured Streaming: A Declarative API for Real-Time Applications in Apache Spark 18

Structured Streaming: A Declarative API for Real-Time Applic...

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44th ACM SIGMOD International Conference on Management of Data

作者： Armbrust, Michael Das, Tathagata Torres, Joseph Yavuz, Burak Zhu, Shixiong Xin, Reynold Ghodsi, Ali Stoica, Ion Zaharia, Matei Databricks Inc San Francisco CA 94105 USA Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9781450317436

With the ubiquity of real-time data, organizations need streaming systems that are scalable, easy to use, and easy to integrate into business applications. Structured Streaming is a new high-level streaming API in Apache Spark based on our experience with Spark Streaming. Structured Streaming differs from other recent streaming APIs, such as Google Dataflow, in two main ways. First, it is a purely declarative API based on automatically incrementalizing a static relational query (expressed using SQL or DataFrames), in contrast to APIs that ask the user to build a DAG of physical operators. Second, Structured Streaming aims to support end-to-end real-time applications that integrate streaming with batch and interactive analysis. We found that this integration was often a key challenge in practice. Structured Streaming achieves high performance via Spark SQL's code generation engine and can outperform Apache Flink by up to 2x and Apache Kafka Streams by 90x. It also offers rich operational features such as rollbacks, code updates, and mixed streaming/batch execution. We describe the system's design and use cases from several hundred production deployments on Databricks, the largest of which process over 1 PB of data per month.

关键词： stream processing programming models apache spark

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Relaxing the Correctness Conditions on Concurrent Data Structures for Multicore CPUs. A Numerical Case Study 12th

Relaxing the Correctness Conditions on Concurrent Data Struc...

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12th International Conference on Parallel Processing and Applied Mathematics (PPAM)

作者： Laccetti, Giuliano Lapegna, Marco Mele, Valeria Montella, Raffaele Univ Napoli Federico II Dept Math & Applicat Naples Italy Univ Napoli Parthenope Dept Sci & Technol Naples Italy

ISBN: (纸本)9783319780542;9783319780535

The rise of new multicore CPUs introduced new challenges in the process of design of concurrent data structures: in addition to traditional requirements like correctness, linearizability and progress, the scalability is of paramount importance. It is a common opinion that these two demands are partially in conflict each others, so that in these computational environments it is necessary to relax the requirements on the traditional features of the data structures. In this paper we introduce a relaxed approach for the management of heap based priority queues on multicore CPUs, with the aim to realize a tradeoff between efficiency and sequential correctness. The approach is based on a sharing of information among only a small number of cores, so that to improve performance without completely losing the features of the data structure. The results obtained on a numerical algorithm show significant benefits in terms of parallel efficiency.

关键词： HPC heterogeneous systems Concurrent data structures programming models

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BabelFlow: An Embedded Domain Specific Language for Parallel Analysis and Visualization 32

BabelFlow: An Embedded Domain Specific Language for Parallel...

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32nd IEEE International Parallel and Distributed Processing Symposium (IPDPS)

作者： Petruzza, Steve Treichler, Sean Pascucci, Valerio Bremer, Peer-Timo Univ Utah Salt Lake City UT 84112 USA Stanford Univ Stanford CA 94305 USA Lawrence Livermore Natl Lab Livermore CA USA

ISBN: (纸本)9781538643686

The rapid growth in simulation data requires large-scale parallel implementations of scientific analysis and visualization algorithms, both to produce results within an acceptable timeframe and to enable in situ deployment. However, efficient and scalable implementations, especially of more complex analysis approaches, require not only advanced algorithms, but also an in-depth knowledge of the underlying runtime. Furthermore, different machine configurations and different applications may favor different runtimes, i.e., MPI vs Charm++ vs Legion, etc., and different hardware architectures. This diversity makes developing and maintaining a broadly applicable analysis software infrastructure challenging. We address some of these problems by explicitly separating the implementation of individual tasks of an algorithm from the dataflow connecting these tasks. In particular, we present an embedded domain specific language (EDSL) to describe algorithms using a new task graph abstraction. This task graph is then executed on top of one of several available runtimes (MPI, Charm++, Legion) using a thin layer of library calls. We demonstrate the flexibility and performance of this approach using three different large scale analysis and visualization use cases, i.e., topological analysis, rendering and compositing dataflow, and image registration of large microscopy scans. Despite the unavoidable overheads of a generic solution, our approach demonstrates performance portability at scale, and, in some cases, outperforms hand-optimized implementations.

关键词： Embedded DSL User productivity In-situ analysis Simulation runtime systems programming models

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Distributed memory futures for compile-time, deterministic-by-default concurrency in distributed C plus plus applications 4

Distributed memory futures for compile-time, deterministic-b...

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IEEE/ACM 4th International Workshop on Extreme Scale programming models and Middleware (ESPM2)

作者： Wilke, Jeremiah J. Hollman, David S. Lewis, Cannada Markosyan, Aram Morals, Nicolas Sandia Natl Labs Scalable Modeling & Anal Livermore CA 94550 USA

ISBN: (纸本)9781728101781

Futures are a widely-used abstraction for enabling deferred execution in imperative programs. Deferred execution enqueues tasks rather than explicitly blocking and waiting for them to execute. Many task-based programming models with some form of deferred execution rely on explicit parallelism that is the responsibility of the programmer. Deterministic-by-default (implicitly parallel) models instead use data effects to derive concurrency automatically, alleviating the burden of concurrency management. Both implicitly and explicitly parallel models are particularly challenging for imperative object-oriented programming. Fine-granularity parallelism across member functions or amongst data members may exist, but is often ignored. In this work, we define a general permissions model that leverages the C++ type system and move semantics to define an asynchronous programming model embedded in the C++ type system. Although a default distributed memory semantic is provided, the concurrent semantics are entirely configurable through C++ constexpr integers. Correct use of the defined semantic is verified at compile-time, allowing deterministic-by-default concurrency to be safely added to applications. Here we demonstrate the use of these "extended futures" for distributed memory asynchronous communication and load balancing. An MPI particle-in-cell application is modified with the wrapper class using this task model, with results presented for a Haswell system up to 64 nodes.

关键词： task-based runtimes template metaprogramming parallel computing programming models execution models

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Scalable Collectives for Distributed Asynchronous Many-Task Runtimes 32

Scalable Collectives for Distributed Asynchronous Many-Task ...

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27th International Heterogeneity in Computing Workshop in conjunction with 32nd IEEE International Parallel and Distributed Processing Symposium (IPDPS)

作者： Whitlock, Matthew Kolla, Hemanth Treichler, Sean Pebay, Philippe Bennett, Janine C. Oklahoma State Univ Stillwater OK 74078 USA Sandia Natl Labs Livermore CA 94550 USA Stanford Univ Stanford CA 94305 USA NexGen Analyt Sheridan WY USA

ISBN: (纸本)9781538655559

Global collectives (reductions/aggregations) are ubiquitous and feature in nearly every application of distributed high-performance computing (HPC). While it is advisable to devise algorithms by placing collectives off the critical path of execution, they are sometimes unavoidable for correctness, numerical convergence and analyses purposes. Scalable algorithms for distributed collectives are well studied and have become an integral part of MPI, but new and emerging distributed computing frameworks and paradigms such as Asynchronous Many-Task (AMT) models lack the same sophistication for distributed collectives. Since the central promise of AMT runtimes is that they automatically discover, and expose, task dependencies in the underlying program and can schedule work optimally to minimize idle time and hide data movement, a naively designed collectives protocol can completely offset any gains made from asynchronous execution. In this study we demonstrate that scalable distributed collectives are indispensable for performance in AMT models. We design, implement and test the performance of a scalable collective algorithm in Legion, an exemplar data-centric AMT programming model. Our results show that AMT systems contain the necessary primitives that allow for fully scalable collectives without breaking the transparent data movement abstractions. Scalabiity tests of an integrated Legion 1D stencil mini-application show the clear benefit of implementing scalable collectives and the performance degradation when a naive collectives alternative is used instead.

关键词： programming models Asynchronous Many-Task Parallel Computing Distributed Collectives Computational Statistics

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A Domain-Specific Approach To Unifying The Many Dimensions of Context-Aware Home Service Development 4

A Domain-Specific Approach To Unifying The Many Dimensions o...

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IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)

作者： Volanschi, Nic Carteron, Adrien Consel, Charles INRIA Bordeaux France Bordeaux INP Bordeaux France

ISBN: (纸本)9781538693803

Developing context-aware homes involves a range of stakeholders, addressing many dimensions such as service design and development, infrastructure deployment, and maintenance. Such a variety of dimensions often translate into heterogeneous, low-level, silo-based processing of sensor data to extract context information. This paper analyzes a range of existing data processing layers in the domain of aging in place to identify key concepts and operations specific to context-aware processing. Based on this analysis, we introduce a context-aware, domain-specific language and its software architecture, which allow to put in synergy the stakeholders of a context-aware home by providing them with a unified approach to designing and developing services. Our approach offers context aware-specific abstractions and notations, within a data-centric and data-driven paradigm. We have validated our approach by applying it to an assisted living platform for aging in place, deployed in the home of 129 users. In particular, we used our domain-specific language to re-implement 53 existing services, originating from the stakeholders of the assisted living platform. These services were deployed and successfully tested for their effectiveness in performing the specific tasks of the stakeholders, such as detection of daily activities, user risk situations, or sensor failures.

关键词： context-aware domain-specific data-centric data-driven aging in place programming models

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Profiling and Debugging Support for the Kokkos programming Model

Profiling and Debugging Support for the Kokkos Programming M...

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International Supercomputing Conference (ISC) on High Performance

作者： Hammond, Simon D. Trott, Christian R. Ibanez, Daniel Sunderland, Daniel Sandia Natl Labs Ctr Comp Res Albuquerque NM 87123 USA

ISBN: (纸本)9783030024659;9783030024642

Supercomputing hardware is undergoing a period of significant change. In order to cope with the rapid pace of hardware and, in many cases, programming model innovation, we have developed the Kokkos programming Model - a C++-based abstraction that permits performance portability across diverse architectures. Our experience has shown that the abstractions developed can significantly frustrate debugging and profiling activities because they break expected code proximity and layout assumptions. In this paper we present the Kokkos Profiling interface, a lightweight, suite of hooks to which debugging and profiling tools can attach to gain deep insights into the execution and data structure behaviors of parallel programs written to the Kokkos interface.

关键词： Profiling Performance-portable programming models

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