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检索条件"任意字段=23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2018"

共 18 条记录，以下是1-10 订阅

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Proceedings of the acm sigplan symposium on principles and practice of parallel programming, ppopp

Proceedings of the ACM SIGPLAN Symposium on Principles and P...

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23rd acm sigplan symposium on principles and practice of parallel programming, ppopp 2018

ISBN: (纸本)9781450349826

The proceedings contain 50 papers. The topics discussed include: interval-based memory reclamation;harnessing epoch-based reclamation for efficient range queries;a persistent lock-free queue for non-volatile memory;hierarchical memory management for mutable state;bridging the gap between deep learning and sparse matrix format selection;optimizing N-dimensional, winograd-based convolution for manycore CPUs;vSensor: leveraging fixed-workload snippets of programs for performance variance detection;featherlight on-the-fly false-sharing detection;communication-avoiding parallel minimum cuts and connected components;and an effective fusion and tile size model for optimizing image processing pipelines.

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POSTER: Revealing parallel Scans and Reductions in Sequential Loops through Function Reconstruction 23

POSTER: Revealing Parallel Scans and Reductions in Sequentia...

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23rd acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Jiang, Peng Agrawal, Gagan Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA

ISBN: (纸本)9781450349826

Many sequential loops are actually scans or reductions and can be parallelized across iterations despite the loop-carried dependences. In this work, we consider the parallelization of such scan/reduction loops, and propose a practical runtime approach called sampling-and-reconstruction to extract the hidden scan/reduction patterns in these loops.

关键词： Loop parallelization

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POSTER: Reducing the Burden of parallel Loop Schedulers for Many-Core Processors 23

POSTER: Reducing the Burden of Parallel Loop Schedulers for ...

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23rd acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Arif, Mahwish Vandierendonck, Hans Queens Univ Belfast Belfast Antrim North Ireland

ISBN: (纸本)9781450349826

This work proposes a low-overhead half-barrier pattern to schedule fine-grain parallel loops and considers its integration in the Intel OpenMP and Cilkplus schedulers. Experimental evaluation demonstrates that the scheduling overhead of our techniques is 43% lower than Intel OpenMP and 12.1 x lower than Cilk. We observe 22% speedup on 48 threads, with a peak of 2.8 x speedup.

关键词： Scheduling

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POSTER: A Predictable Synchronisation Algorithm 23

POSTER: A Predictable Synchronisation Algorithm

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23rd acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Reif, Stefan Schroeder-Preikschat, Wolfgang Friedrich Alexander Univ Erlangen Nurnberg Erlangen Germany

ISBN: (纸本)9781450349826

Interaction with physical objects often imposes latency requirements to multi-core embedded systems. One consequence is the need for synchronisation algorithms that provide predictable latency, in addition to high throughput. We present a synchronisation algorithm that needs at most 7 atomic memory operations per asynchronous critical section. The performance is competitive, at least, to locks.

关键词： Concurrent Data Structures parallel Algorithms Synchronization Predictability

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A Scalable Queue for Work Distribution on GPUs 18

A Scalable Queue for Work Distribution on GPUs

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23rd acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Kerbl, Bernhard Mueller, Joerg Kenzel, Michael Schmalstieg, Dieter Steinberger, Markus Graz Univ Technol Graz Austria

ISBN: (纸本)9781450349826

Harnessing the power of massively parallel devices like the graphics processing unit (GPU) is difficult for algorithms that show dynamic or inhomogeneous workloads. To achieve high performance, such advanced algorithms require scalable, concurrent queues to collect and distribute work. We present a new concurrent work queue, the Broker Queue, a highly efficient, linearizable queue for fine-granular work distribution on the GPU. We evaluate its usability and benefits in contrast to existing queuing algorithms. Our queue is up to one order of magnitude faster than non-blocking queues, and outperforms simpler queue designs that are unfit for fine-granular work distribution.

关键词： GPU queuing concurrent parallel scheduling

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PAM: parallel Augmented Maps 18

PAM: Parallel Augmented Maps

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23rd acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Sun, Yihan Ferizovic, Daniel Belloch, Guy E. Carnegie Mellon Univ Pittsburgh PA 15213 USA Karlsruhe Inst Technol Karlsruhe Germany

ISBN: (纸本)9781450349826

Ordered (key-value) maps are an important and widely-used data type for large-scale data processing frameworks. Beyond simple search, insertion and deletion, more advanced operations such as range extraction, filtering, and bulk updates form a critical part of these frameworks. We describe an interface for ordered maps that is augmented to support fast range queries and sums, and introduce a parallel and concurrent library called PAM (parallel Augmented Maps) that implements the interface. The interface includes a wide variety of functions on augmented maps ranging from basic insertion and deletion to more interesting functions such as union, intersection, filtering, extracting ranges, splitting, and range-sums. We describe algorithms for these functions that are efficient both in theory and practice. As examples of the use of the interface and the performance of PAM we apply the library to four applications: simple range sums, interval trees, 2D range trees, and ranked word index searching. The interface greatly simplifies the implementation of these data structures over direct implementations. Sequentially the code achieves performance that matches or exceeds existing libraries designed specially for a single application, and in parallel our implementation gets speedups ranging from 40 to 90 on 72 cores with 2-way hyperthreading.

关键词： Data handling

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Communication-Avoiding parallel Minimum Cuts and Connected Components 18

Communication-Avoiding Parallel Minimum Cuts and Connected C...

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23rd acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Gianinazzi, Lukas Kalvoda, Pavel De Palma, Alessandro Besta, Maciej Hoefler, Torsten Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland Google Inc Mountain View CA USA

ISBN: (纸本)9781450349826

We present novel scalable parallel algorithms for finding global minimum cuts and connected components, which are important and fundamental problems in graph processing. To take advantage of future massively parallel architectures, our algorithms are communication-avoiding: they reduce the costs of communication across the network and the cache hierarchy. The fundamental technique underlying our work is the randomized sparsification of a graph: removing a fraction of graph edges, deriving a solution for such a sparsified graph, and using the result to obtain a solution for the original input. We design and implement sparsification with O(1) synchronization steps. Our global minimum cut algorithm decreases communication costs and computation compared to the state-of-the-art, while our connected components algorithm incurs few cache misses and synchronization steps. We validate our approach by evaluating MPI implementations of the algorithms on a petascale supercomputer. We also provide an approximate variant of the minimum cut algorithm and show that it approximates the exact solutions well while using a fraction of cores in a fraction of time.

关键词： parallel Computing Minimum cuts Randomized Algorithms Graph Algorithms

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Hierarchical Memory Management for Mutable State 18

Hierarchical Memory Management for Mutable State

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23rd acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Guatto, Adrien Westrick, Sam Raghunathan, Ram Acar, Umut Fluet, Matthew Carnegie Mellon Univ Pittsburgh PA 15213 USA Rochester Inst Technol Rochester NY 14623 USA

ISBN: (纸本)9781450349826

It is well known that modern functional programming languages are naturally amenable to parallel programming. Achieving efficient parallelism using functional languages, however, remains difficult. Perhaps the most important reason for this is their lack of support for efficient in-place updates, i.e., mutation, which is important for the implementation of both parallel algorithms and the run-time system services (e.g., schedulers and synchronization primitives) used to execute them. In this paper, we propose techniques for efficient mutation in parallel functional languages. To this end, we couple the memory manager with the thread scheduler to make reading and updating data allocated by nested threads efficient. We describe the key algorithms behind our technique, implement them in the MLton Standard ML compiler, and present an empirical evaluation. Our experiments show that the approach performs well, significantly improving efficiency over existing functional language implementations.

关键词： parallel functional language implementation garbage collection hierarchical heaps mutation promotion

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Poster: Performance Challenges in Modular parallel Programs 23

Poster: Performance Challenges in Modular Parallel Programs

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23rd acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Acar, Umut A. Aksenov, Vitaly Chargueraud, Arthur Rainey, Mike Carnegie Mellon Univ Pittsburgh PA 15213 USA INRIA Rocquencourt France ITMO Univ St Petersburg Russia Univ Strasbourg CNRS ICube Strasbourg France

ISBN: (纸本)9781450349826

Over the past decade, many programming languages and systems for parallel-computing have been developed, including Cilk, Fork/Join Java, Habanero Java, parallel Haskell, parallel ML, and X10. Although these systems raise the level of abstraction at which parallel code are written, performance continues to require the programmer to perform extensive optimizations and tuning, often by taking various architectural details into account. One such key optimization is granularity control, which requires the programmer to determine when and how parallel tasks should be sequentialized. In this paper, we briefly describe some of the challenges associated with automatic granularity control when trying to achieve portable performance for parallel programs with arbitrary nesting of parallel constructs. We consider a result from the functional-programming community, whose starting point is to consider an "oracle" that can predict the work of parallel codes, and thereby control granularity. We discuss the challenges in implementing such an oracle and proving that it has the desired theoretical properties under the nested-parallel programming model.

关键词： Including parallel loops and nested parallel computations Such as Cilk's spawn and sync Suffice to express many common parallel patterns Wherein parallel computations may themselves start and synchronize with other parallel computations

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Efficient parallel determinacy race detection for two-dimensional dags 18

Efficient parallel determinacy race detection for two-dimens...

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23rd acm sigplan symposium on principles and practice of parallel programming, ppopp 2018

作者： Xu, Yifan Angelina Lee, I-Ting Agrawal, Kunal Washington University St. Louis United States

ISBN: (纸本)9781450349826

A program is said to have a determinacy race if logically parallel parts of a program access the same memory location and one of the accesses is a write. These races are generally bugs in the program since they lead to non-deterministic program behavior - different schedules of the program can lead to different results. Most prior work on detecting these races focuses on a subclass of programs with fork-join parallelism. This paper presents a race-detection algorithm, 2D-Order, for detecting races in a more general class of programs, namely programs whose dependence structure can be represented as planar dags embedded in 2D grids. Such dependence structures arise from programs that use pipelined parallelism or dynamic programming recurrences. Given a computation with T1 work and T∞ span, 2D-Order executes it while also detecting races in O(T1/P +T∞) time on P processors, which is asymptotically optimal. We also implemented PRacer, a race-detection algorithm based on 2D-Order for Cilk-P, which is a language for expressing pipeline parallelism. Empirical results demonstrate that PRacer incurs reasonable overhead and exhibits scalability similar to the baseline (executions without race detection) when running on multiple cores. © 2018 Copyright held by the owner/author(s).

关键词： Dynamic programming

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