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检索条件"任意字段=Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming"

共 364 条记录，以下是121-130 订阅

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Self-Checkpoint: An In-Memory Checkpoint Method Using Less Space and Its practice on Fault-Tolerant HPL 17

Self-Checkpoint: An In-Memory Checkpoint Method Using Less S...

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22nd ACM SIGPLAN symposium on principles and practice of parallel programming (PPoPP)

作者： Tang, Xiongchao Zhai, Jidong Yu, Bowen Chen, Wenguang Zheng, Weimin Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China

ISBN: (纸本)9781450344937

Fault tolerance is increasingly important in high performance computing due to the substantial growth of system scale and decreasing system reliability. In-memory/diskless checkpoint has gained extensive attention as a solution to avoid the IO bottleneck of traditional disk-based checkpoint methods. However, applications using previous in-memory checkpoint suffer from little available memory space. To provide high reliability, previous in-memory checkpoint methods either need to keep two copies of checkpoints to tolerate failures while updating old checkpoints or trade performance for space by flushing in-memory checkpoints into disk. In this paper, we propose a novel in-memory checkpoint method, called self-checkpoint, which can not only achieve the same reliability of previous in-memory checkpoint methods, but also increase the available memory space for applications by almost 50%. To validate our method, we apply the self-checkpoint to an important problem, fault tolerant HPL. We implement a scalable and fault tolerant HPL based on this new method, called SKT-HPL, and validate it on two large-scale systems. Experimental results with 24,576 processes show that SKT-HPL achieves over 95% of the performance of the original HPL. Compared to the state-of-the-art in-memory checkpoint method, it improves the available memory size by 47% and the performance by 5%.

关键词： Fault Tolerance In-Memory Checkpoint Fault-Tolerant HPL Memory Consumption

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Efficient Massively parallel Methods for Dynamic programming 2017

Efficient Massively Parallel Methods for Dynamic Programming

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49th Annual ACM-SIGACT symposium on theory of Computing (STOC)

作者： Im, Sungjin Moseley, Benjamin Sun, Xiaorui Univ Calif Elect Engn & Comp Sci 5200 N Lake Rd Merced CA 95344 USA Washington Univ Dept Comp Sci & Engn 1 Brookings Dr St Louis MO 63130 USA Univ Calif Berkeley Simons Inst Theory Comp Berkeley CA 94702 USA Simons Inst Theory Comp Berkeley CA USA

ISBN: (纸本)9781450345286

Modern science and engineering is driven by massively large data sets and its advance heavily relies on massively parallel computing platforms such as Spark, MapReduce, and Hadoop. theoretical models have been proposed to understand the power and limitations of such platforms. Recent study of developed theoretical models has led to the discovery of new algorithms that are fast and efficient in both theory and practice, thereby beginning to unlock their underlying power. Given recent promising results, the area has turned its focus on discovering widely applicable algorithmic techniques for solving problems efficiently. In this paper we make progress towards this goal by giving principles for simulating a large class of sequential dynamic programs in the distributed setting. In particular, we identify two key properties, monotonicity and decomposibility, which allow us to derive efficient distributed algorithms for problems possessing the properties. We showcase our framework by considering several core dynamic programming applications, Longest Increasing Subsequence, Optimal Binary Search Tree, and Weighted Interval Selection. For these problems, we derive algorithms yielding solutions that are arbitrarily close to the optimum, using O(1) rounds and (O) over tilde (n/m) memory on each machine where n is the input size and m is the number of machines available.

关键词： Massively parallel computing Dynamic programming

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JParEnt: parallel entropy decoding for JPEG decompression on heterogeneous multicore architectures 7

JParEnt: Parallel entropy decoding for JPEG decompression on...

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Euro-Par Conference / 7th International Workshop on programming Models and Applications for Multicores and Manycores (PMAM) held in conjunction with the 21st SIGPLAN symposium on principles and practice of parallel programming (PPoPP)

作者： Sodsong, Wasuwee Jung, Minyoung Park, Jinwoo Burgstaller, Bernd Yonsei Univ Dept Comp Sci Seoul South Korea

ISBN: (纸本)9781450341967

the JPEG format employs Huffman codes to compress the entropy data of an image. Huffman codewords are of variable length, which makes parallel entropy decoding a difficult problem. To determine the start position of a codeword in the bitstream, the previous codeword must be decoded first. We present JParEnt, a new approach to parallel entropy decoding for JPEG decompression on heterogeneous multicores. JParEnt conducts JPEG decompression in two steps: (1)an efficient sequential scan of the entropy data on the CPU to determine the start-positions (boundaries) of coefficient blocks in the bitstream, followed by (2)a parallel entropy decoding step on the graphics processing unit (GPU). the block boundary scan constitutes a reinterpretation of the Huffman-coded entropy data to determine codeword boundaries in the bitstream. We introduce a dynamic workload partitioning scheme to account for GPUs of low compute power relative to the CPU. this configuration has become common with the advent of SoCs with integrated graphics processors (IGPs). We leverage additional parallelism through pipelined execution across CPU and GPU. For systems providing a unified address space between CPU and GPU, we employ zero-copy to completely eliminate the data transfer overhead. Our experimental evaluation of JParEnt was conducted on six heterogeneous multicore systems: one server and two desktops with dedicated GPUs, one desktop with an IGP, and two embedded systems. For a selection of more than 1000JPEG images, JParEnt outperforms the SIMD-implementation of the libjpeg-turbo library by up to a factor of 4.3x, and the previously fastest JPEG decompression method for heterogeneous multicores by up to a factor of 2.2x. JParEnt's entropy data scan consumes 45% of the entropy decoding time of libjpeg-turbo on average. Given this new ratio for the sequential part of JPEG decompression, JParEnt achieves up to97% of the maximum attainable speedup (95% on average). On the IGP-based desktop platform,

关键词： JPEG decoding entropy decoding prefix codes heterogeneous multicores GPU programming

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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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20th ACM SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2015

ISBN: (纸本)9781450332057

the proceedings contain 44 papers. the topics discussed include: predicate RCU: an RCU for scalable concurrent updates;automatic scalable atomicity via semantic locking;a framework for practical parallel fast matrix multiplication;PLUTO+: near-complete modeling of affine transformations for parallelism and locality;distributed memory code generation for mixed irregular/regular computations;performance implications of dynamic memory allocators on transactional memory systems;low-overhead software transactional memory with progress guarantees and strong semantics∗;barrier elision for production parallel programs;scalable and efficient implementation of 3D unstructured meshes computation: a case study on matrix assembly;and diagnosing the causes and severity of one-sided message contention.

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NUMA-aware Scheduling and Memory Allocation for data-flow task-parallel Applications 16

NUMA-aware Scheduling and Memory Allocation for data-flow ta...

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21st ACM SIGPLAN symposium on principles and practice of parallel programming (PPoPP)

作者： Drebes, Andi Pop, Antoniu Heydemann, Karine Drach, Nathalie Cohen, Albert Univ Manchester Sch Comp Sci Manchester M13 9PL Lancs England UPMC Paris 06 Sorbonne Univ CNRS LIP6UMR 7606 Paris France Inria Ecole Normale Super Rocquencourt France

ISBN: (纸本)9781450340922

Dynamic task parallelism is a popular programming model on shared-memory systems. Compared to data parallel loop-based concurrency, it promises enhanced scalability, load balancing and locality. these promises, however, are undermined by non-uniform memory access (NUMA) systems. We show that it is possible to preserve the uniform hardware abstraction of contemporary task-parallel programming models, for both computing and memory resources, while achieving near-optimal data locality. Our run-time algorithms for NUMA-aware task and data placement are fully automatic, application-independent, performance-portable across NUMA machines, and adapt to dynamic changes. Placement decisions use information about inter-task data dependences and reuse. this information is readily available in the run-time systems of modern task-parallel programming frameworks, and from the operating system regarding the placement of previously allocated memory. Our algorithms take advantage of data-flow style task parallelism, where the privatization of task data enhances scalability through the elimination of false dependences and enables fine-grained dynamic control over the placement of application data. We demonstrate that the benefits of dynamically managing data placement outweigh the privatization cost, even when comparing with target-specific optimizations through static, NUMA-aware data interleaving. Our implementation and the experimental evaluation on a set of high-performance benchmarks executing on a 192-core system with 24 NUMA nodes show that the fraction of local memory accesses can be increased to more than 9 9 %, resulting in a speedup of up to 5x compared to a NUMA-aware hierarchical work-stealing baseline.

关键词： Scalability

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Multi-track programming competitions with scratch 16

Multi-track programming competitions with scratch

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47th ACM Technical symposium on Computing Science Education, SIGCSE 2016

作者： Arnold, Jason Bort, Heather Naugle, Ryan O'Hare, Casey Brylow, Dennis Department of Mathematics Statistics and Computer Science Marquette University 1313 West Wisconsin Avenue MilwaukeeWI53201-1881 United States

ISBN: (纸本)9781450338561

High school programming competitions often follow the traditional model of collegiate competitions, exemplified by the ACM International Collegiate programming Contest (ICPC). this tradition has been reinforced by the nature of Advanced Placement Computer Science (AP CS A) for which ICPC-style problems are considered an excellent practice regimen. As more and more students in high school computer science courses approach the field from broader starting points, such as Exploring Computer Science (ECS), or the new AP CS principles course an analogous structure for high school outreach events becomes of greater importance. this paper describes our work on developing a Scratch-based alternative competition for high school students, that can be run in parallel with a traditional morning of ICPC-style problems. © 2016 ACM.

关键词： Curricula

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PPoPP 2014 - proceedings of the 2014 ACM SIGPLAN symposium on principles and practice of parallel programming

PPoPP 2014 - Proceedings of the 2014 ACM SIGPLAN Symposium o...

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2014 19th ACM SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2014

ISBN: (纸本)9781450326568

the proceedings contain 43 papers. the topics discussed include: predator: predictive false sharing detection;concurrency testing using schedule bounding: an empirical study;trace driven dynamic deadlock detection and reproduction;efficient search for inputs causing high floating-point errors;portable, MPI-interoperable coarray Fortran;eliminating global interpreter locks in ruby through hardware transactional memory;leveraging hardware message passing for efficient thread synchronization;well-structured futures and cache locality;time-warp: lightweight abort minimization in transactional memory;beyond parallel programming with domain specific languages;a decomposition for in-place matrix transposition;in-place transposition of rectangular matrices on accelerators;and parallelizing dynamic programming through rank convergence.

关键词： FORTRAN (programming language)

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Tiles: A new language mechanism for heterogeneous parallelism 2015

Tiles: A new language mechanism for heterogeneous parallelis...

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20th ACM SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2015

作者： Chen, Yifeng Cui, Xiang Mei, Hong HCST Key Lab. School of EECS Peking University Beijing100871 China

ISBN: (纸本)9781450332057

this paper studies the essence of heterogeneity from the perspective of language mechanism design. the proposed mechanism, called tiles, is a program construct that bridges two relative levels of computation: an outer level of source data in larger, slower or more distributed memory and an inner level of data blocks in smaller, faster or more localized memory.

关键词： parallel programming

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An OpenACC-based unified programming model for multi-accelerator systems 2015

An OpenACC-based unified programming model for multi-acceler...

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20th ACM SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2015

作者： Kim, Jungwon Lee, Seyong Vetter, Jeffrey S. Oak Ridge National Laboratory United States Georgia Institute of Technology United States

ISBN: (纸本)9781450332057

this paper proposes a novel SPMD programming model of OpenACC. Our model integrates the different granularities of parallelism from vector-level parallelism to node-level parallelism into a single, unified model based on OpenACC. It allows programmers to write programs for multiple accelerators using a uniform programming model whether they are in shared or distributed memory systems. We implement a prototype of our model and evaluate its performance with a GPU-based supercomputer using three benchmark applications.

关键词： Supercomputers

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the lock-free k-LSM relaxed priority queue 2015

The lock-free k-LSM relaxed priority queue

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20th ACM SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2015

作者： Wimmer, Martin Gruber, Jakob Träff, Jesper Larsson Tsigas, Philippas Faculty of Informatics Parallel Computing Vienna University of Technology Vienna/Wien1040 Austria Computer Science and Engineering Chalmers University of Technology Göteborg412 96 Sweden

ISBN: (纸本)9781450332057

We present a new, concurrent, lock-free priority queue that relaxes the delete-min operation to allow deletion of any of the ρ+1 smallest keys instead of only a minimal one, where ρ is a parameter that can be configured at runtime. It is built from a logarithmic number of sorted arrays, similar to log-structured merge-trees (LSM). For keys added and removed by the same thread the behavior is identical to a non-relaxed priority queue. We compare to state-of-the-art lock-free priority queues with both relaxed and non-relaxed semantics, showing high performance and good scalability of our approach.

关键词： parallel programming

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