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检索条件"任意字段=21st ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2016"

共 21 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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21st acm sigplan symposium on principles and practice of parallel programming, ppopp 2016

ISBN: (纸本)9781450340922

The proceedings contain 55 papers. The topics discussed include: coarse grain parallelization of deep neural networks;high performance model based image reconstruction;exploiting accelerators for efficient high dimensional similarity search;declarative coordination of graph-based parallel programs;distributed halide;parallel type-checking with Haskell using saturating LVars and stream generators;articulation points guided redundancy elimination for betweenness centrality;multi-core on-the-fly SCC decomposition;a high-performance parallel algorithm for nonnegative matrix factorization;gunrock: a high-performance graph processing library on the GPU;keep calm and react with foresight: strategies for low-latency and energy-efficient elastic data stream processing;and work stealing for interactive services to meet target latency.

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Assessing the performance portability of modern parallel programming models using TeaLeaf

Assessing the performance portability of modern parallel pro...

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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： Martineau, Matthew McIntosh-Smith, Simon Gaudin, Wayne Univ Bristol HPC Grp Bristol Avon England UK Atom Weap Estab AWE Aldermaston England

In this work, we evaluate several emerging parallel programming models: Kokkos, RAJA, OpenACC, and OpenMP 4.0, against the mature CUDA and OpenCL APIs. Each model has been used to port Tealeaf, a miniature proxy application, or mini app, that solves the heat conduction equation and belongs to the Mantevo Project. We find that the best performance is achieved with architecture-specific implementations but that, in many cases, the performance portable models are able to solve the same problems to within a 5% to 30% performance penalty. While the models expose varying levels of complexity to the developer, they all achieve reasonable performance with this application. As such, if this small performance penalty is permissible for a problem domain, we believe that productivity and development complexity can be considered the major differentiators when choosing a modern parallel programming model to develop applications like Tealeaf.

关键词： Kokkos OpenMP 4 0 performance portability programming models RAJA

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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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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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Enabling semantics to improve detection of data races and misuses of lock-free data structures

Enabling semantics to improve detection of data races and mi...

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作者： Dolz, Manuel F. Astorga, David Del Rio Fernandez, Javier Torquati, Massimo Garcia, Jose Daniel Garcia-Carballeira, Felix Danelutto, Marco Univ Carlos III Madrid Dept Comp Sci Madrid 28911 Spain Univ Pisa Dept Comp Sci I-56127 Pisa Italy

The rapid progress of multi/many-core architectures has caused data-intensive parallel applications not yet fully optimized to deliver the best performance. In the advent of concurrent programming, frameworks offering structured patterns have alleviated developers' burden adapting such applications to multithreaded architectures. While some of these patterns are implemented using synchronization primitives, others avoid them by means of lock-free data mechanisms. However, lock-free programming is not straightforward, ensuring an appropriate use of their interfaces can be challenging, since different memory models plus instruction reordering at compiler/processor levels can interfere in the occurrence of data races. The benefits of race detectors are formidable in this sense;however, they may emit false positives if are unaware of the underlying lock-free structure semantics. To mitigate this issue, this paper extends ThreadSanitizer, a race detection tool, with the semantics of 2 lock-free data structures: the single-producer/single-consumer and the multiple-producer/multiple-consumer queues. With it, we are able to drop false positives and detect potential semantic violations. The experimental evaluation, using different queue implementations on a set of benchmarks and real applications, demonstrates that it is possible to reduce, on average, 60% the number of data race warnings and detect wrong uses of these structures.

关键词： data race detectors parallel programming semantics wait- lock-free data structures

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Guided installation of basic linear algebra routines in a cluster with manycore components

Guided installation of basic linear algebra routines in a cl...

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作者： Cuenca, J. Garcia, L. P. Gimenez, D. Herrera, F. J. Univ Murcia Dept Engn & Technol Comp Murcia Spain Tech Univ Cartagena Serv Support Technol Res Murcia Spain Univ Murcia Dept Comp & Syst Murcia Spain

Computational systems are nowadays composed of basic computational components that share multiprocessors and coprocessors of different types, typically several graphics processing units (GPUs) or many integrated cores (MICs), and those computational components are combined in heterogeneous clusters of nodes with different characteristics, including coprocessors of different types, with varying numbers of nodes at different speeds. The software previously developed and optimized for simpler system needs to be redesigned and reoptimized for these new, more complex systems. The adaptation to hybrid multicore+multiGPU and multicore+multiMIC of autotuning techniques for basic linear algebra routines is analyzed. The matrix-matrix multiplication kernel, which is optimized for different computational system components through guided experimentation, is studied. The routine is installed for each node in the cluster, and the information generated from individual installations may be used for a hierarchical installation in a cluster. The basic matrix-matrix multiplication may, in turn, be used inside higher level routines, which delegate their efficient execution to the optimization of the lower level routine. Experimental results are satisfactory in different multicore+multiGPU and multicore+multiMIC systems. So the guided search of execution configurations for satisfactory execution times proves to be a useful tool for heterogeneous systems, where the complexity of the system means a correct use of highly efficient routines and libraries is difficult.

关键词： autotuning heterogeneous computing hybrid programming parallel linear algebra manycore

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Data-centric Combinatorial Optimization of parallel Code 16

Data-centric Combinatorial Optimization of Parallel Code

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21st acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Luo, Hao Chen, Guoyang Li, Pengcheng Ding, Chen Shen, Xipeng Univ Rochester Rochester NY 14627 USA North Carolina State Univ Raleigh NC 27695 USA

ISBN: (纸本)9781450340922

Memory performance is one essential factor for tapping into the full potential of the massive parallelism of GPU. It has motivated some recent efforts in GPU cache modeling. This paper presents a new data-centric way to model the performance of a system with heterogeneous memory resources. The new model is composable, meaning it can predict the performance difference due to placing data differently by profiling the execution just once.

关键词： Locality metrics Locality modeling Footprint

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Samsara parallel: A Non-BSP parallel-in-Time Model 16

Samsara Parallel: A Non-BSP Parallel-in-Time Model

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21st acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Chen, Yifeng Huang, Kun Wang, Bei Li, Guohui Cui, Xiang Peking Univ HCST Key Lab EECS Beijing 100871 Peoples R China Chinese Acad Sci Dalian Inst Chem Phys Dalian 116023 Peoples R China

ISBN: (纸本)9781450340922

Many time-dependent problems like molecular dynamics of protein folding require a large number of time steps. The latencies and overheads of common-purpose clusters with accelerators are too big for high-frequency iteration. We introduce an algorithmic model called Samsara parallel (or SP) which, unlike BSP, relies on asynchronous communications and can repeatedly return to earlier time steps to refine the precision of computation. This also extends a line of research called parallel-in-Time in computational chemistry and physics.

关键词： BSP parallel-in-time Molecular Dynamics

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Merge-based Sparse Matrix-Vector Multiplication (SpMV) using the CSR storage Format 16

Merge-based Sparse Matrix-Vector Multiplication (SpMV) using...

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21st acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Merrill, Duane Garland, Michael NVIDIA Corp Santa Clara CA 95050 USA

ISBN: (纸本)9781450340922

We present a perfectly balanced, "merge-based" parallel method for computing sparse matrix-vector products (SpMV). Our algorithm operates directly upon the Compressed Sparse Row (CSR) sparse matrix format, a predominant in-memory representation for general-purpose sparse linear algebra computations. Our CsrMV performs an equitable multi-partitioning of the input dataset, ensuring that no single thread can be overwhelmed by assignment to (a) arbitrarily-long rows or (b) an arbitrarily-large number of zerolength rows. This parallel decomposition requires neither offline preprocessing nor specialized/ancillary data formats. We evaluate our method on both CPU and GPU microarchitecture across an enormous corpus of diverse real world matrix datasets. We show that traditional CsrMV methods are inconsistent performers subject to order-of-magnitude slowdowns, whereas the performance response of our method is substantially impervious to row-length heterogeneity.

关键词： SpMV segmented reduction sparse matrix sparse graph parallel decomposition merge merge-path GPU

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parallel Type-checking with Haskell using Saturating LVars and stream Generators 16

Parallel Type-checking with Haskell using Saturating LVars a...

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21st acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： Newton, Ryan R. Agacan, Omer S. Fogg, Peter Tobin-Hochstadt, Sam Indiana Univ Bloomington IN 47405 USA edX Cambridge MA USA

ISBN: (纸本)9781450340922

Given the sophistication of recent type systems, unification-based type-checking and inference can be a time-consuming phase of compilation-especially when union types are combined with subtyping. It is natural to consider improving performance through parallelism, but these algorithms are challenging to parallelize due to complicated control structure and difficulties representing data in a way that is both efficient and supports concurrency. We provide techniques that address these problems based on the LVish approach to deterministic-by-default parallel programming. We extend LVish with Saturating LVars, the first LVars implemented to release memory during the object's lifetime. Our design allows us to achieve a parallel speedup on worst-case (exponential) inputs of Hindley-Milner inference, and on the Typed Racket type-checking algorithm, which yields up an 8.46x parallel speedup on 14 cores for type-checking examples drawn from the Racket repository.

关键词： parallel programming

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Adding Approximate Counters 16

Adding Approximate Counters

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21st acm sigplan symposium on principles and practice of parallel programming (ppopp)

作者： steele, Guy L., Jr. Tristan, Jean-Baptiste Oracle Labs Burlington MA 01803 USA

ISBN: (纸本)9781450340922

We describe a general framework for adding the values of two approximate counters to produce a new approximate counter value whose expected estimated value is equal to the sum of the expected estimated values of the given approximate counters. (To the best of our knowledge, this is the first published description of any algorithm for adding two approximate counters.) We then work out implementation details for five different kinds of approximate counter and provide optimized pseudocode. For three of them, we present proofs that the variance of a counter value produced by adding two counter values in this way is bounded, and in fact is no worse, or not much worse, than the variance of the value of a single counter to which the same total number of increment operations have been applied. Addition of approximate counters is useful in massively parallel divide-and-conquer algorithms that use a distributed representation for large arrays of counters. We describe two machine-learning algorithms for topic modeling that use millions of integer counters, and confirm that replacing the integer counters with approximate counters is effective, speeding up a GPU-based implementation by over 65% and a CPU-based by nearly 50%, as well as reducing memory requirements, without degrading their statistical effectiveness.

关键词： approximate counters distributed computing divide and conquer multithreading parallel computing statistical counters

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