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检索条件"任意字段=Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

共 330 条记录，以下是71-80 订阅

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CuPBoP: A Framework to Make CUDA Portable 23

CuPBoP: A Framework to Make CUDA Portable

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proceedings of the 28th acm sigplan Annual symposium on principles and practice of parallel programming

作者： Ruobing Han Jun Chen Bhanu Garg Jeffrey Young Jaewoong Sim Hyesoon Kim Georgia Institute of Technology Seoul National University

ISBN: (纸本)9798400700156

CUDA, as one of the most popular choices for GPU programming, can be executed only on NVIDIA GPUs. To execute CUDA on non-NVIDIA devices, researchers have proposed to translate CUDA to other programming languages. However, this approach cannot achieve high coverage due to the challenges in source-to-source *** propose a framework, CuPBoP, that executes CUDA programs on non-NVIDIA devices without relying on other programming languages. CuPBoP consists of two parts. the compilation part applies transformations on CUDA host/kernel IRs. the runtime part consists of the runtime libraries for CUDA built-in functions. For the CPU backends, compared with the existing frameworks, CuPBoP achieves the highest coverage on all CPUs that we evaluate (x86, aarch64, RISC-V).We make CuPBoP publicly available to inspire more works in this area 1.

关键词： AArch64 X86 portable programming CUDA RISC-V

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ParGeo: a library for parallel computational geometry 22

ParGeo: a library for parallel computational geometry

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proceedings of the 27th acm sigplan symposium on principles and practice of parallel programming

作者： Yiqiu Wang Shangdi Yu Laxman Dhulipala Yan Gu Julian Shun MIT CSAIL UC Riverside

We present ParGeo, a multicore library for computational geometry algorithms. We describe two of the algorithms from ParGeo, convex hull and the smallest enclosing ball, and present a short evaluation of all implement...

ISBN: (纸本)9781450392044

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parallel and Distributed Bounded Model Checking of Multi-threaded Programs 20

Parallel and Distributed Bounded Model Checking of Multi-thr...

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25th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Inverso, Omar Trubiani, Catia Gran Sasso Sci Inst Laquila Italy

ISBN: (纸本)9781450368186

We introduce a structure-aware parallel technique for context-bounded analysis of concurrent programs. the key intuition consists in decomposing the set of concurrent traces into symbolic subsets that are separately explored by multiple instances of the same decision procedure running in parallel. the decision procedures work on different partitions of the search space without cooperating, whence distribution follows effortlessly. Our experiments on a selection of complex multi-threaded programs show significant analysis speedups and scalability, and greater performance gains than with general-purpose parallel solvers.

关键词： Concurrency Multithreading Sequentialization Software Verification parallel Analysis Bounded Model Checking SAT

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Automatic differentiation of parallel loops with formal methods 22

Automatic differentiation of parallel loops with formal meth...

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proceedings of the 27th acm sigplan symposium on principles and practice of parallel programming

作者： Jan Hückelheim Laurent Hascoët Argonne National Laboratory Inria Sophia Antipolis

ISBN: (纸本)9781450392044

the accompanying poster to this short paper presents a combination of reverse mode AD and formal methods to enable efficient differentiation of (or backpropagation through) shared-memory parallel code. Compared to the state of the art, our approach can more often avoid the need for atomic updates or private data copies during the parallel derivative computation, even in the presence of unstructured or data-dependent data access patterns. this is achieved by gathering information about the memory access patterns from the input program, which is assumed to be correctly parallelized. this information is then used to build a model of assertions in a theorem prover, which can be used to check the safety of shared memory accesses during the parallel derivative computation.

关键词： OpenMP

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PLUM: Static parallel Program Locality Analysis under Uniform Multiplexing 20

PLUM: Static Parallel Program Locality Analysis under Unifor...

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25th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Liu, Fangzhou Chen, Dong Smith, Wesley Ding, Chen Univ Rochester Rochester NY 14627 USA Natl Univ Def Technol Changsha Peoples R China

ISBN: (纸本)9781450368186

Data movement has a significant impact on program performance. For multithread programs, this impact is amplified, since different threads often interfere with each other by competing for shared cache space. However, recent de facto locality metrics consider either sequential execution only, or derive locality for multithread programs in an inefficient way, i.e. exhaustive simulation. this paper presents PLUM, a compiler solution for timescale locality analysis for parallel programs. Experiments demonstrate that the prediction accuracy is 93.97% on average. PLUM is the first tool that analyzes data locality for parallel programs during compile time;in addition, it provides an approach for efficiently studying the representative interleaving pattern for parallel executions.

关键词： Static analysis Locality Multithread

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parallel algorithms for masked sparse matrix-matrix products 22

Parallel algorithms for masked sparse matrix-matrix products

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proceedings of the 27th acm sigplan symposium on principles and practice of parallel programming

作者： Srđan Milaković Oguz Selvitopi Israt Nisa Zoran Budimlić Aydin Buluç Rice University Lawrence Berkeley Nat. Laboratory AWS AI

ISBN: (纸本)9781450392044

Computing the product of two sparse matrices (SpGEMM) is a fundamental operation in various combinatorial and graph algorithms as well as various bioinformatics and data analytics applications for computing inner-product similarities. For an important class of algorithms, only a subset of the output entries are needed, and the resulting operation is known as Masked SpGEMM since a subset of the output entries is considered to be "masked out". In this work, we investigate various novel algorithms and data structures for this rather challenging and important computation, and provide guidelines on how to design a fast Masked-SpGEMM for shared-memory architectures.

关键词： GraphBLAS

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parallel Determinacy Race Detection for Futures 20

Parallel Determinacy Race Detection for Futures

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25th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Xu, Yifan Singer, Kyle Lee, I-Ting Angelina Washington Univ St Louis St Louis MO 63130 USA

ISBN: (纸本)9781450368186

the use of futures can generate arbitrary dependences in the computation, making it difficult to detect races efficiently. Algorithms proposed by priorwork to detect races on programs with futures all have to execute the program sequentially. We propose F-Order, the first known parallel race detection algorithm that detects races on programs that use futures. Given a computation with work T-1 and span T-infinity, our algorithm detects races in time O((T-1 lg (k) over cap + k(2))/ P + T-infinity(k + lg r lg (k) over cap)) on P processors, where k is the number of future operations, r is the maximum number of readers per memory location, and (k) over cap is the maximum number of future operations done by a single future task, which is typically small. We have also implemented a prototype system based on the proposed algorithm and empirically demonstrates its practical efficiency and scalability.

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LB-HM: load balance-aware data placement on heterogeneous memory for task-parallel HPC applications 22

LB-HM: load balance-aware data placement on heterogeneous me...

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proceedings of the 27th acm sigplan symposium on principles and practice of parallel programming

作者： Zhen Xie Jie Liu Sam Ma Jiajia Li Dong Li University of California College of William & Mary

ISBN: (纸本)9781450392044

the emergence of heterogeneous memory (HM) provides a cost-effective and high-performance solution to memory-consuming HPC applications. However, using HM, wisely migrating data objects on it is critical for high performance. In this work, we introduce a load balance-aware page management system, named LB-HM. LB-HM introduces task semantics during memory profiling, rather than being application-agnostic. Evaluating with a set of memory-consuming HPC applications, we show that we show that LB-HM reduces existing load imbalance and leads to an average of 17.1% and 15.4% (up to 26.0% and 23.2%) performance improvement, compared with a hardware-based solution and an industry-quality software-based solution on Optane-based HM.

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Automatic synthesis of parallel unix commands and pipelines with KumQuat 22

Automatic synthesis of parallel unix commands and pipelines ...

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proceedings of the 27th acm sigplan symposium on principles and practice of parallel programming

作者： Jiasi Shen Martin Rinard Nikos Vasilakis MIT

ISBN: (纸本)9781450392044

We present KumQuat, a system for automatically generating data-parallel implementations of Unix shell commands and pipelines. the generated parallel versions split input streams, execute multiple instantiations of the original pipeline commands to process the splits in parallel, then combine the resulting parallel outputs to produce the final output stream. KumQuat automatically synthesizes the combine operators, with a domain-specific combiner language acting as a strong regularizer that promotes efficient inference of correct combiners. We present experimental results that show that these combiners enable the effective parallelization of our benchmark scripts.

关键词： automatic parallelization program synthesis

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A parallel Sparse Tensor Benchmark Suite on CPUs and GPUs 20

A Parallel Sparse Tensor Benchmark Suite on CPUs and GPUs

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25th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Li, Jiajia Lakshminarasimhan, Mahesh Wu, Xiaolong Li, Ang Olschanowsky, Catherine Barker, Kevin Pacific Northwest Natl Lab Richland WA 99352 USA Univ Utah Salt Lake City UT USA Purdue Univ W Lafayette IN 47907 USA Boise State Univ Boise ID 83725 USA

ISBN: (纸本)9781450368186

Tensor computations present significant performance challenges that impact a wide spectrum of applications. Efforts on improving the performance of tensor computations include exploring data layout, execution scheduling, and parallelism in common tensor kernels. this work presents a benchmark suite for arbitrary-order sparse tensor kernels using state-of-the-art tensor formats: coordinate (COO) and hierarchical coordinate (HiCOO). It demonstrates a set of reference tensor kernel implementations and some observations on Intel CPUs and NVIDIA GPUs. the full paper can be referred to at http://***/abs/2001.00660.

关键词： sparse tensors benchmark GPU roofline model

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