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检索条件"任意字段=17th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

共 368 条记录，以下是181-190 订阅

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Establishing a Miniapp as a Programmability Proxy 12

Establishing a Miniapp as a Programmability Proxy

引用

17th acm sigplan symposium on principles and practice of parallel programming

作者： Stone, Andrew I. Dennis, John M. Strout, Michelle Mills Colorado State Univ Ft Collins CO 80523 USA Natl Ctr Atmospher Res Boulder CO USA

ISBN: (纸本)9781450311601

Miniapps serve as test beds for prototyping and evaluating new algorithms, data structures, and programming models before incorporating such changes into larger applications. For the miniapp to accurately predict how a prototyped change would affect a larger application it is necessary that the miniapp be shown to serve as a proxy for that larger application. Although many benchmarks claim to proxy the performance for a set of large applications, little work has explored what criteria must be met for a benchmark to serve as a proxy for examining programmability. In this poster we describe criteria that can be used to establish that a miniapp serves as a performance and programmability proxy.

关键词： Languages Measurement Performance Programmability Proxy miniapp benchmark POP conjugate gradient parallel programming

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OpenCL as a Unified programming Model for Heterogeneous CPU/GPU Clusters 12

OpenCL as a Unified Programming Model for Heterogeneous CPU/...

引用

17th acm sigplan symposium on principles and practice of parallel programming

作者： Kim, Jungwon Seo, Sangmin Lee, Jun Nah, Jeongho Jo, Gangwon Lee, Jaejin Seoul Natl Univ Sch Comp Sci & Engn Ctr Manycore Programming Seoul 151744 South Korea

ISBN: (纸本)9781450311601

In this paper, we propose an OpenCL framework for heterogeneous CPU/GPU clusters, and show that the framework achieves both high performance and ease of programming. the framework provides an illusion of a single system for the user. It allows the application to utilize multiple heterogeneous compute devices, such as multicore CPUs and GPUs, in a remote node as if they were in a local node. No communication API, such as the MPI library, is required in the application source. We implement the OpenCL framework and evaluate its performance on a heterogeneous CPU/GPU cluster that consists of one host node and nine compute nodes using eleven OpenCL benchmark applications.

关键词： Algorithm Design Experimentation Languages Measurement Performance OpenCL Clusters Heterogeneous computing programming models

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An Overview of Medusa: Simplified Graph Processing on GPUs 12

An Overview of Medusa: Simplified Graph Processing on GPUs

引用

17th acm sigplan symposium on principles and practice of parallel programming

作者： Zhong, Jianlong He, Bingsheng Nanyang Technol Univ Singapore 639798 Singapore

ISBN: (纸本)9781450311601

Graphs are the de facto data structures for many applications, and efficient graph processing is a must for the application performance. GPUs have an order of magnitude higher computational power and memory bandwidth compared to CPUs and have been adopted to accelerate several common graph algorithms. However, it is difficult to write correct and efficient GPU programs and even more difficult for graph processing due to the irregularities of graph structures. To address those difficulties, we propose a programming framework named Medusa to simplify graph processing on GPUs. Medusa offers a small set of APIs, based on which developers can define their application logics by writing sequential code without awareness of GPU architectures. the Medusa runtime system automatically executes the developer defined APIs in parallel on the GPU, with a series of graph-centric optimizations. this poster gives an overview of Medusa, and presents some preliminary results.

关键词： Algorithms Performance GPGPU GPU programming Graph Processing Runtime Framework

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Using GPU's to Accelerate Stencil-based Computation Kernels for the Development of Large Scale Scientific Applications on Heterogeneous Systems 12

Using GPU's to Accelerate Stencil-based Computation Kernels ...

引用

17th acm sigplan symposium on principles and practice of parallel programming

作者： Tao, Jian Blazewicz, Marek Brandt, Steven R. Louisiana State Univ Ctr Computat & Technol Baton Rouge LA 70803 USA Poznan Supercomp & Networking Ctr Applicat Dept Poznan Poland

ISBN: (纸本)9781450311601

We present CaCUDA - a GPGPU kernel abstraction and a parallel programming framework for developing highly efficient large scale scientific applications using stencil computations on hybrid CPU/GPU architectures. CaCUDA is built upon the Cactus computational toolkit, an open source problem solving environment designed for scientists and engineers. Due to the flexibility and extensibility of the Cactus toolkit, the addition of a GPGPU programming framework required no changes to the Cactus infrastructure, guaranteeing that existing features and modules will continue to work without modification. CaCUDA was tested and benchmarked using a 3D CFD code based on a finite difference discretization of Navier-Stokes equations.

关键词： Algorithms Design Languages GPGPU programming Computational Framework HPC Stencil Computation

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Scalable parallel debugging with statistical assertions 12

Scalable parallel debugging with statistical assertions

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17th acm sigplan symposium on principles and practice of parallel programming, PPoPP'12

作者： Dinh, Minh Ngoc Abramson, David Jin, Chao Gontarek, Andrew Moench, Bob DeRose, Luiz Monash University Clayton 3800 VIC Australia Cray Inc. Saint Paul MN 55101-2987 United States

ISBN: (纸本)9781450311601

Traditional debuggers are of limited value for modern scientific codes that manipulate large complex data structures. this paper discusses a novel debug-time assertion, called a "Statistical Assertion", that allows a user to reason about large data structures, and the primitives are parallelised to provide an efficient solution. We present the design and implementation of statistical assertions, and illustrate the debugging technique with a molecular dynamics simulation. We evaluate the performance of the tool on a 12,000 cores Cray XE6.

关键词： Data structures

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Scalable GPU Graph Traversal 12

Scalable GPU Graph Traversal

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17th acm sigplan symposium on principles and practice of parallel programming

作者： Merrill, Duane Garland, Michael Grimshaw, Andrew Univ Virginia Charlottesville VA 22903 USA NVIDIA Corp Santa Clara CA USA

ISBN: (纸本)9781450311601

Breadth-first search (BFS) is a core primitive for graph traversal and a basis for many higher-level graph analysis algorithms. It is also representative of a class of parallel computations whose memory accesses and work distribution are both irregular and data-dependent. Recent work has demonstrated the plausibility of GPU sparse graph traversal, but has tended to focus on asymptotically inefficient algorithms that perform poorly on graphs with non-trivial diameter. We present a BFS parallelization focused on fine-grained task management constructed from efficient prefix sum that achieves an asymptotically optimal O(|V|+|E|) work complexity. Our implementation delivers excellent performance on diverse graphs, achieving traversal rates in excess of 3.3 billion and 8.3 billion traversed edges per second using single and quad-GPU configurations, respectively. this level of performance is several times faster than state-of-the-art implementations both CPU and GPU platforms.

关键词： Algorithms performance Breadth-first search GPU graph algorithms parallel algorithms prefix sum graph traversal sparse graph

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Extending a C-like Language for Portable SIMD programming 12

Extending a C-like Language for Portable SIMD Programming

引用

17th acm sigplan symposium on principles and practice of parallel programming

作者： Leissa, Roland Hack, Sebastian Wald, Ingo Univ Saarland Compiler Design Lab Saarbrucken Germany Intel Corp Visual Applicat Res Santa Clara CA 95051 USA

ISBN: (纸本)9781450311601

SIMD instructions are common in CPUs for years now. Using these instructions effectively requires not only vectorization of code, but also modifications to the data layout. However, automatic vectorization techniques are often not powerful enough and suffer from restricted scope of applicability;hence, programmers often vectorize their programs manually by using intrinsics: compiler-known functions that directly expand to machine instructions. they significantly decrease programmer productivity by enforcing a very error-prone and hard-to-read assembly-like programming style. Furthermore, intrinsics are not portable because they are tied to a specific instruction set. In this paper, we show how a C-like language can be extended to allow for portable and efficient SIMD programming. Our extension puts the programmer in total control over where and how control-flow vectorization is triggered. We present a type system and a formal semantics of our extension and prove the soundness of the type system. Using our prototype implementation IVL that targets Intel's MIC architecture and SSE instruction set, we show that the generated code is roughly on par with handwritten intrinsic code.

关键词： Languages Performance theory language theory parallel programming polymorphism semantics SIMD SIMT type system vectorization

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Scalable parallel Debugging with Statistical Assertions

Scalable Parallel Debugging with Statistical Assertions

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17th acm sigplan symposium on principles and practice of parallel programming

作者： Minh Ngoc Dinh Abramson, David Jin, Chao Gontarek, Andrew Moench, Bob DeRose, Luiz Monash Univ Clayton Vic 3800 Australia Cray Inc St Paul MN 55101 USA

关键词： Performance Verification parallel debugging statistic assertion

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Communication-Centric Optimizations by Dynamically Detecting Collective Operations 12

Communication-Centric Optimizations by Dynamically Detecting...

引用

17th acm sigplan symposium on principles and practice of parallel programming

作者： Hoefler, Torsten Schneider, Timo Univ Illinois Dept Comp Sci Urbana IL USA Tech Univ Chemnitz Dept Comp Sci Chemnitz Germany

ISBN: (纸本)9781450311601

the steady increase of parallelism in high-performance computing platforms implies that communication will be most important in large-scale applications. In this work, we tackle the problem of transparent optimization of large-scale communication patterns using online compilation techniques. We utilize the Group Operation Assembly Language (GOAL), an abstract parallel dataflow definition language, to specify our transformations in a device-independent manner. We develop fast schemes that analyze dataflow and synchronization semantics in GOAL and detect if parts of the (or the whole) communication pattern express a known collective communication operation. the detection of collective operations allows us to replace the detected patterns with highly optimized algorithms or low-level hardware calls and thus improve performance significantly. Benchmark results suggest that our technique can lead to a performance improvement of orders of magnitude compared with various optimized algorithms written in Co-Array Fortran. Detecting collective operations also improves the programmability of parallel languages in that the user does not have to understand the detailed semantics of high-level communication operations in order to generate efficient and scalable code.

关键词： Performance Languages Collective Communication parallel Compiler Optimization parallel Dataflow

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PARRAY: A Unifying Array Representation for Heterogeneous parallelism 12

PARRAY: A Unifying Array Representation for Heterogeneous Pa...

引用

17th acm sigplan symposium on principles and practice of parallel programming

作者： Chen, Yifeng Cui, Xiang Mei, Hong Peking Univ Sch EECS HCST Key Lab Beijing 100871 Peoples R China

ISBN: (纸本)9781450311601

this paper introduces a programming interface called PARRAY (or parallelizing ARRAYs) that supports system-level succinct programming for heterogeneous parallel systems like GPU clusters. the current practice of software development requires combining several low-level libraries like Pthread, OpenMP, CUDA and MPI. Achieving productivity and portability is hard with different numbers and models of GPUs. PARRAY extends mainstream C programming with novel array types of the following features:1)the dimensions of an array type are nested in a tree structure, conceptually reflecting the memory hierarchy;2) the definition of an array type may contain references to other array types, allowing sophisticated array types to be created for parallelization;3) threads also form arrays that allow programming in a Single-Program Multiple-Code block (SPMC) style to unify various sophisticated communication patterns. this leads to shorter, more portable and maintainable parallel codes, while the programmer still has control over performance-related features necessary for deep manual optimization. Although the source-to-source code generator only faithfully generates low-level library calls according to the type information,higher-level programming and automatic performance optimization are still possible through building libraries of subprograms on top of PARRAY. the case study on cluster FFT illustrates a simple 30-line code that 2x-outperforms Intel Cluster MKL on the Tianhe-1A system with 7168 Fermi GPUs and 14336 CPUs.

关键词： Languages Performance theory parallel programming Array Representation Heterogeneous parallelism GPU Clusters

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