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Beyond parallel programming with domain specific languages 14

Beyond parallel programming with domain specific languages

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proceedings of the 19th acm sigplan symposium on principles and practice of parallel programming

作者： Kunle Olukotun Stanford University Stanford CA USA

ISBN: (纸本)9781450326568

Today, almost all computer architectures are parallel and heterogeneous; a combination of multiple CPUs, GPUs and specialized processors. this creates a challenging problem for application developers who want to develop high performance programs without the effort required to use low-level, architecture specific parallel programming models (e.g. OpenMP for CMPs, CUDA for GPUs, MPI for clusters). Domain-specific languages (DSLs) are a promising solution to this problem because they can provide an avenue for high-level application-specific abstractions with implicit parallelism to be mapped directly to low level architecture-specific programming models; providing both high programmer productivity and high execution *** this talk I will describe an approach to building high performance DSLs, which is based on DSL embedding in a general purpose programming language, metaprogramming and a DSL infrastructure called Delite. I will describe how we transform DSL programs into efficient first-order low-level code using domain specific optimization, parallelism and locality optimization with parallel patterns, and architecture-specific code generation. All optimizations and transformations are implemented in Delite: an extensible DSL compiler infrastucture that significantly reduces the effort required to develop new DSLs. Delite DSLs for machine learning, data querying, graph analysis, and scientific computing all achieve performance competitive with manually parallelized C++ code.

关键词： domain specific languages

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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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Performance portable C++ programming with RAJA 19

Performance portable C++ programming with RAJA

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proceedings of the 24th symposium on principles and practice of parallel programming

作者： David Beckingsale Richard Hornung Tom Scogland Arturo Vargas Lawrence Livermore National Laboratory

ISBN: (纸本)9781450362252

With the rapid change of computing architectures, and variety of programming models; the ability to develop performance portable applications has become of great importance. this is particularly true in large production codes where developing and maintaining hardware specific versions is *** simplify the development of performance portable code, we introduce RAJA, our C++ library that allows developers to write single-source applications that can target multiple hardware and programming model back-ends. We provide a thorough introduction to all of RAJA features, and walk through some hands-on examples that will allow attendees to understand how RAJA might benefit their own applications. Attendees should bring a laptop computer to participate in the hands-on *** tutorial will introduce attendees to RAJA, a C++ library for developing performance portable applications. Attendees will learn how to write performance portable code that can execute on a range of programming models (OpenMP, CUDA, Intel TBB, and HCC) and hardware (CPU, GPU, Xeon Phi).Specifically, attendees will learn how to convert existing C++ applications to use RAJA, and how to use RAJA's programming abstractions to expose existing parallelism in their applications without complex algorithm rewrites. We will also cover specific guidelines for using RAJA in a large application, including some common "gotchas" and how to handle memory management. Finally, attendees will learn how to categorize loops to allow for simple and systematic performance tuning on any architecture.

关键词： parallel programming

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Efficient pseudorecursive evaluation schemes for non-adaptive sparse grids 1

引用

2nd Workshop on Sparse Grids and Applications, SGA 2012

作者： Buse, Gerrit Pflüger, Dirk Jacob, Riko TU München München Germany Institute for Parallel and Distributed Systems Universität Stuttgart Stuttgart Germany ETH Zurich Zurich Switzerland

ISBN: (数字)9783319045375

ISBN: (纸本)9783319045368

In this work we propose novel algorithms for storing and evaluating sparse grid functions, operating on regular (not spatially adaptive), yet potentially dimensionally adaptive grid types. Besides regular sparse grids our approach includes truncated grids, both with and without boundary grid points. Similar to the implicit data structures proposed in Feuersänger (Dünngitterverfahren für hochdimensionale elliptische partielle Differntialgleichungen. Diploma thesis, Institut für Numerische Simulation, Universität Bonn, 2005) and Murarasu et al. (proceedings of the 16th acm symposium on principles and practice of parallel programming. Cambridge University Press, New York, 2011, pp. 25–34) we also define a bijective mapping from the multi-dimensional space of grid points to a contiguous index, such that the grid data can be stored in a simple array without overhead. Our approach is especially well-suited to exploit all levels of current commodity hardware, including cache-levels and vector extensions. Furthermore, this kind of data structure is extremely attractive for today’s real-time applications, as it gives direct access to the hierarchical structure of the grids, while outperforming other common sparse grid structures (hash maps, etc.) which do not match with modern compute platforms that well. For dimensionality d ≤10 we achieve good speedups on a 12 core Intel Westmere-EP NUMA platform compared to the results presented in Murarasu et al. (proceedings of the International Conference on Computational Science—ICCS 2012. Procedia Computer Science, 2012). As we show, this also holds for the results obtained on Nvidia Fermi GPUs, for which we observe speedups over our own CPU implementation of up to 4.5 when dealing with moderate dimensionality. In high-dimensional settings, in the order of tens to hundreds of dimensions, our sparse grid evaluation kernels on the CPU outperform any other known implementation. © Springer International Publishing Switzerland 2014.

关键词： parallel programming

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the Z-polyhedral model 07

The Z-polyhedral model

引用

proceedings of the 12th acm sigplan symposium on principles and practice of parallel programming

作者： Gautam Gupta Sanjay Rajopadhye Colorado State University Fort Collins CO and INRIA-Rennes France Colorado State University Fort Collins CO

ISBN: (纸本)9781595936028

the polyhedral model is a well developed formalism and has been extensively used in a variety of contexts viz. the automatic parallelization of loop programs, program verification, locality, hardware generationand more recently, in the automatic reduction of asymptotic program complexity. Such analyses and transformations rely on certain closure properties. However, the model is limited in expressivity and the need for a more general class of programs is widely *** provide the extension to ⁰-polyhedra which are the intersection of polyhedra and lattices. We prove the required closure properties using a novel representation and interpretation of ⁰-polyhedra. In addition, we also prove closure in the ⁰-polyhedral model under images by dependence functions---thereby proving that unions of LBLs, widely assumedto be a richer class of sets, is equal to unions of ⁰-polyhedra. Another corollary of this result is the equivalence of the unions of ⁰-polyhedraand Presburger sets. Our representation and closure properties constitute the foundations of the ⁰-polyhedral model. As an example, we presentthe transformation for automatic reduction of complexity in the ⁰-polyhedral model.

关键词： program transformation models of computations loop optimization equational programming

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GPU initiated OpenSHMEM: correct and efficient intra-kernel networking for dGPUs 20

GPU initiated OpenSHMEM: correct and ef...

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proceedings of the 25th acm sigplan symposium on principles and practice of parallel programming

作者： Khaled Hamidouche Michael LeBeane Advanced Micro Devices Inc.

ISBN: (纸本)9781450368186

Current state-of-the-art in GPU networking utilizes a host-centric, kernel-boundary communication model that reduces performance and increases code complexity. To address these concerns, recent works have explored performing network operations from within a GPU kernel itself. However, these approaches typically involve the CPU in the critical path, which leads to high latency and inefficient utilization of network and/or GPU *** this work, we introduce GPU Initiated OpenSHMEM (GIO), a new intra-kernel PGAS programming model and runtime that enables GPUs to communicate directly with a NIC without the intervention of the CPU. We accomplish this by exploring the GPU's coarse-grained memory model and correcting semantic mismatches when GPUs wish to directly interact with the network. GIO also reduces latency by relying on a novel template-based design to minimize the overhead of initiating a network operation. We illustrate that for structured applications like a Jacobi 2D stencil, GIO can improve application performance by up to 40% compared to traditional kernel-boundary networking. Furthermore, we demonstrate that on irregular applications like Sparse Triangular Solve (SpTS), GIO provides up to 44% improvement compared to existing intra-kernel networking schemes.

关键词： distributed programming models RDMA networks GPUs

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21st century computer architecture 14

21st century computer architecture

引用

proceedings of the 19th acm sigplan symposium on principles and practice of parallel programming

作者： Mark D. Hill University of Wisconsin - Madison Madison WI USA

ISBN: (纸本)9781450326568

this talk has two parts. the first part will discuss possible directions for computer architecture research, including architecture as infrastructure, energy first, impact of new technologies, and cross-layer opportunities. this part is based on a 2012 Computing Community Consortium (CCC) whitepaper effort led by Hill, as well as other recent National Academy and ISAT studies. See: http://***/ccc/docs/init/***. the second part of the talk will discuss one or more exam-ples of cross-layer research advocated in the first part. For example, our analysis shows that many "big-memory" server workloads, such as databases, in-memory caches, and graph analytics, pay a high cost for page-based virtual memory: up to 50% of execution time wasted. Via small changes to the operating system (Linux) and hardware (x86-64 MMU), this work reduces execution time these workloads waste to less than 0.5%. the key idea is to map part of a process's linear virtual address space with a new incarnation of segmentation, while providing compatibility by mapping the rest of the virtual address space with pag-ing.

关键词： computer systems performace architechture programming methods new technology energy

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Space and time efficient execution of parallel irregular computations 97

Space and time efficient execution of parallel irregular com...

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

作者： Cong Fu Tao Yang Department of Computer Science University of California Santa Barbara CA

ISBN: (纸本)9780897919067

Solving problems of large sizes is an important goal for parallel machines with multiple CPU and memory resources. In this paper, issues of efficient execution of overhead-sensitive parallel irregular computation under memory constraints are addressed. the irregular parallelism is modeled by task dependence graphs with mixed granularities. the trade-off in achieving both time and space efficiency is investigated. the main difficulty of designing efficient run-time system support is caused by the use of fast communication primitives available on modern parallel architectures. A run-time active memory management scheme and new scheduling techniques are proposed to improve memory utilization while retaining good time efficiency, and a theoretical analysis on correctness and performance is provided. this work is implemented in the context of RAPID system [5] which provides run-time support for parallelizing irregular code on distributed memory machines and the effectiveness of the proposed techniques is verified on sparse Cholesky and LU factorization with partial pivoting. the experimental results on Cray-T3D show that solvable problem sizes can be increased substantially under limited memory capacities and the loss of execution efficiency caused by the extra memory managing overhead is reasonable.

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parallel thinking 09

Parallel thinking

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proceedings of the 14th acm sigplan symposium on principles and practice of parallel programming

作者： Guy E. Blelloch Carnegie Mellon University Pittsburgh PA USA

ISBN: (纸本)9781605583976

Assuming that the multicore revolution plays out the way the microprocessor industry expects, it seems that within a decade most programming will involve parallelism at some level. One needs to ask how this affects the the way we teach computer science, or even how we have people think about computation. With regards to teaching there seem to be three basic choices: (1) we only train a small number of experts in parallel computation who develop a collection of libraries, and everyone else just uses them; (2) we leave our core curriculum pretty much as is, but add some advanced courses on parallelism or perhaps tack on a few lectures at the end of existing courses; or (3) we start teaching parallelism from the start and embed it throughout the curriculum with the idea of getting students to think about parallelism as the most natural form of computation and sequential computation as a special *** talk will examine some of the implications of the third option. It will argue that thinking about parallelism, when treated in an appropriate way, might be as easy or easier that thinking sequentially. A key prerequisite, however, is to identify what the core ideas in parallelism are and how they might be layered and integrated with existing concepts. Another more difficult issue is how to cleanly integrate these ideas among courses. After all much of the success of sequential computation follows from the concept of a random access machine and its ability to serve as a simple, albeit imperfect, interface between programming languages, algorithm analysis, and hardware design. the talk will go through an initial list of some core ideas in parallelism, and an approach to integrating these ideas between parallel algorithms, programming languages, and, to some extent, hardware. this requires, however, moving away from the concept of a machine model as a interface for thinking about computation.

关键词： algorithms education parallelism

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An effective garbage collection strategy for parallel programming languages on large scale distributed-memory machines 97

An effective garbage collection strategy for parallel progra...

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

作者： Kenjiro Taura Akinori Yonezawa Department of Information Science Faculty of Science University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113 Japan

ISBN: (纸本)9780897919067

this paper describes the design and implementation of a garbage collection scheme on large-scale distributed-memory computers and reports various experimental results. the collector is based on the conservative GC library by Boehm & Weiser. Each processor traces local pointers using the GC library while traversing remote pointers by exchanging "mark messages" between processors. It exhibits a promising performance---in the most space-intensive settings we tested, the total collection overhead ranges from 5% up to 15% of the application running time (excluding idle time). We not only examine basic performance figures such as the total overhead or latency of a global collection, but also demonstrate how local collection scheduling strategies affect application performance. In our collector, a local collection is scheduled either independently or synchronously. Experimental results show that the benefit of independent local collections has been overstated in the literature. Independent local collections slowed down application performance to 40%, by increasing the average communication latency. Synchronized local collections exhibit much more robust performance characteristics than independent local collections and the overhead for global synchronization is not significant. Furthermore, we show that an adaptive collection scheduler can select the appropriate local collection strategy based on the application's behavior. the collector has been used in a concurrent object-oriented language ABCL/f and the performance is measured on a large-scale parallel computer (256 processors) using four non-trivial applications written in ABCL/f.

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