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Triolet: A programming system that unifies algorithmic skeleton interfaces for high-performance cluster computing 14

Triolet: A programming system that unifies algorithmic skele...

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2014 19th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2014

作者： Rodrigues, Christopher Jablin, thomas Dakkak, Abdul Hwu, Wen-Mei University of Illinois at Urbana-Champaign United States

ISBN: (纸本)9781450326568

Functional algorithmic skeletons promise a high-level programming interface for distributed-memory clusters that free developers from concerns of task decomposition, scheduling, and communication. Unfortunately, prior distributed functional skeleton frameworks do not deliver performance comparable to that achievable in a low-level distributed programming model such as C with MPI and OpenMP, even when used in concert with high-performance array libraries. there are several causes: they do not take advantage of shared memory on each cluster node;they impose a fixed partitioning strategy on input data;and they have limited ability to fuse loops involving skeletons that produce a variable number of outputs per input. We address these shortcomings in the Triolet programming language through a modular library design that separates concerns of parallelism, loop nesting, and data partitioning. We show how Triolet substantially improves the parallel performance of algorithms involving array traversals and nested, variable-size loops over what is achievable in Eden, a distributed variant of Haskell. We further demonstrate how Triolet can substantially simplify parallel programming relative to C with MPI and OpenMP while achieving 23.100% of its performance on a 128-core cluster. Copyright © 2014 acm.

关键词： parallel programming

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parallel Schedule Synthesis for Attribute Grammars 13

Parallel Schedule Synthesis for Attribute Grammars

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18th acm sigplan symposium on principles and practice of parallel programming

作者： Meyerovich, Leo A. Torok, Matthew E. Atkinson, Eric Bodik, Rastislav Univ Calif Berkeley Berkeley CA 94720 USA

ISBN: (纸本)9781450319225

We examine how to synthesize a parallel schedule of structured traversals over trees. In our system, programs are declaratively specified as attribute grammars. Our synthesizer automatically, correctly, and quickly schedules the attribute grammar as a composition of parallel tree traversals. Our downstream compiler optimizes for GPUs and multicore CPUs. We provide support for designing efficient schedules. First, we introduce a declarative language of schedules where programmers may constrain any part of the schedule and the synthesizer will complete and autotune the rest. Furthermore, the synthesizer answers debugging queries about how schedules may be completed. We evaluate our approach with two case studies. First, we created the first parallel schedule for a large fragment of CSS and report a 3X multicore speedup. Second, we created an interactive GPU-accelerated animation of over 100,000 nodes.

关键词： CSS layout sketching attribute grammars scheduling

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Improving parallelism and Locality with Asynchronous Algorithms

Improving Parallelism and Locality with Asynchronous Algorit...

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15th acm sigplan symposium on principles and practice of parallel programming

作者： Liu, Lixia Li, Zhiyuan Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

ISBN: (纸本)9781605587080

As multicore chips become the main building blocks for high performance computers, many numerical applications face a performance impediment due to the limited hardware capacity to move data between the CPU and the off-chip memory. this is especially true for large computing problems solved by iterative algorithms because of the large data set typically used. Loop tiling, also known as loop blocking, was shown previously to be an effective way to enhance data locality, and hence to reduce the memory bandwidth pressure, for a class of iterative algorithms executed on a single processor. Unfortunately, the tiled programs suffer from reduced parallelism because only the loop iterations within a single tile can be easily parallelized. In this work, we propose to use the asynchronous model to enable effective loop tiling such that both parallelism and locality can be attained simultaneously. Asynchronous algorithms were previously proposed to reduce the communication cost and synchronization overhead between processors. Our new discovery is that carefully controlled asynchrony and loop tiling can significantly improve the performance of parallel iterative algorithms on multicore processors due to simultaneously attained data locality and loop-level parallelism. We present supporting evidence from experiments with three well-known numerical kernels.

关键词： asynchronous algorithms loop tiling parallel numerical programs data locality memory performance

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Space-efficient implementation of nested parallelism

Space-efficient implementation of nested parallelism

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proceedings of the 1997 6th acm sigplan symposium on principles and practice of parallel programming

作者： Narlikar, Girija J. Blelloch, Guy E. CMU Sch of Computer Science Pittsburgh United States

Many of today's high level parallel languages support dynamic, fine-grained parallelism. these languages allow the user to expose all the parallelism in the program, which is typically of a much higher degree than the number of processors. Hence an efficient scheduling algorithm is required to assign computations to processors at runtime. Besides having low overheads and good load balancing, it is important for the scheduling algorithm to minimize the space usage of the parallel program. this paper presents a scheduling algorithm that is provably space-efficient and time-efficient for nested parallel languages. In addition to proving the space and time bounds of the parallel schedule generated by the algorithm, we demonstrate that it is efficient in practice. We have implemented a runtime system that uses our algorithm to schedule parallel threads. the results of executing parallel programs on this system show that our scheduling algorithm significantly reduces memory usage compared to previous techniques, without compromising performance.

关键词： parallel processing systems

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Conference Record of the Annual acm symposium on principles of programming Languages

Conference Record of the Annual ACM Symposium on Principles ...

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5th acm SIGACT-sigplan symposium on principles of programming Languages, POPL 1978

the proceedings contain 25 papers. the topics discussed include: compilation and delayed evaluation in apl;the smalltalk-76 programming system design and implementation;clauses: scope structures and defined functions in lucid;data types as values: polymorphism, type-checking, encapsulation?;type definitions with parameters;syntactic control of interference;monoids for rapid data flow analysis;a general scheme for the automatic inference of variable types;symbolic program analysis in almost linear time;automatic discovery of linear restraints among variables of a program;a portable compiler: theory and practice;and automating proofs of the absence of common runtime errors.

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Backtracking-based Load Balancing

Backtracking-based Load Balancing

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

作者： Hiraishi, Tasuku Yasugi, Masahiro Umatani, Seiji Yuasa, Taiichi Kyoto Univ Acad Ctr Comp & Media Studies Kyoto 6068501 Japan Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan

ISBN: (纸本)9781605583976

High-productivity languages for parallel computing become more important as parallel environments including multicores become more common. Cilk is such a language. It provides good load balancing for many applications including irregular ones;that is, it keeps all workers busy by creating plenty of "logical" threads and adopting the oldest-first work stealing strategy. this paper proposes a "logical thread"-free framework called Tascell, which achieves a higher performance and supports a wider range of parallel environments including clusters without loss of productivity. A Tascell worker spawns a "real" task only when requested by another idle worker. the worker performs the spawning by temporarily "backtracking" and restoring its oldest task-spawnable state. Our approach eliminates the cost of spawning/managing logical threads. It also promotes the reuse of workspaces and improves the locality of reference since it does not need to prepare a workspace for each concurrently runnable logical thread. Furthermore, Tascell enables elegant and highly-efficient backtrack search algorithms with delayed workspace copying. For instance, our 16-queens problem solver is 1.86 times faster than Cilk on a system with two dual-core processors. Our approach also enables a single program to run in both shared and distributed memory environments with reasonable efficiency and scalability.

关键词： Design Languages Performance load balancing parallel computing backtracking backtrack search

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PARRAY: A Unifying Array Representation for Heterogeneous parallelism 12

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

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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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Multi-Level parallel Computing of Reverse Time Migration for Seismic Imaging on Blue Gene/Q 13

Multi-Level Parallel Computing of Reverse Time Migration for...

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18th acm sigplan symposium on principles and practice of parallel programming

作者： Lu, Ligang Magerlein, Karen IBM Watson Res Ctr Yorktown Hts NY USA

ISBN: (纸本)9781450319225

Blue Gene/Q (BG/Q) is an early representative of increasing scale and thread count that will characterize future HPC systems: large counts of nodes, cores, and threads; and a rich programming environment with many degrees of freedom in parallel computing optimization. So it is both a challenge and an opportunity to it to accelerate the seismic imaging applications to the unprecedented levels that will significantly advance the technologies for the oil and gas industry. In this work we aim to address two important questions: how HPC systems with high levels of scale and thread count will perform in real applications; and how systems with many degrees of freedom in parallel programming can be calibrated to achieve optimal performance. Based on BG/Q's architecture features and RTM workload characteristics, we developed massive domain partition, MPI , and SIMD Our detailed deep analyses in various aspects of optimization also provide valuable experience and insights into how can be utilized to facilitate the advance of seismic imaging technologies. Our BG/Q RTM solution achieved a 14.93x speedup over the BG/P implementation. Our multi-level parallelism strategies for Reverse Time Migration (RTM) seismic imaging computing on BG/Q provides an example of how HPC systems like BG/Q can accelerate applications to a new level.

关键词： Multi-level parallelism parallel Computing High Performance Computing Performance Optimization Reverse Time Migration Seismic Imaging

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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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Effective Performance Measurement and Analysis of Multithreaded Applications

Effective Performance Measurement and Analysis of Multithrea...

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

作者： Tallent, Nathan R. Mellor-Crummey, John M. Rice Univ Houston TX 77251 USA

ISBN: (纸本)9781605583976

Understanding why the performance of a multithreaded program does not improve linearly with the number of cores in a shared-memory node populated with one or more multicore processors is a problem of growing practical importance. this paper makes three contributions to performance analysis of multithreaded programs. First, we describe how to measure and attribute parallel idleness, namely, where threads are stalled and unable to work. this technique applies broadly to programming models ranging from explicit threading (e. g., Pthreads) to higher-level models such as Cilk and OpenMP. Second, we describe how to measure and attribute parallel overhead-when a thread is performing miscellaneous work other than executing the user's computation. By employing a combination of compiler support and post-mortem analysis, we incur no measurement cost beyond normal profiling to glean this information. Using idleness and overhead metrics enables one to pinpoint areas of an application where concurrency should be increased (to reduce idleness), decreased (to reduce overhead), or where the present parallelization is hopeless (where idleness and overhead are both high). third, we describe how to measure and attribute arbitrary performance metrics for high-level multithreaded programming models, such as Cilk. this requires bridging the gap between the expression of logical concurrency in programs and its realization at run-time as it is adaptively partitioned and scheduled onto a pool of threads. We have prototyped these ideas in the context of Rice University's HPCTOOLKIT performance tools. We describe our approach, implementation, and experiences applying this approach to measure and attribute work, idleness, and overhead in executions of Cilk programs.

关键词： Performance Measurement Algorithms Performance Analysis Call Path Profiling Multithreaded programming Models HPCTOOLKIT

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