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DATA-FLOW EQUATIONS FOR EXPLICITLY parallel PROGRAMS 93

DATA-FLOW EQUATIONS FOR EXPLICITLY PARALLEL PROGRAMS

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4th SYMP ON principles AND practice OF parallel programming ( PPOPP )

作者： GRUNWALD, D SRINIVASAN, H UNIV COLORADO DEPT COMP SCIBOULDERCO 80309

ISBN: (纸本)9780897915892

We present a solution to the reaching definitions problem for programs with explicit lexically specified parallel constructs, such as cobegin/coend or parallel-sections, both with and without explicit synchronization operations, such as Post, Wait or Advance. the reaching definitions information for sequential programs is used to solve many standard optimization problems. In parallel programs, this information can also be used to explicitly direct communication and data ownership. Although work has been done on analyzing parallel programs to detect data races, little work has been done on optimizing such programs. We show how the memory consistency model specified by an explicitly parallel programming language can influence the complexity of the reaching definitions problem. By selecting the ''weakest'' memory consistency semantics, we can efficiently solve the reaching definitions problem for correct programs.

关键词： Computer software

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Cilk: An efficient multithreaded runtime system

Cilk: An efficient multithreaded runtime system

引用

proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Blumofe, Robert D. Joerg, Christopher F. Kuszmaul, Bradley C. Leiserson, Charles E. Randall, Keith H. Zhou, Yuli MIT Lab for Computer Science Cambridge United States

Cilk (pronounced `silk') is a C-based runtime system for multi-threaded parallel programming. In this paper, we document the efficiency of the Cilk work-stealing scheduler, both empirically and analytically. We show that on real and synthetic applications, the `work' and `critical path' of a Cilk computation can be used to accurately model performance. Consequently, a Cilk programmer can focus on reducing the work and critical path of his computation, insulated from load balancing and other runtime scheduling issues. We also prove that for the class of `fully strict' (well-structured) programs, the Cilk scheduler achieves space, time, and communication bounds all within a constant factor of optimal. the Cilk runtime system currently runs on the Connection Machine CM5 MPP, the Intel Paragon MPP, the Silicon Graphics Power Challenge SMP, and the MIT Phish network of workstations. Applications written in Cilk include protein folding, graphic rendering, backtrack search, and the Socrates chess program, which won third prize in the 1994 acm International Computer Chess Championship.

关键词： parallel processing systems

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Flattening and parallelizing irregular, recurrent loop nests 95

Flattening and parallelizing irregular, recurrent loop nests

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proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Ghuloum, Anwar M. Fisher, Allan L. Carnegie Mellon Univ Pittsburgh PA United States

ISBN: (纸本)9780897917001

Irregular loop nests in which the loop bounds are determined dynamically by indexed arrays are difficult to compile into expressive parallel constructs, such as segmented scans and reductions. In this paper, we describe a suite of transformations to automatically parallelize such irregular loop nests, even in the presence of recurrences. We describe a simple, general loop flattening transformation, along with new optimizations which make it a viable compiler transformation. A robust recurrence parallelization technique is coupled to the loop flattening transformation, allowing parallelization of segmented reductions, scans, and combining-sends over arbitrary associative operators. We discuss the implementation and performance results of the transformations in a parallelizing Fortran 77 compiler for the Cray C90 supercomputer. In particular, we focus on important sparse matrix-vector multiplication kernels, for one of which we are able to automatically derive an algorithm used by one of the fastest library routines available.

关键词： parallel processing systems

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StreamScan: Fast Scan Algorithms for GPUs without Global Barrier Synchronization 13

StreamScan: Fast Scan Algorithms for GPUs without Global Bar...

引用

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

作者： Yan, Shengen Long, Guoping Zhang, Yunquan Chinese Acad Sci Inst Software Lab Parallel Software & Computat Sci Beijing 100864 Peoples R China Chinese Acad Sci State Key Lab Comp Sci Beijing 100864 Peoples R China Chinese Acad Sci Grad Univ Beijing 100864 Peoples R China

ISBN: (纸本)9781450319225

Scan (also known as prefix sum) is a very useful primitive for various important parallel algorithms, such as sort, BFS, SpMV, compaction and so on. Current state of the art of GPU based scan implementation consists of three consecutive Reduce-Scan-Scan phases. this approach requires at least two global barriers and 3N (N is the problem size) global memory accesses. In this paper we propose StreamScan, a novel approach to implement scan on GPUs with only one computation phase. the main idea is to restrict synchronization to only adjacent workgroups, and thereby eliminating global barrier synchronization completely. the new approach requires only 2N global memory accesses and just one kernel invocation. On top of this we propose two important optimizations to further boost performance speedups, namely thread grouping to eliminate unnecessary local barriers, and register optimization to expand the on chip problem size. We designed an auto-tuning framework to search the parameter space automatically to generate highly optimized codes for both AMD and Nvidia GPUs. We implemented our technique with OpenCL. Compared with previous fast scan implementations, experimental results not only show promising performance speedups, but also reveal dramatic different optimization tradeoffs between Nvidia and AMD GPU platforms.

关键词： Scan prefix-sum OpenCL CUDA GPU parallel algorithms

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Array operation synthesis scheme to optimize Fortran 90 programs

Array operation synthesis scheme to optimize Fortran 90 prog...

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proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Hwang, Gwan-Hwan Lee, Jenq Kuen Ju, Dz-Ching Natl Tsing-Hua Univ Taiwan

An increasing number of programming languages, such as Fortran 90 and APL, are providing a rich set of intrinsic array functions and array expressions. these constructs which constitute an important part of data parallel languages provide excellent opportunities for compiler optimizations. In this paper, we present a new approach to combine consecutive data access patterns of array constructs into a composite access function to the source arrays. Our scheme is based on the composition of access functions, which is similar to a composition of mathematic functions. Our new scheme can handle not only data movements of arrays of different numbers of dimensions and segmented array operations but also masked array expressions and multiple sources array operations. As a result, our proposed scheme is the first synthesis scheme which can synthesize Fortran 90 RESHAPE, EOSHIFT, MERGE, and WHERE constructs together. Experimental results show speedups from 1.21 to 2.95 for code fragments from real applications on a Sequent multiprocessor machine by incorporating the proposed optimizations.

关键词： FORTRAN (programming language)

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Impala: a middleware system for managing autonomic, parallel sensor systems 03

Impala: a middleware system for managing autonomic, parallel...

引用

9th acm sigplan symposium on principles and practice of parallel programming

作者： Liu, T Martonosi, M Princeton Univ Dept Comp Sci Princeton NJ 08544 USA Princeton Univ Dept Elect Engn Princeton NJ 08544 USA

ISBN: (纸本)9781581135886

Sensor networks are long-running computer systems with many sensing/compute nodes working to gather information about their environment, process and fuse that information, and in some cases, actuate control mechanisms in response. Like traditional parallel systems, communication between nodes is of fundamental importance, but is typically accomplished via wireless transceivers. One further key attribute of sensor networks is that they are almost always long-running systems, intended to operate in situ, with minimal direct human intervention, for months or years. this requirement for long-running autonomy mandates careful design of the runtime system that manages applications on each node, to ensure reliability and ease of upgrades over the life of the system. this paper describes Impala, a middleware architecture that enables application modularity, adaptivity, and repair-ability in wireless sensor networks. Impala allows software updates to be received via the node's wireless transceiver and to be applied to the running system dynamically. In addition, Impala also provides an interface for on-the-fly application adaptation in order to improve the performance, energy-efficiency, and reliability of the software system. Impala has been designed to be a part of the ZebraNet mobile sensor network, but we are also prototyping it within HP/Compaq iPAQ Pocket PC handhelds. We present performance data for both real system measurements of the Pocket PC version as well as simulations of a full mobile sensor system deployment. Overall, Impala is a lightweight runtime system that can greatly improve system reliability, performance, and energy-efficiency. the ideas introduced here for sensor networks have applicability more broadly in other long-running autonomous parallel systems as well.

关键词： design experimentation performance sensor networks middleware system software adaptation software update

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Well-structured futures and cache locality 14

Well-structured futures and cache locality

引用

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

作者： Herlihy, Maurice Liu, Zhiyu Computer Science Department Brown University United States

ISBN: (纸本)9781450326568

In fork-join parallelism, a sequential program is split into a directed acyclic graph of tasks linked by directed dependency edges, and the tasks are executed, possibly in parallel, in an order consistent with their dependencies. A popular and effective way to extend fork-join parallelism is to allow threads to create futures. A thread creates a future to hold the results of a computation, which may or may not be executed in parallel. that result is returned when some thread touches that future, blocking if necessary until the result is ready. Recent research has shown that while futures can, of course, enhance parallelism in a structured way, they can have a deleterious effect on cache locality. In the worst case, futures can incur Ω(PT ∞ +tT∞) deviations, which implies Ω(CPT∞+CtT∞) additional cache misses, where C is the number of cache lines, P is the number of processors, t is the number of touches, and T∞ is the computation span. Since cache locality has a large impact on software performance on modern multicores, this result is troubling. In this paper, however, we show that if futures are used in a simple, disciplined way, then the situation is much better: if each future is touched only once, either by the thread that created it, or by a later descendant of the thread that created it, then parallel executions with work stealing can incur at most O(CPT2∞ ) additional cache misses, a substantial improvement. this structured use of futures is characteristic of many (but not all) parallel applications. Copyright © 2014 acm.

关键词： parallel programming

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A framework for practical parallel fast matrix multiplication 2015

A framework for practical parallel fast matrix multiplicatio...

引用

20th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2015

作者： Benson, Austin R. Ballard, Grey Institute for Computational and Mathematical Engineering Stanford University StanfordCA United States Sandia National Laboratories LivermoreCA United States

ISBN: (纸本)9781450332057

Matrix multiplication is a fundamental computation in many scientific disciplines. In this paper, we show that novel fast matrix multiplication algorithms can significantly outperform vendor implementations of the classical algorithm and Strassen's fast algorithm on modest problem sizes and shapes. Furthermore, we show that the best choice of fast algorithm depends not only on the size of the matrices but also the shape. We develop a code generation tool to automatically implement multiple sequential and shared-memory parallel variants of each fast algorithm, including our novel parallelization scheme. this allows us to rapidly benchmark over 20 fast algorithms on several problem sizes. Furthermore, we discuss a number of practical implementation issues for these algorithms on shared-memory machines that can direct further research on making fast algorithms practical. Copyright 2015 acm.

关键词： Matrix algebra

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Griffin: Uniting CPU and GPU in Information Retrieval Systems for Intra-Query parallelism 18

Griffin: Uniting CPU and GPU in Information Retrieval System...

引用

23rd acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Liu, Yang Wang, Jianguo Swanson, Steven WDC Res Chippenham Wilts England Univ Calif San Diego San Diego CA USA

ISBN: (纸本)9781450349826

Interactive information retrieval services, such as enterprise search and document search, must provide relevant results with consistent, low response times in the face of rapidly growing data sets and query loads. these growing demands have led researchers to consider a wide range of optimizations to reduce response latency, including query processing parallelization and acceleration with co-processors such as GPUs. However, previous work runs queries either on GPU or CPU, ignoring the fact that the best processor for a given query depends on the query's characteristics, which may change as the processing proceeds. We present Griffin, an IR systems that dynamically combines GPU- and CPU-based algorithms to process individual queries according to their characteristics. Griffin uses state-of-the-art CPU-based query processing techniques and incorporates a novel approach to GPU-based query evaluation. Our GPU-based approach, as far as we know, achieves the best available GPU search performance by leveraging a new compression scheme and exploiting an advanced merge-based intersection algorithm. We evaluate Griffin with real world queries and datasets, and show that it improves query performance by 10x compared to a highly optimized CPU-only implementation, and 1.5x compared to our GPU-approach running alone. We also find that Griffin helps reduce the 95th-, 99th-, and 99.9th-percentile query response time by 10.4x, 16.1x, and 26.8x, respectively.

关键词： Information Retrieval Search Engines Query Processing GPU parallel Algorithms

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Helper Locks for Fork-Join parallel programming

Helper Locks for Fork-Join Parallel Programming

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

作者： Agrawal, Kunal Leiserson, Charles E. Sukha, Jim Washington Univ St Louis MO 63130 USA

ISBN: (纸本)9781605587080

Helper locks allow programs with large parallel critical sections, called parallel regions, to execute more efficiently by enlisting processors that might otherwise be waiting on the helper lock to aid in the execution of the parallel region. Suppose that a processor p is executing a parallel region A after having acquired the lock L protecting A. If another processor p' tries to acquire L, then instead of blocking and waiting for p to complete A, processor p' joins p to help it complete A. Additional processors not blocked on L may also help to execute A. the HELPER runtime system can execute fork-join computations augmented with helper locks and parallel regions. HELPER supports the unbounded nesting of parallel regions. We provide theoretical completion-time and space-usage bounds for a design of HELPER based on work stealing. Specifically, let V be the number of parallel regions in a computation, let T-1 be its work, and let (T) over tilde (infinity) be its "aggregate span" - the sum of the spans (critical-path lengths) of all its parallel regions. We prove that HELPER completes the computation in expected time O(T-1/P + (T) over tilde (infinity) + PV) on P processors. this bound indicates that programs with a small number of highly parallel critical sections can attain linear speedup. For the space bound, we prove that HELPER completes a program using only O(P (S) over tilde (1)) stack space, where e (S) over tilde (1) is the sum, over all regions, of the stack space used by each region in a serial execution. Finally, we describe a prototype of HELPER implemented by modifying the Cilk multithreaded runtime system. We used this prototype to implement a concurrent hash table with a resize operation protected by a helper lock.

关键词： Algorithms Performance theory Cilk fork-join multithreading helper lock nested parallelism parallel region scheduling work stealing

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