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 lib...
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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.
the proceedings contains 21 papers from the Fifthacmsigplansymposium on principles & practice of parallelprogramming PPOPP. Topics discussed include data parallel programs;data libraries;data caches;data acces...
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the proceedings contains 21 papers from the Fifthacmsigplansymposium on principles & practice of parallelprogramming PPOPP. Topics discussed include data parallel programs;data libraries;data caches;data access;distributed and shared memory multiprocessors;dataflow analysis;scheduling;optimization;and synchronization.
作者:
PHILIPPSEN, MICSI
International Computer Science Institute Berkeley CA and Dept. of Informatics University of Karlsruhe
this paper investigates the problem of aligning array data and processes in a distributed-memory implementation. We present complete algorithms for compile-time analysis, the necessary program restructuring, and subse...
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ISBN:
(纸本)9780897917001
this paper investigates the problem of aligning array data and processes in a distributed-memory implementation. We present complete algorithms for compile-time analysis, the necessary program restructuring, and subsequent code-generation, and discuss their complexity. We finally evaluate the practical usefulness by quantitative experiments. the technique presented analyzes complete programs, including branches, loops, and nested parallelism. Alignment is determined with respect to offset, stride, and general ass's relations. Pplacement of both data and processes are computed in a unifying framework based on an extended preference graph and its analysis. Dynamic redistributions are derived. the experimental results are very encouraging. the optimization algorithms implemented in our Modula-2* compiler improved the execution times of the programs by an average over 40% on a MasPar MP-1 with 16384 processors.
It is widely acknowledged in high-performance computing circles that parallel input/output needs substantial improvement in order to make scalable computers truly usable. We present a data storage model that allows pr...
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It is widely acknowledged in high-performance computing circles that parallel input/output needs substantial improvement in order to make scalable computers truly usable. We present a data storage model that allows processors independent access to their own data and a corresponding compilation strategy that integrates data-parallel computation with data distribution for out-of-core problems. Our results compare several communication methods and I/O optimizations using two out-of-core problems, Jacobi iteration and LU factorization.
In this paper, we propose a straightforward solution to the problems of compositional parallelprogramming by using skeletons as the uniform mechanism for structured composition. In our approach parallel programs are ...
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In this paper, we propose a straightforward solution to the problems of compositional parallelprogramming by using skeletons as the uniform mechanism for structured composition. In our approach parallel programs are constructed by composing procedures in a conventional base language using a set of high-level, predefined, functional, parallel computational forms known as skeletons. the ability to compose skeletons provides us withthe essential tools for building further and more complex application-oriented skeletons specifying important aspects of parallel computation. Compared withthe process network based composition approach, such as PCN, the skeleton approach abstracts away the fine details of connecting communication ports to the higher level mechanism of making data distributions conform, thus avoiding the complexity of using lower level ports as the means of interaction. thus, the framework provides a natural integration of the compositional programming approach withthe data parallelprogramming paradigm.
Cilk (pronounced `silk') is a C-based runtime system for multi-threaded parallelprogramming. In this paper, we document the efficiency of the Cilk work-stealing scheduler, both empirically and analytically. We sh...
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Cilk (pronounced `silk') is a C-based runtime system for multi-threaded parallelprogramming. 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.
Data-parallel languages, such as High Performance Fortran, are widely regarded as a promising means for writing portable programs for distributed-memory machines. Novel features of these languages call for the develop...
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Data-parallel languages, such as High Performance Fortran, are widely regarded as a promising means for writing portable programs for distributed-memory machines. Novel features of these languages call for the development of new techniques in both compilers and run-time systems. In this paper, we present an improved algorithm for finding the local memory access sequence in computations involving regular sections of arrays with cyclic(k) distributions. After establishing the fact that regular section indices correspond to elements of an integer lattice, we show how to find a lattice basis that allows for simple and fast enumeration of memory accesses. the complexity of our algorithm is shown to be lower than that of the previous solution for the same problem. In addition, the experimental results demonstrate the efficiency of our method in practice.
Scalable busy-wait synchronization algorithms are essential for achieving good parallel program performance on large scale multiprocessors. Such algorithms include mutual exclusion locks, reader-writer locks, and barr...
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Scalable busy-wait synchronization algorithms are essential for achieving good parallel program performance on large scale multiprocessors. Such algorithms include mutual exclusion locks, reader-writer locks, and barrier synchronization. Unfortunately, scalable synchronization algorithms are particularly sensitive to the effects of multiprogramming: their performance degrades sharply when processors are shared among different applications, or even among processes of the same application. In this paper we describe the design and evaluation of scalable scheduler-conscious mutual exclusion locks, reader-writer locks, and barriers, and show that by sharing information across the kernel/application interface we can improve the performance of scheduler-oblivious implementations by more than an order of magnitude.
For a long time efficient use of parallel computers has been hindered by dependencies introduced in software through low-level implementation practice. In this paper we present a programming environment and language c...
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For a long time efficient use of parallel computers has been hindered by dependencies introduced in software through low-level implementation practice. In this paper we present a programming environment and language called Object-Math (Object oriented Mathematical language for scientific computing), which aims at eliminating this problem by allowing the user to represent mathematical equation-based models directly in the system. the system performs analysis of mathematical models to extract parallelism and automatically generates parallel code for numerical solution. In the context of industrial applications in mechanical analysis, we have so far primarily explored generation of parallel code for solving systems of ordinary differential equations (ODEs), in addition to preliminary work on generating code for solving partial differential equations. Two approaches to extracting parallelism have been implemented and evaluated: extracting parallelism at the equation system level and at the single equation level, respectively. We found that for several applications the corresponding systems of equations do not partition well into subsystems. this means that the equation system level approach is of restricted general applicability. thus, we focused on the equation-level approach which yielded significant parallelism for ODE systems solution. For the bearing simulation applications we present here, the achieved speedup is however critically dependent on low communication latency of the parallel computer.
We have modified the C language to support a programming model based on a shared address space with physically distributed memory. Withthis model users can write programs in which the nodes of a massively parallel pr...
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We have modified the C language to support a programming model based on a shared address space with physically distributed memory. Withthis model users can write programs in which the nodes of a massively parallel processor can access remote memory without message passing. AC provides support for distributed arrays as well as pointers to distributed data. Simple array references and pointer dereferencing are sufficient to generate low-overhead remote reads and writes. We have implemented these ideas in a compiler based on the GNU C compiler and targeted at Cray Research's T3D. Initial performance measurements show that AC generates code for remote accesses which is considerably faster than that of the native compiler for structures up to about 16 words in size and virtually equivalent for larger transfers.
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